MBA Notes Knowledge Management

MBA (DISTANCE MODE)

DBA 1735 KNO WLEDGE MAN AGEMENT KNOWLEDGE MANA

IV SEMESTER COURSE MATERIAL

Centre for Distance Education Anna University Chennai Chennai – 600 025

Author Dr AP ATHI Dr.. R. SEN SENAP APA Professor and Head Department of Management Studies Adhiparasakthi Engineering College Melmaruvathur – 603 319

Reviewer DR.T .V .GEETHA DR.T.V .V.GEETHA Professor Department of Computer Science and Engineering Anna University Chennai Chennai – 600 025

Editorial Board Dr .T .V .Geetha Dr.T .T.V .V.Geetha

Dr .H.P eer u Mohamed Dr.H.P .H.Peer eeru

Professor Department of Computer Science and Engineering Anna University Chennai Chennai - 600 025

Professor Department of Management Studies Anna University Chennai Chennai - 600 025

Dr .C ppan Dr.C .C.. Chella Chellappan

Dr .A.K annan Dr.A.K .A.Kannan



Copyrights Reserved (For Private Circulation only) ii

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ACKNOWLEDGEMENT

The author has drawn inputs from several sources for the preparation of this course material, to meet the requirements of the syllabus. The author gratefully acknowledges the following sources: 1. Knowledge Management-Classic and Contemporary Works, Edited by Daryl Morey, Mark Maybury and Bhavani Thuraisingham, Universities Press, Hyderabad, Reprint Edition, 2007. 2. Knowledge Management for Competitive Advantage by Harish Chandra Chaudhary, Excel Books, First Edition, 2005. 3. Knowledge Management Tools and Techniques, edited by Madanmohan Rao, Butterworth-Heinemann, An imprint of Elsevier, Oxford, UK, 2005. 4. Unleashing the Knowledge Force, by Ganesh Natarajn and Uma Ganesh, Tata McGraw-Hill, First Reprint, New Delhi, 2007. 5. Knowledge Management by Sudhir Warier, Vikas Publishing House Pvt Ltd, Second Reprint Edition, Noida, 2007. 6. Knowledge Management-Design and Implementation Edited by Tapas Mahapatra and Shalini Khandelwal, The ICFAI University Press, Hyderabad, First Edition, 2005. 7. Knowledge Management by Shelda Debowski, John Wiley & Sons Australia Ltd, First Edition, 2006. 8. Knowledge Management for Business Strategy Edited by N.M.Shanthi, The ICFAI University Press, Hyderabad, First Edition, 2006. 9. The Knowledge Management Toolkit by Amrit Tiwana, Pearson Education, Second Edition, New Delhi, 2006. 10. Knowledge Management Edited by Nasreen Taher, The ICFAI University Press, Hyderabad, First Edition, 2005. 11. Knowledge Management by Elias M. Awad and Hassan M. Ghaziri, Pearson Education, Delhi, Second Impression, 2008. Inspite of at most care taken to prepare the list of references any omission in the list is only accidental and not purposeful. Dr. R. SENAPATHI Author

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DBA 1735 KNOWLEDGE MANAGEMENT

UNIT I INTRODUCTION Knowledge Economy – Technology and Knowledge Management – Knowledge Management Matrix – Knowledge Management Strategy – Prioritizing knowledge strategies – knowledge as a strategic asset. UNIT II KNOWLEDGE ACQUISITION AND PROCESSING Knowledge Attributes – Fundamentals of knowledge formation – Tacit and Explicit knowledge – Knowledge sourcing, abstraction, conversion and diffusion. UNIT III KNOWLEDGE MANAGEMENT SYSTEMS Knowledge Management and organizational learning, architecture – important considerations – collection and codification of knowledge – Repositories, structure and life cycle – Knowledge Management infrastructure – Knowledge Management applications – Collaborative platforms. UNIT IV KNOWLEDGE CULTURE IN ORGANISATIONS Developing and sustaining knowledge culture – Knowledge culture enablers – implementing knowledge culture enhancement programs – Communities of practice – Developing organizational memory. UNIT V KNOWLEDGE MANAGEMENT – LOOKING AHEAD Knowledge Management tools, techniques – Knowledge Management and measurements – Knowledge audit – Knowledge careers – Practical implementation of Knowledge management systems – Case studies. REFERENCES 1. Key issues in the New Knowledge Management –Joseph M. Firestone and Mark W. McElroy, Butterworth – Hienemann. 2. Knowledge Management – Classic and contemporary works Edited by Daryl Morey & others Universities Press India Private Limited. 3. Knowledge Management, Shelda Debowski, John Wiley & Sons. 4. Knowledge Management, Sudhir Warier,Vikas Publishing House Private Limited. 5. Knowledge Management System Theory and practice,Edited by Stwart Barnes Thomson Learning. 6. Handbook on knowledge management,Edited by CW. Hol Sapple Springer. vii

CONTENTS UNIT I OVERVIEW OF KNOWLEDGE MANAGEMENT 1.1. 1.2. 1.3.

INTRODUCTION LEARNING OBJECTIVES THE CONCEPT OF KNOWLEDGE MANAGEMENT 1.3.1 Definitions of knowledge management 1.3.2 Objectives of knowledge management 1.3.3 Motivation for knowledge management 1.3.4 Knowledge management cycle 1.3.5 Domains of knowledge management 1.3.6 Uses of knowledge management 1.3.7 Nature of knowledge management 1.4. DICIPLINES OF KNOWLEDGE MANAGEMENT 1.5. EVOLUTIONS OF KNOWLEDGE MANGEMENT 1.6. SHORT HISTORY OF KNOWLEDGE MANGEMENT 1.7. AREAS FOR RESEARCH IN KNOWLEDGE MANAGEMENT 1.8. KNOWLEDGE ECONOMY 1.8.1 Background of knowledge management 1.8.2 What is knowledge economy? 1.8.3 Impact of knowledge in the knowledge economy 1.8.4 Characteristics of knowledge economy 1.8.5 Key drivers of knowledge economy 1.8.6 Growth of IT industry in knowledge economy 1.8.7 Implications of knowledge economy 1.9. INDIA AS A KNOWLWEDGE ECONOMY 1.10. TECHNOLOGY AND KNOWLEDGE MANAGEMENT 1.10.1 Electronic technology for knowledge management 1.10.2 Information technology for knowledge management 1.10.3 Knowledge management technology 1.11. KNOWLEDGE MANAGEMENT MATRIX ix

1 2 2 3 5 6 8 9 11 12 13 14 15 16 19 21 21 22 23 23 25 26 27 28 29 31 32 37

1.12.

1.13. 1.14.

KNOWLEDGE MANAGEMENT STRATEGY 1.12.1 The need for knowledge management strategy 1.12.2 Development of organizational KM strategy PRIORITISING KNOWLEDGE STRATEGIES KNOWLEDGE AS A STRATEGIC ASSET 1.14.1. Asset value of knowledge

38 38 39 40 41 43

UNIT II KNOWLEDGE ACQUISITION AND PROCESSING 2.1 2.2 2.3

2.4 2.5

2.6 2.7

2.8

INTRODUCTION LEARNING OBJECTIVES PERSPECTIVES ON KNOWLEDGE 2.3.1 Data, Information and knowledge 2.3.2. Defining knowledge KNOWLEDGE ATTRIBUTES FUNDAMENTALS OF KNOWLEDGE FORMATION 2.5.1 Knowledge formation 2.5.2 Flows of knowledge ORGANISATIONAL KNOWLEDGE TACIT AND EXPLICIT KNOWLEDGE 2.7.1 What is tacit knowledge? 2.7.2. What is explicit knowledge? 2.7.3 Typical application of tacit and explicit knowledge 2.7.4 Basic beliefs between tacit and explicit knowledge approaches 2.7.5 Comparison of properties of tacit Vs explicit knowledge 2.7.6 Advantages and disadvantages of tacit Vs explicit knowledge approaches 2.7.7 Four modes of knowledge conversion ORGANISATIONAL KNOWLEDGE CREATION 2.8.1 Knowledge sourcing 2.8.2 Knowledge abstraction 2.8.3 Knowledge conversion 2.8.4 Knowledge diffusion 2.8.5 Knowledge development and refinement

x

47 47 47 48 51 51 53 53 53 54 56 56 59 62 62 62 63 64 65 66 68 69 69 69

UNIT III KNOWLEDGE MANAGEMENT SYSTEMS 3.1 3.2 3.3 3.4

3.5 3.6.

3.7

3.8 3.9

3.10 3.11

3.12

INTRODUCTION LEARNING OBJECTIVES KNOWLEDGE MANAGEMENT AND ORGANISATIONAL LEARNING HE CONCEPT OF ORGANISATIONAL LEARNING 3.4.1 Definitions of organizational learning 3.4.2 Benefits of organizational learning 3.4.3. What is learning organizations? 3.4.4 Orientation for effective knowledge dissemination 3.4.5 Characteristics of learning organization 3.4.6 Characteristics of the traditional Vs learning organization 3.4.7 Facilitators of organizational learning 3.4.8 The five learning disciplines ARCHITECTURE FOR ORGANISATIONAL LEARNING CATURING AND CODIFICATION OF KNOWLEDGE 3.6.1 Capturing tacit knowledge 3.6.2 Other knowledge capture techniques KNOWLEDGE CODIFICATION 3.7.1 Codifying knowledge 3.7.2 Codification tools and procedures KNOWLEDGE MANGEMENT INFRASTRUCTURE REPOSITORIES 3.9.1 Content of knowledge repository 3.9.2 Features of knowledge repository 3.9.3 The design of knowledge repository 3.9.4 The knowledge refinery 3.9.5 Repository life cycle 3.9.6 Repository structure KNOWLEDE MANAGEMENT APPLICATIONS COLLABORATIVE PLATFORMS 3.11.1 Features of platforms 3.11.2 Tools for collaborative platform 3.11.3 Collaborative knowledge applications CASE STUDY xi

73 73 73 74 76 77 77 78 81 81 82 82 84 87 88 94 99 100 100 104 110 111 111 112 113 113 114 114 117 118 119 122 123

UNIT IV KNOWLEDGE CULTURE IN ORGANISATION 4.1 4.2 4.3

4.4 4.5 4.6. 4.7.

4.8

INTRODUCTION LEARNING OBJECTIVES ORGANISATIONAL CULTURE 4.3.1 Knowledge cultures 4.3.2 Improving knowledge culture KNOWLEDGE CULTURE ENABLERS IMPLEMENTING KNOWLEDGE CULTURE ENHANCEMENT PROGRAMS MAINTANING THE KNOWLEDGE CULTURE COMMUNITIES OF PRACTICE 4.7.1. Defining communities of practice 4.7.2. Communities of practice in organizations 4.7.3. Importance of communities to organizations 4.7.4. Developing and nurturing communities of practice DEVELOPING ORGANISATIONAL MEMORY

127 129 129 130 131 133 137 139 141 141 142 145 146 149

UNIT V KNOWLEDGE MANAGEMENT - LOOKING AHEAD 5.1 5.2. 5.3.

5.4. 5.5.

INTRODUCTION LEARNING OBJECTIVES KNOWLEDGE MANGEMENT TOOLS AND TECHNIQUES 5.3.1. Knowledge capture and creation tools 5.3.2. Knowledge sharing and dissemination tools 5.3.3. Knowledge acquisition and application tools 5.3.4. Strategic implications of KM tools KNOWLEDGE MANAGENMENT AND MEASUREMENT KNOWLEDGE MEASUREMENT TECHNIQUES 5.5.1. Intangible asset measurement 5.5.2. Intangible asset monitor 5.5.3. IC Rating 5.5.4. Balanced scorecard 5.5.5. Implementation barriers xii

153 154 154 154 159 166 170 171 179 179 181 183 183 187

5.6.

5.7. 5.8.

5.9

KNOWLEDGE AUDIT 5.6.1. Aims and objectives of knowledge audit 5.6.2. Key tasks of K-audit 5.6.3. Process mapping 5.6.4. Outcomes of knowledge audit 5.6.5. Components of knowledge audit KNOWLEDGE CAREERS 5.7.1. Organisational knowledge role classification CLASSIFICATION OF KNOWLEDGE MANAGEMENT CAREERS 5.8.1 The qualities and attributes of CKO 5.8.2 Knowledge management analyst 5.8.3 Knowledge architect 5.8.4. Knowledge strategist 5.8.5. Knowledge manager 5.8.6. Research analyst 5.8.7. KM consultant 5.8.8. Media specialist 5.8.9. Senior market intelligence librarian 5.8.10 Knowledge engineer 5.8.11 KM specialist 5.8.12 Intranet developer 5.8.13 KM director 5.8.14 Director of ontologies 5.8.15 Ontologist 5.8.16 NLP specialist 5.8.17 Knowledge development manager CASE STUDIES

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187 188 189 190 191 191 194 195 196 197 198 198 199 200 201 202 202 203 203 204 204 205 205 206 207 207 208

KNOWLEDGE MANAGEMENT

NOTES

UNIT I

INTRODUCTION 1.1 INTRODUCTION Today’s organizations are fundamentally different as compared to organisations that existed two decades ago in terms of their functions, structures and style of management. The new organisations put more premium on understanding, adapting and managing changes and competing on the basis of capturing and utilizing knowledge to better serve customers, improve the operations or to speed up the delivery of their products to markets. The emergence of these new organizations calls for a new way of management, which is generally known as ‘Knowledge Management’ (KM). To begin any topic, it is useful to have a perspective and background to understand what is going on with respect to that topic. Now knowledge management is widely known and practiced in many large organizations, it might be useful to get an overview on this subject before we discuss the details of it. Knowledge management is the hottest subject of the day. The question is: what is this activity called knowledge management, and why it is so important to each and every one of us? Why is it important to adopt this new methodology of management? How to successfully implement KM in organizations? The following section offers some emerging perspectives in response to these questions. This chapter provides an introduction to the study of KM by looking at the overview of KM with regard to its meaning, usefulness, history, future, limitations, etc, and also briefly examines the nature and types of knowledge. The multidisciplinary roots of KM are enumerated, together with their contributions to the discipline. The importance of KM today is described together with the emerging roles and responsibilities needed to examine KM implementation. The emergence of economic system with knowledge as its basic ingredient is enumerated and the need to develop knowledge management strategies to stay competitive in today’s environment were pointed out and finally the need to prioritize the knowledge strategy is justified.

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ANNA UNIVERSITY CHENNAI

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1.2 LEARNING OBJECTIVES After studying this Unit, you should be able to understand the following: • • • • • • • • •

The definition, meaning and evolution of knowledge management Describe how KM helps organizations Outline the history of KM Identify the key process of KM Know the nature, characteristics and key drivers of knowledge economy Identify and compare the technology components of KM The impact of KM matrix and its parts Describe the KM strategy and its need in the context of KM Analyse knowledge as a strategic asset and its value

1.3 THE CONCEPT OF KNOWLEDGE MANAGEMENT Knowledge management, as it is practiced today, is a system of technologies focused upon the delivery of strategically useful knowledge and expertise, the availability of which facilitates effective collaboration and timely decision-making. The strategically literate employee, armed with the best and most up-to-date knowledge, delivered in a timely manner, will produce work that results in more satisfied customers, increased success and corporate value. Knowledge management, before the term was coined, used to be simply the transfer of knowledge from one person to another, the result of which enabled the recipient to benefit from the collected wisdom of the more experienced members of an organization or group. For instance, knowledge transfer happens when the founder of the family business trains his sons and daughters to run the business. It also takes place when a young person goes to college to learn from a renowned professor and when an apprentice welder trains under a master welder. Yet, today, companies have learned that there is much more to knowledge transfer than what took place in the past. They have seen their competitors leap ahead by using technology and sound knowledge transfer principles (newly rediscovered) to create dynamic collaborative environments that deliver knowledge strategically—when and where it is needed and to the people who need it—at the front line where the client solution is being invented. This is knowledge management today. We must not confuse knowledge with information. The two are distinct concepts that function in completely different ways. Information is tangible, hard numbers, facts. Knowledge is intangible, mental awareness, a part of the process of learning, a “habit” burned into the mind. Information represents the working and monitoring of physical objects. Knowledge represents mental objects, intellectual units that have a practical component. Information is independent of context. With knowledge the context affects the meaning and value of the knowledge. Information is easily transferable by means of recording and recitation. Knowledge requires learning and habituation for effective transfer. 2



Information is easily reproducible by means of copying. Knowledge is seldom reproduced in a consistent fashion because it is filtered according to the perspective of each individual, his context and understanding.

NOTES

Information is not knowledge. That was realized clearly during the Information Age when organizations found themselves drowning in huge in-house stores of unusable data. The fundamental difference between knowledge management as it was practiced in the past and how it has evolved today is that corporations are now using network technologies to enable employees to find and use knowledge and, in the process, contribute to a more direct impact on customer satisfaction and corporate value. Companies that effectively use knowledge break it down into its basic components. Knowing why represents having a basic understanding of the reasons for facts, conditions, job responsibilities, client requirements, etc. Knowing what means knowing the cause of a problem or condition. Knowing where provides a spatial reference to understanding. Knowing how provides the critical element for problem solving, the knowledge of how to get something done. Knowing when provides a temporal reference and is closely tied to timing and opportunity development. The major shift brought about by current perspectives on knowledge management is the shift in the value proposition between employer and employee. Employees have become more valuable assets because the knowledge they possess and use on behalf of customers is now recognized as vital to the success of the organization. Yet, if knowledge is an asset, it has to be managed in the same way as financial and physical assets. Estimates indicate that 70 - 80 percent of what employees know is hidden. Many organizations today don’t know what they know and who knows it. KM Viewpoint 1.1 In 1996, teams of leading heart surgeons from five New England medical centers observed one another’s operating room practices and exchanged ideas about their most effective techniques in collaborative learning experiments. The result was a 24% drop in their overall mortality rate for coronary bypass surgery. The concept of Knowledge Management proves to be a life-saver here! 1.3.1 Definitions of knowledge management Knowledge Management refers to the processes and/or tools an organization uses to collect, analyze, store, and disseminate its intellectual capital. This intellectual capital can include training materials, processes, procedures, documents, ideas, skills, experiences, and much more. Besides deployment of appropriate technology and processes by a business enterprise in order to maintain and retain it’s intellectual capital, an effective knowledge management also refers to making optimum use of experience and understanding of human resource in an organization as well as of the information artifacts, such as inherent knowledge 3


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based documents (reports) available internally within the organization, and also, the related information procured from the external resources. A logical extension of this concept is into the entire organization, in the form of Enterprise Knowledge Management (EKM). Among the areas of greatest concern for the modern knowledge worker (from CIO down to the Content Manager), is identifying, collecting, securing and maintaining the information (aka knowledge base) of the organization. Without a process to ensure this system’s usefulness, there are invariably holes which are only found when a user tries to obtain that (missing) information. Let us see the other useful definitions of KM to have a still broader outlook of KM. Arun O. Gupta, Senior Director Business Technology, Pfizer Ltd describes “KM as a practice that addresses the need for information that is required for making effective decisions”. If this information is structured, the same can be translated into knowledge by applying a set of predefined rules. For example, comments on discussion boards can be converted into useful FAQs. The perception of KM differs from one industry vertical to another. In software service companies, knowledge management can be a highly effective practice as it helps capture knowledge across different skill sets. For instance, information regarding common queries about specific technologies (if captured on the Intranet) can help solve common problems. This, in turn, boosts productivity. As Indian software service organisations employ software professionals in thousands, employee inputs can be extremely useful for organisational growth. Satish Joshi, Senior VP, Patni Computer Systems Limited says “For us, “KM is a set of processes and tools which give us the ability to leverage and combine the collective abilities of our knowledge workers.” Simply put, a KM practice should let an organisation provide relevant information to each and every user. As Sunil Kapoor, Head IT, Fortis Healthcare says, “KM is nothing but having customised information tailored to the needs of each user”. As KM practice provides a structured way of capturing knowledge that exists within the organisation, it gives an organisation the ability to improve the productivity and knowledge of its employees by means of knowledge sharing. “A KM practice that encompasses end-to-end processes owned by a department can go a long way toward boosting productivity,” says M D Agrawal, GM IS Refinery Systems, BPCL. According to the American Productivity & Quality Center, “KM refers to the strategies and processes of identifying, capturing, and leveraging knowledge to enhance competitiveness”.

4



According to Yogesh Malhota of www.brint.com “KM refers to the critical issues of organizational adaptation, survival and competence against discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies, and the creative and innovative capacity of human beings”.

NOTES

According to Gartner Group, KM is defined as a discipline that promotes an integrated approach to identifying, managing and sharing all of an enterprise’s information assets. These information assets may include databases, documents, policies and procedures, as well as previously unarticulated expertise and experience resident in individual workers. Gartner defines Knowledge management as an integrated and collaborative approach to the Creation, Capture, Organization, Access and Use of Information Assets. The Knowledge cycle is depicted in the Figure 1.1 below

The various steps involved are described as follows: •

Knowledge is created. This happens in the heads of people.

•

Knowledge is captured. It is put on paper in a report, entered into a computer system of some kind, or simply remembered.

•

Knowledge is organized, where it is classified and modified. The classification can be the addition of keywords which could be indexed. Modification can add context, background or other things that make it easier to reuse later. The test of this step’s success is to determine how easily people in the organization will be able to access and use the knowledge when they need it.

•

“Knowledge is shared and used. When knowledge is shared and used, it’s modified by the resources that use it. This takes us back to knowledge creation.

1.3.2 Objectives of knowledge management The following are the major objectives of KM 1. Create knowledge repositories a) External knowledge (competitive intelligence, market data, surveys, etc.) 5


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b) Structured internal knowledge (reports, marketing materials, etc.) c) Informal internal knowledge (discussion databases of ‘know how’) 2. Improve knowledge access through a) Technical expert referral b) Expert networks used for staffing based on individual competencies c) Turnkey video conferencing to foster easy access to distributed experts. 3. .Enhance the knowledge environment a) Change organizational norms and values related to knowledge in order to encourage knowledge use and knowledge sharing b) Customer’s rating of organisation’s expertise 4. Manage knowledge as an asset a) Attempt to measure the contribution of knowledge to bottom line success 1.3.3 Motivation for Knowledge Management Internal and external pressures and rapid inflows of information make effective operation of organizations extremely difficult (see Figure 1.2). The Internet and ECommerce have generated competitors that are on the other side of the world but only a mouse click away. Employees are moving from organization to organization at alarming rates, taking with them important knowledge of company operations that must be relearned by new employees. The pace of technology, particularly information technology (IT) continues to force management to consider organizational change associated with the implementations of electronic commerce store-fronts, automated inventory procurement and enterprise resource planning (ERP) systems. Changes in government legislation and regulatory practices provide a steady flow of new threats and opportunities. Customers are demanding new products and services that are bundled to their preference. Subsequently, companies are being forced to move faster and at new levels of personalized interaction. Filtering through this barrage of information for relevant data or combinations of information is a formidable undertaking. To address these challenges, organizations must develop management methods that accept information as a valued resource, convert information into organizational knowledge and generate value-added information from that knowledge.

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NOTES

4

Competition Global Opportunities

Employee Turn-over Organization

Customer Demands

Technological Change Regulatory Change

Figure 1.2 Internal and external pressures on an organization. Dealing with these pressures requires methods of managing organization knowledge that are rarely found in today’s companies and institutions. Figure 1.3 shows the major entities that act as sources and sinks of information for organizations. Leading companies are able to filter information in from these entities, build on their organizational knowledge and synthesise valuable information for return. Fundamental to the success of these methods is the realization that information technology does not, on its own, equal knowledge management. Since 1998, books such as “The Information Paradox” by John Thorp have asked serious questions about the role of information systems within organizations, how they are managed and the methods used to measure their benefit. Managing knowledge within an organization involves a composite of people and information technology. We see the ultimate goal for an organization as communicating information and managing knowledge with the same efficiency and effectiveness as an individual.

Employees Gov’t Reg. Management of Organizational Knowledge

Products Services

Customers Channels

Competitors Partners Suppliers

Figure 1.3 Organizational knowledge environments.

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1.3.4. Knowledge Management Cycle For humans the process of transforming data and information into knowledge and then back into value-added information is a cycle that is natural and on going. The following figure depicts this knowledge management cycle as consisting of four fundamental steps that involves the storage, processing and communication of information. We begin the discussion of this cycle as it applies to the individual and move on to discussing the cycle as it applies to small and then large organizations. In each case the methods of storing, processing and communication information are described and followed by a description of the progression through the four steps of the knowledge management cycle. 7

Environmental data Observation and Analysis Problems Opportunities

Information

Knowledge Consolidation

INFORMATION Storage Processing Communication

Theory Generation

Approach Methods

Results Testing and Application

An individual makes his or her way through the world being inundated with data and information from the environment. To deal with this, an individual uses personal memory as well as notes and paper files for storing information. The individual’s brain processes the information with possibly the aid of a calculator or a small computer. Communication of information is primarily internal from a knowledge management perspective. As individuals we pride ourselves on our ability to learn from our triumphs and defeats through the effective consolidation of knowledge. As the figure depicts, knowledge consolidated at the end of one iteration through the knowledge management cycle provides new information that can be used in yet another iteration. Small organizations of 2 to 20 persons are able to emulate the knowledge management cycle of an individual with some degree of success. Information and requests received from customers, partners, and the government is stored within individual memories, in documents and in simple database systems. Information processing takes place in individual brains as well as at productive meetings where the strengths and weakness of the individuals are well understood, accepted and utilized. Various small computer systems and possibly a network server are shared by all. Communication is primarily via ad-hoc meetings augmented by telephone, fax and email messages when a person is traveling or at home. 8



Knowledge consolidation by each individual is facilitated by a collective effort to ensure that failure does not recur for the same reasons and that success can be repeated as often as possible. Consequently, small organizations are said to be well-oiled, creative and able to move quickly to meet a changing environment with a high degree of synergy where the value derived from a project can often be greater than the sum of the individual efforts.

NOTES

Larger organizations have a difficult time emulating the knowledge management cycle of an individual. Large companies and institutions receive proposals, queries and other forms of information from a multitude of customers, channels, partners, government and regulatory bodies. Information is stored in various formats and locations that include policy documents, filing cabinets, internal process and product databases as well as external customer and distribution databases, microfiche, audio tape and video tape. Portions of the information in-flow are processed by individual brains only to be confounded by a multitude of meetings in which the persons assigned to various roles change from quarter to quarter. Various computer systems developed over the last ten years process portions of information in silos that have a difficult time talking to one another for technical and political reasons. Communication is achieved via a cornucopia of local area network, Internet, mobile devices. Meetings must be scheduled several weeks in advance for executives and many events must be cancelled and rescheduled due to conflicts. Knowledge gained at the end of a product cycle is often lost and for this reason failure can recur and success is not repeated as often as possible. Subsequently, large organizations are said to be lethargic, lacking creativity and slow to react to meet a changing environment. The chaos that results is largely due to the ineffective management of organizational knowledge. 1.3.5 Domains for Knowledge Management The diagram (Figure 1.4) is organized in four parts to indicate four technical domains for Knowledge Management. And the tools listed in the four technical domains can be used to help institutions share, distribute, capture and create knowledge better.

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Figure 1.4 Technical domains of KM Knowledge Sharing: Group Collaboration Systems (GCS) foster the creation and sharing of knowledge among people working in groups. Improved group coordination and collaboration is enabled through e-mail, teleconferencing, data-conferencing, videoconferencing, groupware, and Internet-based applications. Groupware and Intranets represent the most prevalent examples. Distribute Knowledge: Office Automation Systems (OAS) helps disseminate and coordinate the flow of information throughout the institutions. An OAS can be any application of information technology that intends to increase the productivity of information workers. Common examples include word processing, desktop publishing, imaging, electronic calendars, and desktop databases. Capture Knowledge: Artificial Intelligence Systems (AIS) provides institutions and administrators with codified knowledge that can be reused by others in the institution to expand the knowledge base. Examples include expert systems, neural networks, fuzzy logic, and genetic algorithms. Create Knowledge: Knowledge Work Systems (KWS) support the activities of highly skilled knowledge workers and professionals as they create new knowledge and try to integrate it into the institutions. KWS have special characteristics that support the unique needs of knowledge workers. Examples of knowledge work applications include computeraided design (CAD) systems and virtual reality (VR) systems for simulation and modeling.

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NOTES

KM Viewpoint 1.2 Pfizer India has embarked on two initiatives that will gradually evolve into a KM framework. The first one involves capturing documents and creating a context sensitive repository. The second initiative focuses on converting unstructured data into structured data and warehousing the same. Together, these initiatives will provide Pfizer with key metrics and information that will assist decision making.

1.3.6. Uses of Knowledge Management The Knowledge Management principles are being used for: •

Reducing cycle times

•

Reducing overheads

•

Boosting revenues by getting products and services to market faster

•

Improving customer service by streamlining response time

•

Empowering employees

•

Creating innovative and high quality products

•

Creating knowledge-sharing platform for the geographically dispersed teams

•

Enhancing employee retention rates by recognizing the value of employees’knowledge and rewarding them for it

•

Fostering innovation by encouraging the free flow of ideas

•

Streamlining operations and reducing costs by eliminating redundant or unnecessary processes

•

Enhancing supply chain management

•

Enhancing web publishing

•

Managing legal, intellectual property

•

Providing project workspace

•

Delivering competitive intelligence

•

Managing customer relationships

•

Providing training, corporate learning

•

Capturing and sharing best practices

•

Fostering cross-departmental effectiveness

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•

Making available increased knowledge content in the development and provision of products and services

•

Achieving shorter new product development cycles

•

Facilitating and managing organizational innovation and learning

•

Leveraging the expertise of people across the organization

•

Increasing network connectivity between employees and external groups with the objective of improving information flow

•

Managing the proliferation of data and information in complex business environments and allowing employees to access appropriate information sources

•

Managing intellectual capital and intellectual assets in the workforce (such as the expertise and know-how possessed by key individuals) as individuals retire and new workers are hired

Ultimately making the business more adept at change, with the aim of improving competitiveness and profitability. To facilitate this vision, not only does the business have structured data available in its strategic applications, it also has network drives and databases, may be an Intranet, the information on individuals’ hard drives, external sources and, most importantly, the knowledge, skills and experiences of its employees. 1.3.7 Nature of Knowledge Management 1. Knowledge Management is about people. It is directly linked to what people know, and how what they know can support business and organizational objectives. It draws on human competency, intuition, ideas, and motivations. It is not a technology-based concept. Although technology can support a Knowledge Management effort, it shouldn’t begin there. 2. Knowledge Management is orderly and goal-directed. It is inextricably tied to the strategic objectives of the organization. It uses only the information that is the most meaningful, practical, and purposeful. 3. Knowledge Management is ever-changing. There is no such thing as an immutable law in Knowledge Management. Knowledge is constantly tested, updated, revised, and sometimes even”obsoleted”when it is no longer practicable. It is a fluid, ongoing process. 4. Knowledge Management is value-added. It draws upon pooled expertise, relationships, and alliances. Organizations can further the two-way exchange of ideas by bringing in experts from the field to advise or educate managers on recent trends and developments. Forums, councils, and boards can be instrumental in creating common ground and organizational cohesiveness. 5. Knowledge Management is visionary. This vision is expressed in strategic business terms rather than technical terms, and in a manner that generates enthusiasm, buy-in, and motivates managers to work together toward reaching common goals. 12



6. Knowledge Management is complementary. It can be integrated with other organizational learning initiatives such as Total Quality Management (TQM). It is important for knowledge managers to show interim successes along with progress made on more protracted efforts such as multiyear systems developments infrastructure, or enterprise architecture projects.

NOTES

1.4 DISCIPLINES OF KNOWLEDGE MANAGEMENT Knowledge management draws upon a vast number of diverse disciplines such as: •

Religion and Philosophy to understand the role and nature of knowledge and the permission of individuals ‘to think for themselves’

•

Psychology to understand the role of knowledge in human behavior. Psychology too is concerned about different kinds of knowing as well as about how and why people learn, forgets, ignore, act, or fail to act. It looks at natural cognitive processes and raises questions of will and motivation that make it impossible to think of knowledge in terms of mechanical transfer from donors to recipients.

•

Business Theory & Economics to create strategies, determine priorities, evaluate progress and to understand work, and its organization. KM Viewpoint 1.3 When BP (now BP Amoco) decided to analyze, using a knowledge perspective, why they had such differing performance levels in their deep-water drilling rigs, they found wide differences in local knowledge and practices, knowledge that was mostly tacit and undocumented. As a result of their efforts to have this local knowledge more globally practiced, BP achieved very significant savings and subsequently achieved legendary status within knowledge management circles.

•

Cognitive Sciences to understand how best to support knowledge workers’ mental functioning required by their work settings

•

Ergonomics to create effective and acceptable work environment

•

Information Sciences to build supporting infrastructure and special knowledgerelated capabilities

•

Knowledge Engineering to elicit and codify knowledge

•

Artificial Intelligence to automate routine and assist knowledge-intensive work with reasoning and other high-level functions

•

Management Sciences to optimize operations and integrate KM efforts with other enterprise efforts

13


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•

Social Sciences to provide KM-related motivations, people processes, and cultural environments. Sociology has contributed both macro and micro perspectives to knowledge management. The first rigorous attempts to define a postindustrial, knowledge-based society were made by sociologist Daniel Bell and sociologically oriented economist Fritz Machlip, among others. Their documentation of this momentous change—the underlying principles for working with knowledge— crystallized and validated a dawning sense that something quite different was happening globally in the world of work. At the micro level, sociology’s strong research interest in the complex structures of internal networks and communities has obvious relevance to knowledge management. Knowledge management has inherited the concern for social facts. Rather than build from theory, it looks at what people actually do—the circumstances in which they share knowledge or do not share it; the ways they use, change, or ignore what they learn from others. Those social facts guide (or should guide) the development of knowledge management tools and techniques.

1.5 EVOLUTION OF KNOWLEDGE MANAGEMENT The following table provides a bird’s eye view of the important phases of evolution of Knowledge Management: Table 1. Evolution of Knowledge Management PERIOD

AUTHOUR/ORGANISATION CONTRIBUTION

BRIEF DESCRIPTION OF EVOLUTION

1938

H.G.WELLS

1960 1986

PETER DRUCKER Dr.K.WIIG

1989

McGRAW & HARRISONBRIGGS

1990

SENGE

1991 1995

NONAKA & TAKEUCHI

1994

BROWN

1996

STEWART

1997 2000 2003

KAPLAN & NORTON

Coined the word ’World Brain’ which depicts an intellectual organization the sum total of collective knowledge Coined the term ‘knowledge worker’ Coined KM concept at UN Described ‘knowledge engineering’ as involving information gathering, domain familiarization, analysis & design efforts and accumulated knowledge must be translated into code, tested and refined Focused on the ‘learning organisation’ as one tha can learn from past experiences stored in corporate memory systems Studied how knowledge is produced, used, and diffused within organizations and how much knowledge contributed to the diffusion of innovation Described what is ‘Community of Practices’ Introduced the concept called ‘Intellectual Capital’ Concept of Balanced Scorecard

ACADEMIA

KM courses in Universities with KM texts

14



1.6 SHORT HISTORY OF KNOWLEDGE MANAGEMENT

NOTES

In past eras, most employees had to fit into their organizational structures by means of performance standards based upon strictly defined job descriptions. Employment was secure as long as they performed assigned tasks and minded their own business. Out-ofthe-box thinking was not likely and knowledge hoarding was the order of the day. During the era of business process reengineering, cost accountants saw the most knowledgeable workers as an unnecessary expense, a liability to be eliminated through down sizing or early retirement. Many organizations made the strategic mistake of pushing their intellectual assets out the door. Knowledge hoarding was then replaced by a culture of knowledge hiding. In the past, consultancies practiced knowledge management on the fly. International networks of consultants communicated through computer networks by sharing their own problem-solving expertise with other consultants whose clients had the same problems. But consultants are in the business of selling their own knowledge and had little inclination to share it, especially with their colleagues and peers. During the 1990s chief executives in the consulting trades realized that the foundation of our economy had been shifting from natural resources toward intellectual assets. They began evaluating how knowledge was being used in their organizations. The biggest shock came with the discovery that 80 percent of corporate knowledge assets were not owned by the companies. They went home every night with the employees. As a result, questions such as how knowledge is acquired, used and delivered became paramount. These early pioneers knew that their organizations had to adapt quickly. They spent their time rethinking what they were doing, how they were doing it and why. They tore down barriers and ancient processes and replaced them with a systematic approach to knowledge sharing based on the fluid dynamics of a networked economy. As CEOs evaluated their knowledge management dynamics, it became apparent that the people who drove their enterprises were those who were creating and accumulating knowledge. And as time went on, the value of these people and what they knew was exerting an increasing influence on the success of their organizations. The challenge then became how to create the information, organizational intelligence, business models, communication tools and learning systems around these extremely important people. This goal had to become a central mission, a basic purpose for the existence of these consulting organizations – if they were to be successful. The lessons learned by these early adopters of knowledge management indicated that though they knew what knowledge was, finding out who has it, reorganizing operations to nourish and manage it, changing the work culture to support it and building knowledge networks around it were the real challenges of the future. 15


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With the advent of networked resources, new ways to codify, share, store and deliver knowledge enabled organizations to strategically use critical knowledge more easily and cheaply. The challenge, however, became how to develop a successful knowledge management model—there were too few examples from which to work. The result was a new knowledge management industry that was born out of the few models that were developed in those early days. Today, a group of leading edge companies like Lotus, Open Text, Documentum and others have developed knowledge management tools that enable corporations to manage and deliver strategic knowledge. It is no longer necessary to reinvent the wheel, and since many of the tools available were created for management consulting firms, it is possible to select and integrate a full-featured Knowledge Management System that includes and integrates key components like document management and collaborative software. 1.7 AREAS FOR RESEARCH IN KNOWLEDGE MANAGEMENT Based on differences between how individuals and organizations manage knowledge, let us see several important areas of research in knowledge management for organizations, particularly large organizations. The following table presents the major research topics by each of the four steps of the knowledge management cycle described in the sub section 1.3.4. Table 1.2 Areas of research within each step of the knowledge management cycle. Observation and Analysis

1. 2. 3.

Retrieval and filtering of data/information Enabling access to salient environmental data Sharing organizational goals and objectives

Theory Generation

4. 5. 6.

Elimination of “silo” processing and reinvention Fostering knowledge creation through small teams Reduction of bureaucracy and formal meetings

Testing and Application

7.

Knowledge Consolidation

10. Methods of collective reflection 11. Building trust for the dissemination of knowledge 12. Retaining knowledge when employees leave

Enabling “start to finish” development and deployment 8. Effective measurement of business processes and knowledge assets 9. Management of changing requirements

16



Retrieval and filtering of data / information. The rate of data and information in-flow to organizations by way of card-readers, automated telemetry, telephone calls and most notably the Internet is overwhelming. Most company wrestle every day with effective and efficient methods of retrieve data and filtering out the salient information. This is an area where both people skills and technology require improvement. Studies of the relative strengths and weaknesses of systematic approaches to information retrieval and filtering in the workplace would be of benefit. The education of knowledge workers in library science research skills is needed. Intelligent user interfaces that can learn the profile of a user’s interest and filter information based on that profile would greatly facilitate Internet searches. Research into advanced methods of Knowledge Query and Manipulation (KQML) will also facilitate the retrieval of information. Integrated with content management systems and the Internet, these technologies will provide very powerful observation tools.

NOTES

Enabling access to salient environmental data. Although there is much organizational data that is encoded into electronic form for ease of communications and analysis, there is other important information that is not. For example, in hospitals much of the important information on a patient is recorded with pencil on paper; on the manufacturing floor, important data is communicated verbally; and information surrounding important interactions with customers is rarely communicated beyond the sales staff and their managers. Internet, groupware and portal technologies can be used to assist with these problems, however there is a fundament need for cultural change in most organizations that encourages the capture of salient environmental data. Research is required into methods of cultivating cultural change. Sharing organizational goals / objectives. Large organizations suffer greatly from a lack of sharing and caring about organization goals. Clear and repeated communication of company objectives to all employees provides an environment in which knowledge can be better managed. Methods of sharing organizational goals and objectives and bringing them in-line with individual goals are important areas of research. Elimination of “silo” processing and reinvention. Large organizations have traditionally developed “silos” of endeavour because departmental and professional barriers make knowledge management difficult. This leads to competing analysis of environmental data and the generation of tactical business strategies that often conflict when they are executed. The best organizations are composed of “organic” networked teams where knowledge is able to flow freely across disciplines and departmental boundaries. The major problems that must be addressed are dynamic management methods and career development approaches that consider individual and organizational objectives and reward trusting relationships at every opportunity. Fostering knowledge creation through small teams. Work-teams of small numbers of people that share common goals are highly innovative environments. Having 17


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members of an organization move between these groups passing along best-practice methods is very important, yet often disruptive. Sharing knowledge takes time and can cause short-term delays in group performance. Creating an organizational culture that is receptive to personnel movement and knowledge exchange is a challenge. Technologies such as electronic mail, corporate intranets, portals and collaborative software (such as Lotus Notes) can be very helpful in creating and enabling small teams. Research and application of new management methods and technologies is needed. Reduction of bureaucracy and formal meetings. Moving from four levels of management bureaucracy to delegated authority and responsibility has been one of the most difficult transitions for modern organizations. The traditional hierarchy fosters a climate of presentations, proposals and meetings versus strong analysis and decisive action. A healthy knowledge management environment is one in which people wish to share information for the common good and not one in which they must share information in order to proceed with projects or business plans. This having been said, legal and fiscal responsibility requires a formal chain of command within organizations. Resolving this conflict continues to be an important area of research in business administration. Technologies such as message passing, groupware and document management systems can facilitate a more efficiently and effective movement of “paper-work” within the office and across the globe. Standard protocols and languages, such as the eXtensible Markup Language (XML), for interoperation between systems is an active area of research Enabling “start to finish” development and deployment. Too often in large organizations, design engineers or business strategists are not involved in the testing of the final product or the implementation of the tactical operations. This can lead to a false sense of accomplishment on the part of the engineer or strategist and a poor opinion of upper management and technical authority on the part of front-line employees. Methods of feedback between designer and user need to be created that ensure better communication of success and failure with a minimum investment of both parties’ time. Solutions can include people-centered approaches such as education of front line workers, practical job shadowing by designer engineers and the involvement of designers, testers and front-line workers from the start of design to implementation and deployment. Effective measurement of business processes and knowledge assets. Marketing through data mining and customer relationship management is really the first area of business administration outside of finance to widely employ rigorous mathematical methods. This has many management researchers excited about the use of measures and mathematics in other areas. Further work is needed in measuring the quality and value of business processes and intangible knowledge assets. In particular, methods of measuring success due to knowledge creation and knowledge transfer are needed.

18



Management of changing requirements. The pressures affecting modern organizations ensure that change will always occur. Tried and proven methods of managing change within projects and product cycles are needed. Project management research has turned to engineering methodologies that have established methods of change management. Innovative new methods of managing projects, products and services have also been developed that take iterative, incremental approaches that can more easily incorporate change (e.g. the Unified Software Development Process used in Software Engineering).

NOTES

Methods of collective reflection. An organization unlike an individual, rarely takes the time to reflect on successes and failures. Surprisingly, when an organization does do so, it is often recognized as a hallmark event; a defining moment in the life of the business. Most typically these events take place off-site, in seclusion and happen at best annually and often only at points of crisis. Why? There must be better ways to regularly reflect on successes and failures and share in the consolidation of new knowledge. Building trust for the dissemination of knowledge. Success factors within most organizations are closely guarded secrets. From an intellectual property perspective this makes a great deal of sense. However, secrets between departments, work-units or project teams within the same organization are counter-productive. Without trust between people there cannot be a productive sharing of information that results in knowledge transfer. The generation of a trusting environment is one that must extend from the top of the organization to the grass roots. Trust building activities such as team social activities, induction programs, job rotation, milestone celebrations, impromptu lunches and face-to-face communications need to be encouraged. Retaining knowledge when employees leave. The loss of organizational knowledge when an employee leaves is a very serious problem. Methods of retaining knowledge can be divided into proactive and reactive categories. Proactive methods include personnel rotation programs, master/apprentice schemes and recording information from internal experts (such as salesmanship techniques). Reactive methods include exit interviews and aftermath peer discussion sessions. Further research is required to find better methods of retaining organizational knowledge. 1.8. KNOWLEDGE ECONOMY For countries in the vanguard of the world economy, the balance between knowledge and resources has shifted so far towards the former that knowledge has become perhaps the most important factor determining the standard of living - more than land, tools and labour. Today’s most technologically advanced economies are truly knowledge-based. For the last two hundred years, neo-classical economics has recognised only two factors of production: labour and capital. Knowledge, productivity, education, and intellectual capital were all regarded as exogenous factors that are, falling outside the system. 19


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New Growth Theory is based on work by Stanford economist Paul Romer and others who have attempted to deal with the causes of long-term growth, something that traditional economic models have had difficulty with. Following from the work of economists such as Joseph Schumpeter, Robert Solow and others, Romer has proposed a change to the neoclassical model by seeing technology (and the knowledge on which it is based) as an intrinsic part of the economic system. Knowledge has become the third factor of production in leading economies. Technology and knowledge are now the key factors of production. Romer’s theory differs from neo-classical economic theory in several important ways: •

Knowledge is the basic form of capital. Economic growth is driven by the accumulation of knowledge.

•

While any given technological breakthrough may seem to be random, Romer considers that new technological developments, rather than having one-off impact, can create technical platforms for further innovations, and that this technical platform effect is a key driver of economic growth.

•

Technology can raise the return on investment, which explains why developed countries can sustain growth and why developing economies, even those with unlimited labour and ample capital, cannot attain growth. Traditional economics predicts that there are diminishing returns on investment. New Growth theorists argue that the non-rivalry and technical platform effects of new technology can lead to increasing rather than diminishing returns on technological investment.

•

Investment can make technology more valuable and vice versa. According to Romer, the virtuous circle that results can raise a country’s growth rate permanently. This goes against traditional economics.

•

Romer argues that earning monopoly rents on discoveries is important in providing an incentive for companies to invest in R&D for technological innovation. Traditional economics sees “perfect competition” as the ideal.

Enhancing human capital is critical for GDP growth. But sustained GDP growth doesn’t just happen. In order to make investments in technology, a country must have sufficient human capital. Human capital is the formal education, training and on-the-job learning embodied in the workforce. Various observers describe today’s global economy as one in transition to a ‘knowledge economy’, or an ‘information society’. But the rules and practices that determined success in the industrial economy of the 20th century need rewriting in an interconnected world where resources such as know-how are more critical than other economic resources. Various management writers have for several years highlighted the role of knowledge or intellectual capital in business. The value of high-tech companies such as software and

20



biotechnology companies is not in physical assets as measured by accountants, but in their intangibles such as knowledge and patents. The last few years have a growing recognition by accounting bodies and international agencies that knowledge is a crucial factor of production.

NOTES

1.8.1 Background of knowledge economy We are now living in a knowledge economy where the principal economic resource businesses have to offer their customer is knowledge. The nature of work in an organization has changed enormously with the shift from an industrial economy where the focus is production of commercial products to a knowledge economy where the main outcomes are service and expertise. The shift to a knowledge economy has increased the complexity of work activities. Employers have recognized the value of identifying and accessing a diversity of expertise and knowledge from different sources to work on common goals. People increasingly work closely with others to accomplish common goals, particularly if they are working in service areas or are used as sources of expertise by others. The shift to a knowledge economy has also led to increasing concern for building strong interpersonal relationships with others. Many employees spend considerable time interacting with others: collaborating with work colleagues, customers or people in other organizations through face-to-face meetings, online network, emails and many other mechanisms. 1.8.2 What is knowledge economy? The World Bank Institute offers a formal definition of a knowledge economy as one that creates, disseminates, and uses knowledge to enhance its growth and development. The knowledge economy is often taken to mean only high-technology industries or information and communication technologies (ICTs). It would be more appropriate, however, to use the concept more broadly to cover how any economy harness and uses new and existing knowledge to improve the productivity of agriculture, industry, and services and increase overall welfare. A knowledge economy uses data as it raw material and transforms it using technology, analysis tools, and human intelligence into knowledge and expertise. Fig. 1.5 illustrates the main phases of this transformation process.

Fig.1.5 Steps in the Knowledge Creation Process A knowledge-driven economy is one in which the generation and exploitation of knowledge play the predominant part in the creation of wealth. In the industrial era, wealth was created by using machines to replace human labour. Many people associate the 21


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knowledge economy with high-technology industries such as telecommunications and financial services. The term knowledge economy is a relatively new one, commonly used to refer to aspects of the service sector of the economy. This, however, is a restricted view of the term. To a significant extent, the linkages of the operations in the service sector lie in the hardware part. Thus, chips, integrated circuitry, and technology used in biosciences, for instance, are important aspects of knowledge economy. The space occupied by the Information Technology (IT) industry within the content of the term knowledge economy is significantly large, probably due to its being an early starter. However, a certain extent of grayness is associated with the term knowledge economy, primarily because, so far, it has not been adequately defined; nor have its boundaries been drawn with clarity. According to Housel and Bell a knowledge based economy is the one where knowledge is the main source of wealth, growth and employment, with a strong reliance on information technology. In knowledge economy citizens would be working in service industries rather than in manufacturing or agriculture. In knowledge-based economy there is a need to develop a national focus on innovation, research, education and information communication technologies. Further in the knowledge-based economy the shift in focus is from products to services where the greater recognition of the importance of the knowledge held within an organisation is responsible. 1.8.3 Impact of knowledge in the knowledge economy 1. Unlike capital and labour, knowledge strives to be a public good (or what economists call “non-rivalrous”). Once knowledge is discovered and made public, there is zero marginal cost to sharing it with more users. Secondly, the creator of knowledge finds it hard to prevent others from using it. Instruments such as trade secrets protection and patents, copyright, and trademarks provide the creator with some protection. 2. The implication of the knowledge economy is that there is no alternative way to prosperity than to make learning and knowledge-creation of prime importance. There are different kinds of knowledge. “Tacit knowledge” is knowledge gained from experience, rather than that instilled by formal education and training. In the knowledge economy tacit knowledge is as important as formal, codified, structured and explicit knowledge. 3. According to New Growth economics a country’s capacity to take advantage of the knowledge economy depends on how quickly it can become a “learning economy’. Learning means not only using new technologies to access global knowledge, it also means using them to communicate with other people about innovation. In the “learning economy” individuals, firms, and countries will be able to create wealth in proportion to their capacity to learn and share innovation. 22



1.8.4 Characteristics of knowledge economy The knowledge economy differs from the traditional economy in several key respects:

NOTES

1. The traditional economy is that of scarcity. The economics of knowledge economy is that of abundance. Knowledge is the resource which unlike other resources will not deplete when used. It can be shared and grow through its application. 2. In the knowledge economy the distances will be meaningless and the world will be considered as a global village where using appropriate technology virtual organisations, virtual teams and market places are possible in which operations will be faster than in the traditional economy. 3. In the knowledge economy, it is difficult to apply controls in terms of laws, taxes and barriers in the national level as the businesses become global in nature. 4. In the knowledge economy, the knowledge and information leak may be inevitable where the demand is highest and the barriers are lowest. 5. In the knowledge economy the products which are developed based on knowledge will attract premium price compared to the products with low embedded knowledge or knowledge intensity. 6. Price and value of knowledge depends heavily on context. The same knowledge can have different value to different people at different times. 7. Knowledge when locked into systems or processes has higher inherent value than when it can ‘walk out of the door’ in people’s heads. 8. Human capitals - competencies - are a key component of value in a knowledgebased company, yet few companies report competency levels in annual reports. In contrast, downsizing is often seen as a positive ‘cost cutting’ measure. These characteristics, so different from those of the physical economy, require new thinking and approaches by policy makers, senior executives and knowledge workers alike. To do so, though, requires leadership and risk taking, against the prevailing and slow changing attitudes and practices of existing institutions and business practice. 1.8.5 Key drivers of knowledge economy (a) The Importance of Intellectual Capital Intellectual capital is a firm’s source of competitive advantage. To become knowledge driven, companies must learn how to recognise changes in intellectual capital in the worth of their business and ultimately in their balance sheets. A firm’s intellectual capital employees’ knowledge, brainpower, know-how, and processes, as well as their ability to continuously improve those processes - is a source of competitive advantage. But there is now considerable evidence that the intangible component of the value of high technology and service firms far outweighs the tangible values of its physical assets, such as buildings or equipment. The physical assets of a firm such as Microsoft, for example, are a tiny proportion of its market capitalisation. The difference is its intellectual capital. 23


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(b) The Importance of ICT ICT (Information Communication Technology) releases people’s creative potential and knowledge and are the enablers of change. They do not by themselves create transformations in society. ICT are best regarded as the facilitators of knowledge creation in innovative societies. The new economics looks at ICT not as drivers of change but as tools for releasing the creative potential and knowledge embodied in people. However, the ICT sector has a powerful multiplier effect in the overall economy compared with manufacturing. A 1995 study of the effect of software producer Microsoft on the local economy revealed that each job at Microsoft created 6.7 new jobs in Washington State, whereas a job at Boeing created 3.8 jobs. Wealth-generation is becoming more closely tied to the capacity to add value using ICT products and services. (c) The New Economics of Information The rate of technological change has greatly increased over the past thirty years. Three laws have combined to explain the economics of information. Moore’s Law holds that the maximum processing power of a microchip at a given price doubles roughly every 18 months. In other words, computers become faster, but the price of a given level of computing power halves. Gilder’s Law - the total bandwidth of communication systems will triple every 12 months - describes a similar decline in the unit cost of the net. Metcalfe’s Law holds that the value of a network is proportional to the square of the number of nodes. So, as a network grows, the value of being connected to it grows exponentially, while the cost per user remains the same or even reduces. While Metcalfe’s Law has been applied to the Internet, it is also true of telephone systems. Gordon Moore first formulated Moore’s Law in the early 1970s. There can be no doubt that the cycle of technology development and implementation is accelerating and that we are moving inexorably onward, out of the Industrial Age and into the Information Age. (d) Globalisation ICT open up global markets and foster competition. With the advent of information and communication technologies, the vision of perfect competition is becoming a reality. Consumers can now find out the prices offered by all vendors for any product. New markets have opened up, and prices have dropped. When businesses can deliver their products down a phone line anywhere in the world, twenty-four hours a day, the advantage goes to the firm that has the greatest value-addition, the best-known brand, and the lowest “weight’. Software provides the best example: huge added value through computer code, light “weight” so that it can be delivered anywhere at any time.

24



Competition is fostered by the increasing size of the market opened up by these technologies. Products with a high knowledge component generate higher returns and a greater growth potential. Competition and innovation go hand in hand. Products and processes can be swiftly imitated and competitive advantage can be swiftly eroded. Knowledge spreads more quickly, but a firm must be able to innovate more quickly than its competitors in order to compete in the knowledge economy.

NOTES

(e) Brands are critical. Brands strengthen consumers’ trust in nations and their products. In a global marketplace where consumers are overwhelmed by choice, brand recognition assures their trust in both the tangibles and intangibles that a product will deliver. Like intellectual capital, brand equity can be hard to measure yet it may account for a significant proportion of a company’s value. It is intangible in the sense that it often consists of customers’ perceptions of the value they gain from using a product or service rather than any measurable benefit. A nation’s brand can be as important (or more) as the firm’s, and provide extra leverage for whichever firm’s brand is attached to the actual product – Indian tea, Swiss watches, Scotch whisky, German cars, Japanese appliances, New Zealand butter. 1.8.6 Growth of IT industry in the knowledge economy IT industry in India has grown, and has had an impact on various segments of the economy. In addition to being a sunrise revenue-generating industrial sector, the IT industry has established linkages with hardware manufacturing industries thereby giving a fillip to that sector. The IT industry has also made its presence felt on the education sector from where it draws one of its main resources. Further, this industry has helped generate employment potentialities in the economy. The Business Process Outsourcing units are further expected to play a major role in the generation of additional employment. This by no means is a simple contribution. And yet these and other attributes have been emphasised to the extent that the industry has acquired a larger than life image. It is only a short step from here to attribute this industry with pan-economic relevance. As a proxy for the knowledge economy, this industry is often identified as a solution provider for shortcomings in the economy, which is quite far-fetched in the current scenario. The impact of IT is best understood when the differences between industrial and knowledge-intensive ventures are recognised. Industrial growth derives from investments in large-scale infrastructure (such as railways, roadways, power grids and dams). Such infrastructure supports the growth of physical-asset intensive industries (such as the steel and transportation industries) that create and move physical entities (such as goods, water and people). These ventures employ numerous workers with limited education and skills, and can uplift large sections of society.

25


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In contrast, ventures in the knowledge economy usually involve the production of knowledge-intensive goods (like software), and the large-scale capture, movement and utilisation of information using sophisticated network infrastructure (such as computers, cable, fiber and routers). Beyond the physical labour required for initial construction, building and maintaining such infrastructure requires specialised knowledge. 1.8.7 Implications of knowledge economy The evolving knowledge economy provides critical implications for policy makers of local and national government as well as international agencies and institutions concerned with the growth and development of an economy as well as the businesses concerned with creating knowledge based organization. Following are some of the important implications of knowledge economy. Implications for policy makers 1. Traditional measures of economic success must be supplemented by new ones such as encouraging knowledge based industries with incentives and rewards. 2. Economic development policy should focus not on creation of jobs, but rather on infrastructure for sustainable ‘knowledge enhancement’ that act as an attraction to knowledge-based industries. 3. Development of policies for efficient regulation and taxation for information and knowledge trading at international level as well as looking to future knowledgebased industries rather than traditional industries. 4. Policies to promote collaboration to stimulate market development. 5. Strict policy measures to check information and knowledge frauds and thefts. 6. Wider policy support to knowledge based industries to remove regional imbalances. 7. Recognition and support of local talents to get into knowledge based industries and to prevent brain drain. 8. Policy support to promote education and training to take the challenges of knowledge economy and to promote R&D activities. Implications for business 1. Recognition of the importance of knowledge to the organisational business bottom line. 2. Design and develop new measures of enhancing corporate performance based on knowledge. 3. Systematically enhance learning and knowledge, through new organisational structure and processes that is in tune with the changing global environment. 4. Building a technology infrastructure to enhance knowledge creation and sharing. Example: Hewlett-Packard’s uses an intranet for knowledge sharing throughout the company on a global basis. 26



5. To foster organisational wide dissemination of knowledge through effective Internet / Intranet technologies and business practices.

NOTES

6. Recognising human contribution to knowledge such research and development, discovery, patents,etc., 7. Many businesses are now realizing the role of knowledge and are creating knowledge management programmes and appointing CKOs (Chief Knowledge Officers). Such responses should be part of a coordinated effort that: a) Recognizes the importance of knowledge to their business bottom line. Example: Buckman Laboratories recognizes the value of solving customer problems by enhancing knowledge flows from their chemical experts direct to the customer interface. b) Develops new measures of corporate performance based on knowledge: Example: Skandia’s supplements annual reports with intellectual capital reports using measures from the Skandia Navigator. c) Encourages the sharing of knowledge through effective Internet settings and business practices: Example: Steelcase designs ‘smart’ working environments and has developed a culture of knowledge sharing. 1.9 INDIA AS A KNOWLEDGE ECONOMY The various experts’ vision is that India will become a leader in the global knowledge economy by 2010. This will be the result of a highly focused effort to achieve global thought leadership in a few select fields that offer the highest potential for Knowledge Process Outsourcing (KPO). Here are some reasons for the optimism: 1. India enjoys unique advantages in having a large pool of English-speaking professionals with degrees in engineering, science or mathematics, who are capable and flexible to learn new skills fast given the right opportunity and reward structure. 2. The Indian Diaspora (diaspora-a dispersion of people originally belonging to one nation) in the United States and the United Kingdom has several among them who have achieved thought leadership in knowledge intensive fields. They are a rich source of domain expertise and can be motivated to help transfer knowledge and expertise to India and nurture a new generation of India-based thought leaders. 3. The entrepreneurial and energetic business community in India has the capacity to step up to this challenge and is capable of working closely with a supportive government to remove barriers that stand in the way of achieving of this vision. 4. Indians are able and willing to learn the necessary analytic and interpersonal skills needed to achieve thought leadership in the knowledge economy. A small minority of the scientists and engineers, primarily those who graduate from the IITs, IIMs and other elite institutes in India, have figured out on their own how to become world-class knowledge workers and thought leaders.

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5. India also has many of the other key ingredients for making itself as knowledge economy such as macroeconomic stability, a dynamic private sector, institutions of a free market economy, a well-developed financial sector, broad & diversified science and technology infrastructure, a well-developed ICT sector, and global provider of software services. KM Viewpoint 1.1 National Knowledge Commission India’s growing population of young people will give the country a demographic advantage over many western countries and possibly even China in the decades to come. As a result, India’s Prime Minister has said India must position itself to “leapfrog in the race for social and economic development” through the formulation of knowledge-oriented focus of development. As a result of this initiative, the National Knowledge Commission (NKC) was established in June 2005. The main objective of the commission will be to take appropriate actions to give India a knowledge advantage to create, apply and disseminate knowledge. This objective is expected to be implemented through the following strategies: • • •

Creation of Knowledge: strengthen education systems, promote research and development in a variety of fields, and partner with foreign sources to expand learning. Application of Knowledge: target health, agriculture, government and industry sectors to balance traditional knowledge, innovation encouragement and revise governance through technology. Dissemination of Knowledge: focus on widespread basic education for all citizens, especially those marginalized groups, create a culture of learning, foster improved literacy, create lifelong opportunities for skill acquirement, improve information and communication technology (ICT) and enhance standards of education through public awareness.

1.10. TECHNOLOGY AND KNOWLEDGE MANAGEMENT Effective knowledge management typically requires an appropriate combination of organisational, social, and managerial along with the deployment of appropriate technology. Technology is a facilitator of knowledge management, a tool to assist individuals and groups in creation, capturing and distribution of knowledge. IT brings in a new revolution in knowledge management, by acting as a catalyst to the organizations knowledge management practices. Technology advances have greatly contributed for the growth of knowledge management although the field has not yet reached full maturity. The capacity to link the many systems and processes in an electronic system has opened up many different possibilities of businesses. Many companies have embraced electronic processing to conduct their basic work activities through newer technologies such as e-workplace, e-commerce 28



and e-community. These reflect a shift in orientation from working with papers to the use of an electronic interface to perform organizational activities. Knowledge management has flourished as the technological systems have increased in robustness, reliability and costeffectiveness.

NOTES

Historically, there have been a number of technologies ‘enabling’ or facilitating knowledge management practices in the organization, including expert systems, knowledge bases, various types of Information Management, intranets, groupware, search and retrieval engines, software help desk tools, document management systems and other IT systems supporting organizational knowledge flows. The advent of the Internet brought with it further enabling technologies, including elearning, web conferencing, collaborative software, content management systems, corporate ‘Yellow pages’ directories, email lists, wikis, blogs, and other technologies. Each enabling technology can expand the level of inquiry available to an employee, while providing a platform to achieve specific goals or actions. The practice of KM will continue to evolve with the growth of collaboration applications, visual tools and other technologies. Since its adoption by the mainstream population and business community, the Internet has led to an increase in creative collaboration, learning and research, e-commerce, and instant information. Knowledge management does have a very strong technology components attached to it. Knowledge management is strategic management and hence it requires that the top management fully exploit the opportunities given by information technology for business purposes. 1.10.1. Electronic technology for transferring knowledge The availability of the World Wide Web has been instrumental in catalyzing the knowledge management movement. Information technology may, if well resourced and implemented, provide a comprehensive knowledge base that is speedily accessed, interactive, and of immediate value to the user. However there are also many examples of systems that are neither quick, easy-to-use, problem free in operation, or easy to maintain. The Web, for example, frequently creates information overload. The development of tools that support knowledge sharing in an appropriate and user-friendly way, particularly in organization-wide knowledge sharing programs, is not a trivial task. Most of the technological tools now available tend to help dissemination of knowhow, but offer less assistance for knowledge use. Tools that assist in knowledge creation are even less well developed, although collaborative workspaces offer promising opportunities, by enabling participation, across time and distance, in project design or knowledge-base development, so that those most knowledgeable about development problems — the people living them on a day-to-day basis – can actively contribute to their 29


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solution. Some of the more user-friendly technologies are the traditional ones — face-toface discussions, the telephone, electronic mail, and paper-based tools such as flip charts. Among the issues that need to be considered in providing information technology for knowledge sharing programs are: 1. Responsiveness to user needs: continuous efforts must be made to ensure that the information technology in use meets the varied and changing needs of users. 2. Content structure: in large systems, classification and cataloguing become important so that items can be easily found and quickly retrieved. 3. Content quality requirements: standards for admitting new content into the system need to be established and met to ensure operational relevance and high value. 4. Integration with existing systems: since most knowledge sharing programs aim at embedding knowledge sharing in the work of staff as seamlessly as possible, it is key to integrate knowledge-related technology with preexisting technology choices. 5. Scalability: solutions that seem to work well in small groups (e.g. HTML web sites) may not be appropriate for extrapolation organization-wide or on a global basis. 6. Hardware-software compatibility is important to ensure that choices are made that are compatible with the bandwidth and computing capacity available to users. 7. Synchronization of technology with the capabilities of users is important so as to take full advantage of the potential of the tools, particularly where the technology skills of users differ widely. Knowledge sharing programs that focus on the simultaneous improvement of the whole system, both technology tools and human practices, are likely to be more successful than programs that focus on one or the other. One of the major risks in knowledge management programs is the tendency for organizations to confuse knowledge management with some form of technology, whether it is Lotus Notes, the World Wide Web, or one of the off-the-shelf technology tools that are now proliferating. In the process, the essentially ecological concept of knowledge management becomes degraded into a simple information system that can be engineered without affecting the way the work is done. It is not that information systems are bad. Rather, it is important to recognize that knowledge management is a different and better way of working which affects people, and requires social arrangements like communities to enable it to happen on any consistent and sustained basis.

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NOTES

KM Viewpoint 1.4 KA Technology for KM at Rolls-Royce Rolls-Royce plc is one of the world’s leading organisations in the design, development and manufacture of jet engines and also a leading industrial partner in SPEDE. The company identified the relevance of early findings from SPEDE to its own KM programme and embarked upon a bilateral programme with the University of Nottingham to exploit KA techniques for the rapid development of components of the Rolls-Royce Capability Intranet. Rolls-Royce’s Capability Intranet is intended to become the company’s quality system, providing quick and easy access to all the latest information needed by staff in order to complete tasks accurately and reliably including the capture of lessons learned and evolving best practices. The scope of the Capability Intranet spans business processes, manufacturing processes, product definitions, technical skills and training. It includes quality manuals, working practices, information about technologies and capabilities and specific examples of good (and bad) practice based on real case examples. A technology transfer programme was conceived in early 1998 whereby established KA tools and techniques could be applied and evaluated within the context of developing knowledge-rich web sites for the Rolls-Royce Capability Intranet. The programme has involved a series of coached projects, typically comprising two company employees on secondment to a special facility based at the University of Nottingham for a period of twelve weeks. Sixteen groups have passed through the facility over the past year amounting to thirty-eight Rolls-Royce employees. At the moment, a total of twelve Rolls-Royce employees are on the programme, though this is expected to rise significantly over the next year as personnel and facilities are expanded.

1.10.2. Information Technology for Knowledge Management There is an ongoing lively debate about the role that information technology can play for knowledge management. On the one hand, information technology is used pervasively in organizations, and thus qualifies as a natural medium for the flow of knowledge. A recent study from the American Productivity and Quality Center shows that organizations embarking in knowledge management efforts generally rely, for accomplishing their goals, on the setting up of a suitable IT infrastructure. At the other end of the spectrum, leading knowledge management theorists have warned about the attitude that drives management towards strong investments in IT, possibly at the expense of investments in human capital. The danger that this viewpoint sees is that IT-driven knowledge management strategies may end up objectifying and calcifying knowledge into static, inert information, thus disregarding altogether the role of tacit knowledge. Knowledge management strategies of this type would bring back the ghost of the infamous, and none too far in time, re-engineering days, when the corporate motto was “More IT, less people!”; they conjure grim scenarios of organizations with enough memory to remember everything and not enough intelligence to do anything with it.

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Part of the problem here derives from a linguistic ambiguity: nowadays information technologies are as much about creating direct connections among people through such applications as electronic mail, chat-rooms, video-conferencing and other types of groupware as they are about storing information in databases and other types of repositories. As for information databases, they can also be fruitfully re-thought, in a knowledge management perspective, as resources for the sharing of best practices and for preserving the intellectual capital of organizations. Generally speaking, investments in IT seem to be unavoidable in order to scale up knowledge management projects. The best way of applying information technology to knowledge management is probably a combination of two factors: on the one hand, the awareness of the limits of information technology, and of the fact that any IT deployment will not achieve much, if it is not accompanied by a global cultural change toward knowledge values; on the other hand, the availability of information technologies that have been expressly designed with knowledge management in view. 1.10.3. Knowledge Management Technologies The early Knowledge Management technologies were online corporate yellow pages (expertise locators) and document management systems. Combined with the early development of collaborative technologies (in particular Lotus Notes), KM technologies expanded in the mid 1990s. Subsequently it followed developments in technology in use in Information Management. In particular the use of semantic technologies for search and retrieval and the development of knowledge management specific tools such as those for communities of practice. More recently social computing tools (such as blogs and wikis) have developed to provide a more unstructured, self-governing approach to the transfer, capture and creation of knowledge through the development of new forms of community, network or matrix. However, such tools for the most part are still based on text and code, and thus represent explicit knowledge transfer. These tools face challenges in distilling meaningful re-usable knowledge and intelligible information and ensuring that their content is transmissible through diverse channels, platforms and forums. Let us briefly understand the some of the technologies that are currently associated with the field of knowledge management: Some Key Technologies are as follows: The impact of each technology varies enormously from situation to situation. Several technologies recur in many knowledge management programs, partly because they are generic and pervade many core activities and processes. Let us briefly review some of the main technologies used in KM programs. (a) Intranet, Internet The ubiquitous Internet protocols make it easy for users to access “any information, any where, at any time”. Further, browsers and client software can act as front-ends to 32



information in many formats and many of the other knowledge tools such as document management or decision support. Remember too, that the basic functions of email, discussion lists and private newsgroups often have the biggest short term impact.

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KM Viewpoint 1.5 Booz Allen & Hamilton’s Knowledge Online is an Intranet that provides a wealth of information (e.g. best practice, industry trends, database of experts) to their consultants world-wide. Through active information management by knowledge editors (subject experts and librarians) the information remains well structured and relevant. (b) Groupware - Lotus Notes What groupware products like Lotus Notes add over and above Intranets are discussion databases. Users such as Thomas Miller, a London based manager of insurance mutuals, access their ‘organizational memory’, as well as current news feeds in areas of interest, through one of Lotus’s key features, its multiple ‘views’. When writing new insurance proposals, existing explicit knowledge can be assembled from the archive, guided by expert systems front-end, while tacit knowledge is added through discussion databases. (c) Intelligent Agents The problem of information overload is becoming acute for many professionals. Intelligent agents can be trained to roam networks to select and alert users of new relevant information. Additionally they can be used to filter out less relevant information from information feeds. However, in practice it seems that a well run knowledge center, such as those at Price Waterhouse, the best intelligent agent is still a human being! A related technology is that of text summarizing, which British Telecom have found can summarize large documents, retaining over 90 per cent of the relevant meaning with less than a quarter of the original text. (d) Mapping Tools There are an increasing number of tools, such as COPE and IDONS, that help individuals and teams develop cognitive maps or ‘shared mental models’. These have been used by companies such as Shell to develop future scenarios and resolve conflicting stakeholder requirements. In addition, other mapping tools, such as those found in Knowledge X, can represent conceptual linkages between different source documents. (e) Document Management Documents, and especially structured documents, are the form in which much explicit knowledge is shared. With annotation and redlining facilities, they can become active

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knowledge repositories, where the latest version and thinking is readily shared amongst project eams. KM Viewpoint 1.6 By using a document management system for the construction of the Thelma North Sea oil platform, AGIP reduced construction time by 9 months and reduced document handling costs by 60 per cent. Suppliers like Dataware are repositioning their products as knowledge management products and are also adding ‘knowledge enriching’ functionality.

(f) Expert systems Knowledge-based expert systems, or simply expert systems, use human knowledge to solve problems that normally would require human intelligence. These expert systems represent the expertise knowledge as data or rules within the computer. These rules and data can be called upon when needed to solve problems. Books and manuals have a tremendous amount of knowledge but a human has to read and interpret the knowledge for it to be used. Conventional computer programs perform tasks using conventional decision-making logic — containing little knowledge other than the basic algorithm for solving that specific problem and the necessary boundary conditions. This program knowledge is often embedded as part of the programming code, so that as the knowledge changes, the program has to be changed and then rebuilt. Knowledge-based systems collect the small fragments of human know-how into a knowledge-base which is used to reason through a problem, using the knowledge that is appropriate. A different problem, within the domain of the knowledge-base, can be solved using the same program without reprogramming. The ability of these systems to explain the reasoning process through back-traces and to handle levels of confidence and uncertainty provides an additional feature that conventional programming doesn’t handle. KM Viewpoint 1.7 Most expert systems are developed via specialized software tools called shells. These shells come equipped with an inference mechanism (backward chaining, forward chaining, or both), and require knowledge to be entered according to a specified format. They typically come with a number of other features, such as tools for writing hypertext, for constructing friendly user interfaces, for manipulating lists, strings, and objects, and for interfacing with external programs and databases. These shells qualify as languages, although certainly with a narrower range of application than most programming languages.

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(g) Knowledge base A knowledge base is a centralized repository for information: a public library, and a database of related information about a particular subject. In relation to information technology a knowledge base is a machine-readable resource for the dissemination of information, generally online or with the capacity to be put online. An integral component of knowledge management systems, a knowledge base is used to optimize information collection, organization, and retrieval for an organization, or for the general public.

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A well-organized knowledge base can save enterprise money by decreasing the amount of employee time spent trying to find information about - among myriad possibilities - tax laws or company policies and procedures. As a customer relationship management (CRM) tool, a knowledge base can give customers easy access to information that would otherwise require contact with an organization’s staff; as a rule, this capacity should make the interaction simpler for both the customer and the organization. A number of software applications are available that allow users to create their own knowledge bases, either separately (these are usually called knowledge management software) or as part of another application, such as a CRM package. In general, a knowledge base is not a static collection of information, but a dynamic resource that may itself have the capacity to learn, as part of an artificial intelligence (AI) expert system, for example. According to the World Wide Web Consortium (W3C), in the future the Internet may become a vast and complex global knowledge base known as the Semantic Web. (h) Artificial intelligence technology. AI is providing key components in a variety of KM applications. Closely related domains include informatics, applied informatics, knowledgebase management systems, and qualitative analysis. (i) Case-based reasoning systems. CBR systems solve new problems by adapting previously successful solutions to similar problems. Meeting customer-support requirements is just one of the applications. (j) Competitive intelligence applications. Collecting, analyzing, and communicating the best available information about technological trends and developments outside a company’s walls is the purpose of competitive technical intelligence. It is sometimes referred to as competitive analysis or competitive intelligence. (k) Corporate portals and knowledge portals. It is concerned with gathering the information resources of an organization into a centralized resource. Full-text retrieval and various kinds of taxonomies are applied to provide access to the information. Related terms: corporate portals, knowledge portals, business intelligence, digital dashboards. (l) Data mining. Many large companies — for example, pharmaceutical and chemical corporations — have major intellectual assets buried in their paper and electronic files. Extracting them isn’t easy. Related terms: knowledge discovery and automatic discovery. 35


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(m) Groupware and artifact-based collaboration. The term artifact-based collaboration is often used to describe products like Lotus Notes, because the collaborative activity centers on an artifact — for example, a document authored by many people. See also, Computer-supported collaborative work. Groupware also includes computer applications for organizing meetings and supporting interactions and group decision-making processes-without a substantial shared artifact. (n) Decision-support systems. Decision-support systems incorporate insights from cognitive science, management science, computer science, operations research, and systems engineering both in order to produce computerized artifacts for helping knowledge workers in their performance of cognitive tasks, and to integrate such artifacts within the decisionmaking processes of modern organisations.” (o) Content management and document management. Although document management systems have been with us for many years, many original DM products have been recast as content management systems, whose primary function is to manage the data that goes into corporate Internet and intranet (and extranet) sites. (p) Customer relationship management. Customer Relationship Management (CRM) strategies have been around since the first bazaar, but products designed to automate CRM efforts are among today’s hottest new computer applications. Companies are rushing to automate and better manage all the ways they deal with customers, including people who might not consider themselves customers yet. (q) Customer-support technology. Help desk systems and customer-support systems are designed to reduce the heavy labor costs imposed by demands for information from users of increasingly complex products and improve timeliness and quality of support. “Customers” may be internal or external clients. (r)Performance-support systems and distance-learning technology. Performancesupport systems (PSS) and “eLearning” are designed to reduce the skyrocketing costs of classroom training in specific skills while addressing the problems caused by the rapid pace of change. By the time a classroom training program is designed, it is usually out of date. (s) Hypertext technology. A more recent development or, perhaps more accurately, a return to interest in “hypertext” as a method of representing and providing access to critical organizational knowledge is reflected in the Topic Map standard (ISO/IEC 13250) and in Tim Berners-Lee’s Semantic Web effort. Both are XML-based and are seeking common ground. (This is not the simple Web hypertext model, but the richer, often proprietary hypertext models that preceded the World Wide Web. The HyTime standard on which the Topic Map standard is based grew in part out of a need for creating a common ground among the hundreds of unique hypertext systems.) 36



(t) Semantic networks. A semantic network is a method of representing knowledge often used for critical analysis of literary texts. Similar to hypertext technologies in some ways, but with emphasis on typed links among concepts.

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1.11 KNOWLEDGE MANAGEMENT MATRIX Knowledge Matrix helps in identifying different islands of knowledge to create a Knowledge Management database/data warehouse. The author has referred the following Knowledge Matrix to enable organizations to uncover various sources of knowledge in order to provide knowledge services to both internal and external customers. Please see next page for the Knowledge Matrix External Customers Feedback reports Questionnaires on quality & service Customer profiling Payment history Customer meetings and visits Annual reports & Financial analysis Contact Analysis Customer Newsletter Suppliers Performance history Product catalog Vendor meetings/seminars Annual reports & Financial analysis Internal Employees Knowledge on products/services Technical expertise & Reusable components Best practices from previous projects Learning from previous assignments Vertical industry experience

External Sales and marketing processes Lead-time Information Billing procedures Internal Logistics - Procurement & Inventory Quality processes HR processes Financial processes Lead time information for all the processes Six-sigma processes Project Execution Methodologies Security policies: Network, data and personnel Manufacturing processes

KM Database External Customer feedback reports Product successes Product failures Competitive forces Customer meetings Internal Tools information - various tools developed for different purposes Best things and worst things Postmortem reports

External Demographics Legal policies: Customs & Tax information Competitor analysis Road shows/Meetings/Conferences Research Publications Customers care policies Customer promotions Corporate Vision and Culture Articles/quotes on the organization appeared in trade magazines Internal R&D - Research Publications Learning from projects execution Brand equity information Organization structure & Who's who of the organization? Quality: SEI,ISO, PCMM Project Postmortem reports Induction programs Networking with professional organizations Idea generation/sharing session

Figure 1.6 Knowledge Matrix

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1.12 KNOWLEDGE MANAGEMENT STRATEGY Organisations are facing ever-increasing challenges, brought on by marketplace pressures or the nature of the workplace. Many organisations are now looking to knowledge management (KM) to address these challenges. Such initiatives are often started with the development of a knowledge management strategy. Knowledge management strategy is termed as an approach undertaken by an organization to use its information and knowledge resources for building competitive strength and sustainable growth for realizing that pursuing KM strategy can enable it to dramatically reduce cycle time and costs, increase sales, and to meet the customer needs. However, KM as business strategy will only succeed when certain fundamental requirements are employed. The human resource elements, information technology and information incorporated into the strategic business processes, must all be tightly incorporated into the management and working culture of the organization. It is only by this kind of synthesis of the knowledge management components that creates the organizational ability to exploit the total information and knowledge potentials of the organization. 1.12.1 The Need for KM strategy There are a number of common situations that are widely recognised as benefiting from knowledge management approaches. While they are not the only issues that can be tackled with KM techniques, it is useful to explore a number of these situations in order to provide a context for the development of a KM strategy. Beyond these typical situations, each organisation will have unique issues and problems to be overcome. (a) Call Centers Call centers have increasingly become the main ‘public face’ for many organisations. This role is made more challenging by the expectations of customers that they can get the answers they need within minutes of ringing up. Other challenges confront call centers, including high-pressure, closely-monitored environment, high staff turnover, costly and lengthy training for new staff. In this environment, the need for knowledge management is clear and immediate. Failure to address these issues impacts upon sales, public reputation or legal exposure. (b) Front-line staff Beyond the call center, many organisations have a wide range of front-line staff who interacts with customers or members of the public. They may operate in the field, such as sales staff or maintenance crews; or be located at branches or behind front-desks. In large organisations, this front-line staffs are often very dispersed geographically, with limited communication channels to head office. Typically, there are also few mechanisms for sharing information between staff working in the same business area but different locations. The

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challenge in the front-line environment is to ensure consistency, accuracy and repeatability. KM facilitates this function.

NOTES

(c) Business managers The volume of information available to business management has increased greatly. Known as ‘information overload’, the challenge is now to filter out the key information needed to support business decisions. The pace of organisational change is also increasing, as are the demands on the ‘people skills’ of management staff. In this environment, there is a need for sound decision making. These decisions are enabled by accurate, complete and relevant information. Knowledge management can play a key role in supporting the information needs of management staff. It can also assist with the mentoring and coaching skills needed by modern managers. (d) Aging workforce The public sector is particularly confronted by the impacts of an aging workforce. Increasingly, private sector organisations are also recognising that this issue needs to be addressed if the continuity of business operations is to be maintained. Long-serving staff has a depth of knowledge that is relied upon by other staff, particularly in environments where little effort has been put into capturing or managing knowledge at an organisational level. In this situation, the loss of these key staff can have a major impact upon the level of knowledge within the organisation. Knowledge management can assist by putting in place a structured mechanism for capturing or transferring this knowledge when staff retires. (e) Supporting innovations Many organisations have now recognised the importance of innovation in ensuring long-term growth (and even survival). This is particularly true in fast-moving industry sectors such as IT, consulting, telecommunications, biotechnology and pharmaceuticals. Most organisations, however, are constructed to ensure consistency, repeatability and efficiency of current processes and products. Innovation is does not tend to sit comfortably with this type of focus, and organisations often need to look to unfamiliar techniques to encourage and drive innovation. There has been considerable work in the knowledge management field regarding the process of innovation, and how to nurture it in a business environment. 1.12.2 Development of organisational KM strategies The commonly employed strategy is to design and develop systems and practices to obtain, organize, restructure, warehouse or memorize and distribute knowledge. This strategy enables organizations to dramatically reduce cycle time and costs, increases sales and effectively brings the knowledge of the organization to bear on customer needs. An approach, based on this strategy, results in improvement operations or to develop and

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deliver products and services tailored to the market requirements. Building of teams, relationships and networks forms the basis for effective transfer, besides approaches of encouraging collaborative knowledge transfer. Many organizations especially those in the service industry adopt a strategy with strong focus on their customer. This customer-focused knowledge strategy is directed towards capturing, developing and transferring knowledge and understanding of customers’ diverse needs, preferences, and businesses. These efforts bring about a significant improvement in sales and use the collective knowledge of the organisation to solve customer problems. This strategy recognizes and facilitates learning from customers and understand their needs better and development of effective solutions to take them. By establishing personal responsibility for knowledge, organizations are recognizing that individuals must be supported and made accountable for identifying, maintaining, and expanding their own knowledge as well as renewing and sharing their knowledge assets. Companies are now realizing the value of each knowledgeable and capable employee and recognize the key fact that the development of their skills lay with employee themselves and not with the organization. Some firms building incentives into their appraisal system and offering other motivators to encourage the development of a knowledge-intensive culture. Another important strategy revolves around leveraging assets such as patents, technologies, operational and management practices, customer relations, organizational arrangements, and other structural knowledge assets and concentrates on renewing, organizing, valuing, safekeeping, increasing availability of, and marketing these assets. The final strategy, innovation and knowledge creation emphasizes the creation of new knowledge through basic and applied research and development. Organisations adopting these strategies need to ascend the knowledge spiral and continually discover new and better ways of functioning and innovating. They recognize that innovation is central to growth and that unique knowledge and expertise enhances their competitive value in the marketplace. 1.13 PRIORITIZING KNOWLEDGE STRATEGIES Effective knowledge management is of vital importance for any enterprise with a quest to ensure viability and survival. Enterprises need to develop a KM strategy which impinges on all areas of the organization and requires a corporate approach to make it work. Knowledge strategy designs an organisation’s future based on using knowledge effectively. Knowledge strategy starts with the notion that an organisation’s business strategy should guide its planning for knowledge management. Therefore, knowledge strategy

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follows business strategy. The first activity in knowledge strategy is understanding the current business strategy then progressing that strategy as the basis for organizational analysis.

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The knowledge strategy should clearly articulate why the organization should share its know-how, what the organization will share, with whom the organization will share and how the organization will share. A knowledge strategy should start from existing strategies, plans and modus operandi of an organization. It should explicitly identify specific areas of inefficiency – lost opportunities, or costly mistakes – where a good KM practice would improve productivity and minimize risks. It should seek to support people throughout the organization in performing their daily tasks efficiently and effectively. It should identify how knowledge can create new opportunities – in innovative customer solutions, in business processes or in new product and services. A four-phased approach for prioritizing the knowledge strategy and moving projects forward are as follows: 1. Envisioning business strategy: Identifying and developing a business strategy and linking initial knowledge needs to the strategy. This phase uses strategy workshops, SWOT analyses and scenario planning sessions to develop the initial strategy. 2. Knowledge valuation: Analysing the current state of the organization, diagnosing strategic gaps, evaluating the learning rate and assessing cultural issues. This phase delivers an organizational assessment and gap analysis. 3. Creating knowledge strategy: This phase analyses impacts and develops strategies for addressing gaps and redesigning processes. Strategic gaps are prioritized and action plan developed and knowledge resources and practices are aligned to the strategy. 4. Knowledge path building: This phase establishes plans and designs for building a knowledge architecture to support full organizational participation. This phase coordinates plans, people and information resources to integrate the knowledge strategy into organizations, systems, product lines and business processes. 1.14 KNOWLEDGE AS A STRATEGIC ASSET Business organizations are coming to view knowledge as their most valuable and strategic asset, and bringing that knowledge to bear on problems and opportunities as their most important capability. They are realizing that to remain competitive they must explicitly manage their intellectual assets and capabilities. Today, knowledge is considered as the most strategically important asset for every business organizations. Having unique access to valuable assets in an organisation is one way to create competitive advantage, in some cases either this may not be possible, or competitors may imitate or develop substitutes for those assets. Companies having superior knowledge, however, are able to coordinate and 41


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combine their traditional assets and capabilities in new and distinctive ways, providing more value for their customers than can their competitors. That is, by having superior intellectual assets, an organization can understand how to exploit and develop their traditional assets better than competitors, even if some or all of those traditional assets are not unique. Therefore, knowledge can be considered as the most important strategic asset, and the ability to acquire, integrate, store, share and apply it has become the most important capability for building and sustaining competitive advantage by any organisation. The broadest value proposition, then, for engaging in knowledge management is that it can enhance the organization’s fundamental ability to compete. What is it about knowledge that makes the advantage sustainable? Knowledge, especially context-specific, tacit knowledge embedded in complex organizational routines and developed from experience, tends to be unique and difficult to imitate. And unlike many traditional assets, it is not easily purchased in the marketplace in a ready-to-use form. To acquire similar knowledge, competitors have to engage in similar experiences. However, acquiring knowledge through experience takes time, and competitors are limited in how much they can accelerate their learning merely through greater investment. Knowledge-based competitive advantage is also sustainable because the more a firm already knows, the more it can learn. Learning opportunities for an organization that already has a knowledge advantage may be more valuable than for competitors having similar learning opportunities but starting off knowing less. Sustainability may also come from an organization already knowing something that uniquely complements newly acquired knowledge, providing an opportunity for knowledge synergy not available to its competitors. New knowledge is integrated with existing knowledge to develop unique insights and create even more valuable knowledge. Organizations should therefore seek areas of learning and experimentation that can potentially add value to their existing knowledge via synergistic combination. Sustainability of a knowledge advantage, then, comes from knowing more about some things than competitors, combined with the time constraints faced by competitors in acquiring similar knowledge, regardless of how much they invest to catch up. This represents what economists call increasing returns. Unlike traditional physical goods that are consumed as they are used, providing decreasing returns over time, knowledge provides increasing returns as it is used. The more it is used, the more valuable it becomes, creating a self-reinforcing cycle. If an organization can identify areas where its knowledge leads the competition, and if that unique knowledge can be applied profitably in the marketplace, it can represent a powerful and sustainable competitive advantage. Organizations should strive to use their learning experiences to build on or complement knowledge positions that provide a current or future competitive advantage. Systematically mapping, categorizing and benchmarking organizational knowledge not only can help make 42



knowledge more accessible throughout an organization, but by using a knowledge map to prioritize and focus its learning experiences, an organization can create greater leverage for its learning efforts. It can combine its learning experiences into a “critical learning mass” around particular strategic areas of knowledge.

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While a knowledge advantage may be sustainable, building a defensible competitive knowledge position internally is a long-term effort requiring foresight and planning as well as luck. Longer lead time explains the attraction of strategic alliances and other forms of external ventures as potentially quicker means for gaining access to knowledge. It also explains why the strategic threat from technological discontinuity tends to come from firms outside of or peripheral to an industry. New entrants often enjoy a knowledge base different than that of incumbents, and which can be applied to the products and services of the industry under attack. This has been especially evident in industries where analog products are giving way to digital equivalents. The strategic challenge is to develop sufficient knowledge to support a shift to those new technologies and markets before non-traditional competitors make significant inroads in those markets, while not abandoning its years of experience and knowledge about physical imaging that is supporting its core business. This long learning lead-time or “knowledge friction” highlights the importance of benchmarking and evaluating the strengths, weaknesses, opportunities and threats of an organization’s current knowledge platform and position, as this knowledge provides the primary opportunity from which to compete and grow over the near-to-intermediate term. This must, in turn, be balanced against the organization’s long term plans for developing its knowledge platform. Knowledge is not static and what is innovative knowledge today will ultimately become the core knowledge of tomorrow. Thus defending and growing a competitive position based on strategic knowledge asset requires continual learning and knowledge acquisition. The ability of an organization to learn, accumulate knowledge from its experiences, and reapply that knowledge is itself a skill or competence that, beyond the core competencies directly related to delivering its product or service, may provide strategic advantage. 1.14.1 Asset Value of Knowledge How valuable is knowledge? The value is in the eyes of the beholder - opinions vary widely. However, there are several directions you can approach this from: Market value: what is specific knowledge assets worth on the open market e.g. a team of experts, a customer database, and a license for a patent? Cost: how much does it cost to train a new hire? How many person-days went into developing your intranet content? 43


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Replacement cost: if you had a disaster (a team leaving, your computer records destroyed), what would it cost today to get back to where you started? Liability cost: how exposed are you to legal liability e.g. for product traceability, for long overlooked terms in extant contracts? Many organizations do not have a handle on the value of their assets. They spend a fortune monitoring and accounting for physical assets; yet ignore those assets - that according to most surveys - are worth 5-10 time more than the assets recorded on the company’s balance sheet. Knowledge aware organizations consider human capital as an asset. It is one several components of intellectual capital - others are customer capital, structural capital and intellectual property. Benefits Potential For most organizations the real value of knowledge management is in the benefits it brings to the bottom line. These benefits range from increased knowledge worker productivity, to faster time-to-market for new products, to better customer service. Typically the benefits fall into the following categories: Information and knowledge benefits - retrieving vital information faster, gaining access to expertise, having all the required information accessible in one pace (e.g. through a portal) Intermediate benefits - minimizing duplication, sharing knowledge across organizational boundaries, getting new hire up to speed faster Organizational benefits - reducing costs, increasing productivity, growing asset valuation, innovation Customer and stakeholder benefits - better products and services, higher quality, better value. SUMMARY Knowledge management, as it is practiced today, is a system of technologies focused upon the delivery of strategically useful knowledge and expertise, the availability of which facilitates effective collaboration and timely decision-making. The major objectives of KM are creating knowledge repositories, improving knowledge access, enhancing the knowledge environment and managing knowledge as an asset. Effective knowledge management typically requires an appropriate combination of organisational, social, and managerial along with the deployment of appropriate technology. Technology is a facilitator of knowledge management, a tool to assist individuals and groups in creation, capturing and distribution of knowledge.

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Technology and knowledge are now the key factors of production. Various observers describe today’s global economy as one in transition to a ‘knowledge economy’, or an ‘information society’. The knowledge economy usually involve the production of knowledge-intensive goods (like software), and the large-scale capture, movement and utilisation of information using sophisticated network infrastructure (such as computers, cable, fiber and routers).

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The various experts’ vision is that India will become a leader in the global knowledge economy by 2010. This will be the result of a highly focused effort to achieve global thought leadership in a few select fields that offer the highest potential for Knowledge Process Outsourcing (KPO). Effective knowledge management typically requires an appropriate combination of organisational, social, and managerial along with the deployment of appropriate technology. Technology is a facilitator of knowledge management, a tool to assist individuals and groups in creation, capturing and distribution of knowledge. Knowledge management strategy is termed as an approach undertaken by an organization to use its information and knowledge resources for building competitive strength and sustainable growth for realizing that pursuing KM strategy can enable it to dramatically reduce cycle time and costs, increase sales, and to meet the customer needs. Effective knowledge management is of vital importance for any enterprise with a quest to ensure viability and survival. Enterprises need to develop a KM strategy which impinges on all areas of the organization and requires a corporate approach to make it work. Knowledge strategy designs an organisation’s future based on using knowledge effectively. Knowledge strategy starts with the notion that an organisation’s business strategy should guide its planning for knowledge management. Therefore, knowledge strategy follows business strategy. The first activity in knowledge strategy is understanding the current business strategy then progressing that strategy as the basis for organizational analysis. Business organizations are coming to view knowledge as their most valuable and strategic asset, and bringing that knowledge to bear on problems and opportunities as their most important capability. They are realizing that to remain competitive they must explicitly manage their intellectual assets and capabilities. SHORT QUESTIONS 1. 2. 3. 4.

Define ‘knowledge management’. What is intellectual capital? What are the components of knowledge cycle? List down the domains of knowledge management. 45


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5. Define ‘knowledge economy’. 6. What is groupware? 7. Distinguish between knowledge management and expert system. 8. Mention the difference between knowledge portal and corporate portal? 9. What is semantic network? 10. What do you understand by the word knowledge management matrix? LONG QUESTIONS 1. List down and explain the various objectives of knowledge management. 2. What is the need for KM initiation in today’s context in an organization? 3. Explain the KM cycle with an example. 4. List out the uses of KM for an organization. 5. Trace the history and evolution of knowledge management. 6. Compare ‘industrial economy’ with ‘knowledge economy’. 7. What are the characteristics of knowledge economy? 8. What are the implications of knowledge economy to business and policy makers? 9. Analyse the chances of India becoming world’s leading knowledge economy. 10. Explain the various key technologies needed for the KM programs? 11. Why KM strategy is the need of the hour in today’s competitive environment? 12. Explain the four-phased approach for prioritizing the knowledge strategy. 13. “Knowledge is considered as the most important strategic assets” Do you agree? Why?

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UNIT II

KNOWLEDGE ACQUISITION AND PROCESSING 2.1 INTRODUCTION The ability to manage knowledge is becoming increasingly more crucial in today’s knowledge economy. Knowledge is regarded as valuable commodity that is embedded in products, and in the tacit knowledge of highly mobile employees. The acquisition, creation, processing and dissemination of knowledge have become important for competitiveness in an organization. This chapter deals with the various facets of knowledge by elaborating its meaning, attributes, formation, types as well as its sources, conversion and diffusion. 2.2 LEARNING OBJECTIVES After studying this Unit, you should be able to understand the following: • • • • • •

Outline the meaning and forms of knowledge and its attributes Overview the knowledge formation in an organization What is organizational knowledge? Compare the differences between tacit and explicit knowledge Identify the various sources of knowledge Describe the different phases of knowledge development

2.3 PERSPECTIVES ON KNOWLEDGE Unlike capital and labour, knowledge strives to be a public good. Once knowledge is discovered and made public, there is zero marginal cost to sharing it with others. Secondly, the creator of knowledge finds it hard to prevent others from using it. Instruments such as trade secrets protection and patents, copyright, and trademarks provide the creator with some protection. There are different kinds of knowledge that can usefully be distinguished. Knowwhat, or knowledge about facts, is nowadays diminishing in relevance. Know-why is knowledge about the natural world, society, and the human mind. Know-who refers to the world of social relations and is knowledge of who knows what and who can do what. 47


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Knowing key people is sometimes more important to innovation than knowing scientific principles. Know-where and know-when are becoming increasingly important in a flexible and dynamic economy. Know-how refers to skills, the ability to do things on a practical level. The implication of the knowledge economy is that there is no alternative way to prosperity than to make learning and knowledge-creation of prime importance. There are different kinds of knowledge. “Tacit knowledge” is knowledge gained from experience, rather than that instilled by formal education and training. In the knowledge economy tacit knowledge is as important as formal, codified, structured and explicit knowledge. A country’s capacity to take advantage of the knowledge economy depends on how quickly it can become a “learning economy’. Learning means not only using new technologies to access global knowledge, it also means using them to communicate with other people about innovation. In the “learning economy” individuals, firms, and countries will be able to create wealth in proportion to their capacity to learn and share innovation. At the level of the organisation learning must be continuous. Organisational learning is the process by which organisations acquire tacit knowledge and experience. Such knowledge is unlikely to be available in codified form, so it cannot be acquired by formal education and training. Instead it requires a continuous cycle of discovery, dissemination, and the emergence of shared understandings. Successful firms are giving priority to the need to build a “learning capacity” within the organisation. 2.3.1 Data, Information and Knowledge Before we understand what knowledge means, let us understand the knowledge hierarchy. In common parlance, it is often referred to as DIKW hierarchy. The four levels that we deal with are data, information, knowledge, and wisdom. Data may be regarded as a commodity, value is added to data when they are processed into information and in turn information gains further value when it is applied in new contexts becoming transformed into enterprise specific knowledge. Knowledge is also defined as information to which experience, context, interpretation and reflection are added by individuals so that it becomes a high value form of information. In these circumstances knowledge can be utilized in novel ways - making predictions, for example – thereafter being retained within the organization as organizational knowledge. Contextualized knowledge is regarded as the outcome, or product, of a learning process, because it becomes owned as organizational, such knowledge is sticky in the sense that it is both localized and contextualized. And thus it is argued that organizational knowledge is socially constructed because its added value derives from an intra-organizational social process – the process of sharing. Information gains further value when it is used in new contexts and is transformed into enterprise specific knowledge in the process. 48



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Figure 1.1 The Continuum of Understanding One gains knowledge through context (experiences) and understanding. When one has context, one can weave the various relationships of the experiences. The greater the context, the greater the variety of experiences that one is able to pull from. The greater one understands the subject matter, the more one is able to weave past experiences (context) into new knowledge by absorbing, doing, interacting, and reflecting. Thus, understanding is a continuum: Data comes about through research, creation, gathering, and discovery. Information has context. Data is turned into information by organizing it so that we can easily draw conclusions. Data is also turned into information by “presenting” it, such as making it visual or auditory. Knowledge has the complexity of experience, which come about by seeing it from different perspectives. This is why training and education is difficult - one cannot count on one person’s knowledge transferring to another. Knowledge is built from scratch by the learner through experience. Information is static, but knowledge is dynamic as it lives within us. Wisdom is the ultimate level of understanding. As with knowledge, wisdom operates within us. We can share our experiences that create the building blocks for wisdom, however, it need to be communicated with even more understanding of the personal contexts of our audience than with knowledge sharing. Often, the distinctions between data, information, knowledge, and wisdom continuum are not very discrete, thus the distinctions between each term often seem more like shades of gray, rather than black and white. Data and information deal with the past. They are based on the gathering of facts and adding context. Knowledge deals with the present. It becomes a part of us and enables to

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perform. However, when we gain wisdom, we start dealing with the future as we are now able to vision and design for what will be, rather than for what is or was. KM Viewpoint 1.1 An Example This example uses a bank savings account to show how data, information, knowledge, and wisdom relate to principal, interest rate, and interest. Data: The numbers 100 or 5%, completely out of context, are just pieces of data. Interest, principal, and interest rate, out of context, are not much more than data as each has multiple meanings which are context dependent. Information: If I establish a bank savings account as the basis for context, then interest, principal, and interest rate become meaningful in that context with specific interpretations. • •

Principal is the amount of money, Rs.100, in the savings account. Interest rate, 5%, is the factor used by the bank to compute interest on the principal.

Knowledge: If I put Rs.100 in my savings account, and the bank pays 5% interest yearly, then at the end of one year the bank will compute the interest of Rs.5 and add it to my principal and I will have Rs.105 in the bank. This pattern represents knowledge, which, when I understand it, allows me to understand how the pattern will evolve over time and the results it will produce. In understanding the pattern, I know, and what I know is knowledge. If I deposit more money in my account, I will earn more interest, while if I withdraw money from my account, I will earn less interest. Wisdom: Getting wisdom out of this is a bit tricky, and is, in fact, founded in systems principles. The principle is that any action which produces a result which encourages more of the same action produces an emergent characteristic called growth. And, nothing grows forever for sooner or later growth runs into limits. If one studied all the individual components of this pattern, which represents knowledge, they would never discover the emergent characteristic of growth. Only when the pattern connects, interacts, and evolves over time, does the principle exhibit the characteristic of growth. Now, if this knowledge is valid, why doesn't everyone simply become rich by putting money in a savings account and letting it grow? The answer has to do with the fact that the pattern described above is only a small part of a more elaborate pattern which operates over time. People don't get rich because they either don't put money in a savings account in the first place, or when they do, in time, they find things they need or want more than being rich, so they withdraw money. Withdrawing money depletes the principal and subsequently the interest they earn on that principal. Getting into this any deeper is more of a systems thinking exercise than is appropriate to pursue here.

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2.3.2 Defining knowledge

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Knowledge is the process of translating information (such as data) and past experience into a meaningful set of relationships which are understood and applied by an individual. Knowledge is the perception of the agreement or disagreement of two ideas - John Locke Locke gave us the first hint of what knowledge is all about. Since that time, others have tried to refine it. Davenport and Prusak define knowledge as, “a fluid mix of framed experience, contextual information, values and expert insight that provides a framework for evaluating and incorporating new experiences and information.” Notice that there are two parts to this definition: •

First, there is content: “a fluid mix of framed experience, contextual information, values and expert insight.” This includes a number of things that we have within us, such as experiences, beliefs, values, how we feel, motivation, and information.

•

The second part defines the function or purpose of knowledge, “that provides a framework for evaluating and incorporating new experiences and information.” Notice how this relates back to Locke’s definition — we have within us a framework (one idea) that we use for evaluating new experiences (the second idea).

“Knowledge is information that changes something or somebody — either by becoming grounds for actions, or by making an individual (or an institution) capable of different or more effective action.” - Peter F. Drucker 2.4. KNOWLEDGE ATTRIBUTES Knowledge is commonly distinguished from data and information. Data represent observations or facts out of context, and therefore not directly meaningful. Information results from placing data within some meaningful context, often in the form of a message. Knowledge is that which we come to believe and value based on the meaningfully organized accumulation of information (messages) through experience, communication or inference. Knowledge can be viewed both as a thing to be stored and manipulated and as a process of simultaneously knowing and acting - that is, applying expertise. As a practical matter, organizations need to manage knowledge both as object and process. Although knowledge is increasingly being viewed as a commodity or an intellectual asset, it possesses some attributes that are radically different from those of other valuable commodities. These knowledge attributes includes the following: 1. Knowledge exists everywhere. Even in an organization where strong KM practices don’t exist, there are islands of knowledge. Knowledge about products, customers, markets, and operational issues, the existence is haphazard or unorganized.

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2. Knowledge is perishable. What knowledge is used today would become outdated tomorrow. Sustained efforts need to be put to imbibe new information and unlearn old and outdated knowledge. 3. Knowledge is an asset. The brands, patents, special skills, and customer relations of an organization are treated as assets. Treating knowledge as a tangible asset allows for a value to be imputed to knowledge repositories. For example companies can publish a set of Intellectual Capital Account annually so that investors and other stakeholders can value the business for its intellectual worth. 4. Use of knowledge does not consume it. 5. Transfer of knowledge does not result in losing it. 6. Knowledge is abundant, but the ability to use it is scarce. 7. Much of the organization’s knowledge goes out of the organization. 8. Knowledge can be tacit or explicit. Tacit knowledge is subconsciously understood and applied, difficult to articulate, developed from direct experience and action, and usually shared through highly interactive conversation, story-telling and shared experience. Explicit knowledge, in contrast, can be more precisely and formally articulated. Therefore, although more abstract, it can be more easily codified, documented, transferred or shared. Explicit knowledge is playing an increasingly large role in organizations, and it is considered by some to be the most important factor of production in the knowledge economy. Imagine an organization without procedure manuals, product literature, or computer software. 9. Knowledge may be of several types, each of which may be made explicit. Knowledge about something is called declarative knowledge. A shared, explicit understanding of concepts, categories, and descriptors lays the foundation for effective communication and knowledge sharing in organizations. Knowledge of how something occurs or is performed is called procedural knowledge. Shared explicit procedural knowledge lays a foundation for efficiently coordinated action in organizations. Knowledge why something occurs is called causal knowledge. Shared explicit causal knowledge, often in the form of organizational stories, enables organizations to coordinate strategy for achieving goals or outcomes. 10. Knowledge also may range from general to specific. General knowledge is broad, often publicly available, and independent of particular events. Specific knowledge, in contrast, is context-specific. General knowledge, its context commonly shared, can be more easily and meaningfully codified and exchanged, especially among different knowledge or practice communities. Codifying specific knowledge so as to be meaningful across an organization requires its context to be described along with the focal knowledge. This, in turn, requires explicitly defining contextual categories and relationships that are meaningful across knowledge communities. To see how difficult (and important) this may be, ask people from different parts of your organization to define a customer, an order, or even your major lines of business, and see how much the responses vary.

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11. Knowledge relates to place and context. For example, your father’s knowledge about farming is specific to a particular place and a particular time from say 1920 to the 1990s. Some of what he knows about farming could be adapted to other circumstances, but most of his knowledge pertains directly to paddy and cattle production in that particular place. My knowledge and yours also is related intimately to the areas where we grew up and where we live.

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12. All information is not knowledge, and all knowledge is not valuable. The key is to find the worthwhile knowledge within a vast sea of information. 2.5 FUNDAMENTALS OF KNOWLEDGE FORMATION “Knowledge is power”, knowledge management helps us to share, learn and regenerate the new knowledge. Knowledge is the most important asset and greatest competitive advantage of many organizations today. Simultaneously, it can be observed that many organizations realize it is highly problematic and complicated to collect, store, retrieve, find, disseminate and reuse knowledge in modern fast changing organization. Knowledge and information is expressed in commonly accepted idea, information arguably becomes knowledge. Knowledge is intuitive, hard to communicate and difficult to express in words and chunk of it’s not stored in database but in the minds of people who work in formation of new knowledge. It is supported by formal process and structures for its acquisition, sharing and utilization. The role of information, knowledge and digital technologies that manipulate them, have become the crucial factors in the economy. Hence, in the plan and policies, activities of every organization require familiarity with basics of information and knowledge. 2.5.1 Knowledge Formation One of the basic problems is understanding the characteristics of “Knowledge formation”. From ancient times the senses have been thought to have the role of channels through which knowledge arrives in to the organism from the environment. The concept of the senses as “Windows to Knowledge” seemed so strong and irrefutable that attempts to treat organism and environment as one system. The traditional concept of the senses as transmitters of knowledge is based explicitly on the idea of two systems (organism and environment) between which the transfer of knowledge occurs. This relationship has been formulated in recent decades with the help of information theory. Knowledge formation is based on information transmission carried out through signals (Stimuli), in which the information is stored with help of a code. Knowledge becomes obsolete as soon as it is formed or created. New knowledge has to be created continuously in order for a company to survive in this competitive business environment. In practical sense, knowledge management is the process of continuously creating new knowledge, disseminating it widely through the organization, and embodying it quickly in new products/services, technologies and systems. 53


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2.5.2 Flows of knowledge Knowledge and information have a long tradition in research. Notions of information became prominent in the middle years of the 20th century, more recently, with the advent of powerful information technologies, information processing has lost its role as a key bottleneck in organizations, and instead, the main challenge to organizations is now seen as producing and processing knowledge. The focus on knowledge is shared by quite a few recent approaches, including organizational, resource-based and knowledge-based views. Knowledge is what has been learned from experience or study. It is a broad concept that usually includes insights, interpretations, and information. Knowledge can be distinguished from information by its inclusion of interpretations, from beliefs by its higher degree of validity, and from wisdom by its more transient veridical, knowledge consists of assumptions about problems and their solutions. Notions of knowledge flows vary somewhat in the literature; some authors have seen knowledge flows as transfer of skills and technology between organizations. Some even understand knowledge flows as a multistage process that might involve initiation, implementation, and integration or search and transfer. Knowledge flows as the aggregate volume of know-how and information transmitted per unit of time, including via telephone, e-mail, regular mail, policy revisions, meetings, shared technologies, and reviews of prototypes. Knowledge is involving three processes viz., first process is encoding—organizations learn by encoding inferences from experiences in organizational routines that guide behaviour. The second and third processes are the twin processes of exploration and exploitation. Exploration captures “search, variation, risk taking, experimentation, play, flexibility, discovery, innovation”. Exploitation captures “refinement, choice, production, efficiency, selection, implementation, execution”. Codification, exploration, and exploitation describe different modes of organizational knowledge production. Codification generates knowledge encoded in forms that facilitate its transmission to others. Exploration generates new, unsettled knowledge with potentially high but uncertain returns. Exploitation generates incremental knowledge with moderate but certain and immediate returns. These differences suggest that the three modes of learning generate knowledge that varies in fluidity and relevance to others and thereby can stimulate or constrain knowledge flows from originating units to other parts of the organization. 2.6 ORGANISATIONAL KNOWLEDGE What is organizational knowledge? In the organizational context, knowledge can be looked at as information that is tested against the business rules of the organization and found to be valid by knowledgeable individuals and is therefore elevated to a level of validated information or knowledge.

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Organizational knowledge is the collective sum of human-centered assets, intellectual property assets, infrastructure assets, and market assets. It is processed information embedded in routines and processes that enable action. It is also knowledge captured by the organization system’s processes, products, rules and culture.

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Organizational knowledge consists of five different types of knowledge: •

Knowing which information is needed (Know what);

•

Knowing how information must be processed (Know how);

•

Knowing why information is needed (Know why);

•

Knowing where information can be found to achieve a specific result (Know where);

•

Knowing when which information is needed (Know when).

•

Individual construct organizational knowledge by sharing the above five types of knowledge with other employees.

Similarly, individual knowledge in an organization consists of four different types of knowledge: •

“Know-what” is the basic knowledge that individuals can acquire through extensive Training;

•

“Know-how” is the ability to apply “know-what” knowledge to complex realworld problems;

•

“Know-why” is deep knowledge of cause-and-effect relationships; and

•

“Self-motivated creativity” is the highest level of knowledge and it consists of will, motivation and adaptability.

The value of organizational knowledge can increase markedly as an organization helps its employee develop self-motivated creativity, and leverage this type of knowledge throughout the organization. Characteristics of organizational knowledge Key characteristics of organizational knowledge are as follows: •

Organizational knowledge is knowledge that is shared among organizational members;

•

Organizational knowledge, which is created via individual knowledge, is more than the sum of individual knowledge;

•

Complete organizational knowledge is achieved only when individuals keep modifying their knowledge through interactions with other organizational members;

•

Organizational knowledge is distributed;

•

Organizational knowledge is created and managed by individuals who act autonomously within a decision domain. 55


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Thus, from an organizational perspective knowledge can be defined as an entity that can be generated, acquired, modified, transferred and applied for the creation of value. 2.7 TACIT AND EXPLICIT KNOWLEDGE In a global economy, it is important to create and sustain an organization as a knowledge creating company and develop the knowledge management system to manage it. Tacit and explicit knowledge are the two components of organizational knowledge and let us note the important differences between what is called tacit and explicit knowledge which appears to be in widespread use. 2.7.1 What is tacit knowledge? Tacit knowledge refers to the personal knowledge embedded in individual experience and involves intangible factors, such as personal beliefs, perspective, and the value system. Tacit knowledge is hard to articulate with formal language (hard, but not impossible). It contains subjective insights, intuitions, and hunches. Before tacit knowledge can be communicated, it must be converted into words, models, or numbers that can be understand. In addition, there are two dimensions to tacit knowledge: Technical Dimension (procedural): This encompasses the kind of informal and skills often captured in the term know-how. For example, a craftsperson develops a wealth of expertise after years of experience. But a craftsperson often has difficulty articulating the technical or scientific principles of his or her craft. Highly subjective and personal insights, intuitions, hunches and inspirations derived from bodily experience fall into this dimension. Cognitive Dimension: This consists of beliefs, perceptions, ideals, values, emotions and mental models so ingrained in us that we take them for granted. Though they cannot be articulated very easily, this dimension of tacit knowledge shapes the way we perceive the world around us. Tacit knowledge is generally described as: • • • •

subconsciously understood or applied difficult to articulate developed from direct action and experience shared through conversation, story-telling etc

Polanyi defines that “tacit knowledge is personal, context-specific and therefore difficult to articulate”. It may be compared to skill acquisition for example swimming. It may be possible to read the ‘how-to’ manual but such manuals do not embody the full reality of the experience in context. For instance swimming in a pool is very different from swimming in the sea.

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According to Pan and Scarbrough, “Tacit knowledge is not available as a text. . . .It involves intangible factors embedded in personal beliefs, experiences, and values.”

NOTES

Nonaka and Takeuchi refer to tacit knowledge “as knowledge that comprises experience and work knowledge that resides only with the individual. Platts and Yeung considers tacit knowledge as “knowledge-in-action” which presumes that this is knowledge that has not been articulated as opposed to explicit knowledge that is readily accessible within the organizational domain. Blumentitt et al contend that information can be captured and stored in digital form whereas tacit knowledge repositories reside only in intelligent systems that are within individuals. The knowledge management literature recognises the growing importance of knowledge-based activities as being important for innovation, especially in knowledge intensive business services and for impact on strategy development and implementation. The literature recognises the potential value of tacit knowledge and the general inability of organizations to gather an individual’s experiences although there are views emerging on how attempts at capturing tacit knowledge might be effected. Whatever the difficulties the argument for finding an effective means of capturing the experiences and skills of any workforce is compelling and it may be that there will never be more than guidelines since any successful knowledge management system will be essentially unique to the organization in which it is operated. What is essential is that whatever any organization takes from the literature an organizational concept of knowledge management is developed alongside an understanding of how it can be used within that organization to gain competitive advantage. To make wider use of the tacit knowledge of individuals, managers are urged to identify the knowledge possessed by various individuals in an organization and then to arrange the kinds of interactions between knowledgeable individuals that will help the organization perform its current tasks, transfer knowledge from one part of the organization to another, and/or create new knowledge that may be useful to the organization. Let us consider an example (See Box of KM – Viewpoint) of current practice in each of these activities that are typical of the tacit knowledge approach. Most managers of organizations today do not know what specific kinds of knowledge the individuals in their organization know. As firms become larger, more knowledge intensive, and more globally dispersed, the need for their managers to “know what we know” is becoming acute. Thus, a common initiative within the tacit knowledge approach is usually some effort to improve understanding of who knows about what in an organization - an effort that is sometimes described as an effort to create “know who” forms of knowledge.

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KM Viewpoint 1.1 An example of such an effort is the creation within Philips, the global electronics company, of a “yellow pages” listing experts with different kinds of knowledge within Philips’ many business units. Today on the Philips intranet one can type in the key words for a specific knowledge domain - say, for example, knowledge about the design of optical pickup units for CD/DVD players and recorders - and the yellow pages will retrieve a listing of the people within Philips worldwide who have stated that they have such knowledge. Contact information is also provided for each person listed, so that anyone in Philips who wants to know more about that kind of knowledge can get in touch with listed individuals. Case examples of tacit knowledge in practice An example of the tacit knowledge approach to transferring knowledge within a global organization is provided by Toyota. When Toyota wants to transfer knowledge of its production system to new employees in a new assembly factory, such as the factory recently opened in Valenciennes, France, Toyota typically selects a core group of two to three hundred new employees and sends them for several months training and work on the assembly line in one of Toyota’s existing factories. After several months of studying the production system and working alongside experienced Toyota assembly line workers, the new workers are sent back to the new factory site. These repatriated workers are accompanied by one or two hundred long-term, highly experienced Toyota workers, who will then work alongside all the new employees in the new factory to assure that knowledge of Toyota’s finely tuned production process is fully implanted in the new factory. Toyota’s use of Quality Circles also provides an example of the tacit knowledge approach to creating new knowledge. At the end of each work week, groups of Toyota production workers spend one to two hours analyzing the performance of their part of the production system to identify actual or potential problems in quality or productivity. Each group proposes “countermeasures” to correct identified problems, and discusses the results of countermeasures taken during the week to address problems identified the week before. Through personal interactions in such Quality Circle group settings, Toyota employees share their ideas for improvement, devise steps to test new ideas for improvement, and assess the results of their tests. This knowledge management practice, which is repeated weekly as an integral part of the Toyota production system, progressively identifies, eliminates, and even prevents errors. As improvements developed by Quality Circles are accumulated over many years, Toyota’s production system has become one of the highest quality production processes in the world.

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Tacit Knowledge Contextual Mental Processes Difficult to Transfer

Tangible Systematic Ease of Transfer

Explicit Knowledge

Figure 1.2 Two Types of Knowledge 2.7.2 What is explicit knowledge? Explicit knowledge refers to the contents that has been captured in some tangible form and can be articulated into formal language, including grammatical statements (words and numbers), mathematical expressions, specifications, manuals, etc. Explicit knowledge can be readily transmitted to others. Also, it can easily be processed by a computer, transmitted electronically, or stored in databases. An example of explicit knowledge with which we are all familiar is the formula for finding the area of a rectangle (i.e., length times width). Other examples of explicit knowledge include documented best practices, the formalized standards by which an insurance claim is adjudicated and the official expectations for performance set forth in written work objectives Explicit knowledge is increasingly being emphasised in both practice and literature, as a management tool to be exploited for the manipulation of organizational knowledge. Groupware, intranets, list servers, knowledge repositories, database management and knowledge action networks allow the sharing of organizational knowledge. Tools such as co-coordinated databases, groupware systems, intranets and internets are seen as the ultimate knowledge management systems for initiating and supporting discussion forums and communities of practice. Managers hope that these tools will retain knowledge within the company when employees have left and also that this will encourage learning and the flourishing of communities of interest across functional boundaries. Working from the premise that important forms of knowledge can be made explicit, the explicit knowledge approach also believes that formal organizational processes can be used to help individuals articulate the knowledge they have to create knowledge assets. The explicit knowledge approach also believes that explicit knowledge assets can then be 59


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disseminated within an organization through documents, drawings, standard operating procedures, manuals of best practice, and the like. Information systems are usually seen as playing a central role in facilitating the dissemination of explicit knowledge assets over company intranets or between organizations via the internet. Usually accompanying the views that knowledge can be made explicit and managed explicitly is the belief that new knowledge can be created through a structured, managed, scientific learning process. Experiments and other forms of structured learning processes can be designed to remedy important knowledge deficiencies or market transactions or strategic partnering may be used to obtain specific forms of needed knowledge or to improve an organization’s existing knowledge assets. The recommendations for knowledge management practice usually proposed by researchers and consultants working within the explicit knowledge approach focus on initiating and sustaining organizational processes for generating, articulating, categorizing, and systematically leveraging explicit knowledge assets. Some examples of cases of knowledge management practice in this mode help to illustrate this approach. Case examples of explicit knowledge in practice In the 1990s, Motorola was the global leader in the market for pagers. To maintain this leadership position, Motorola introduced new generations of pager designs every 1215 months. Each new pager generation was designed to offer more advanced features and options for customization than the preceding generation. Using modular product architectures to create increasingly configurable product designs, Motorola was able to increase the number of customizable product variations it could offer from a few thousand variations in the late 1980s to more than 120 million variations by the late 1990s. In addition, a new factory with higher-speed, more flexible assembly lines was designed and built to produce each new generation of pager. To sustain this high rate of product and process development, Motorola formed teams of product and factory designers to design each new generation of pager and factory. At the beginning of their project, each new team of designers received a manual of design methods and techniques from the team that had developed the previous generation of pager and factory. The new team would then have three deliverables at the end of their project: (i) an improved and more configurable nextgeneration pager design, (ii) the design of a more efficient and flexible assembly line for the factory that would produce the new pager, and (iii) an improved design manual that incorporated the design knowledge provided to the team in the manual it received - plus the new and improved design methods that the team had developed to meet the product and production goals for its project. This manual would then be passed on to the next design team given the task of developing the next generation of pager and its factory. In this way, Motorola sought to make explicit and capture the knowledge developed by its engineers during each project and to systematically leverage that knowledge in launching the work of 60



the next project team. In addition to its tacit knowledge management practice of moving new employees around to transfer knowledge of its production system, Toyota also follows a highly disciplined explicit knowledge management practice of documenting the tasks that each team of workers and each individual worker is asked to perform on its assembly lines. These documents provide a detailed description of how each task is to be performed, how long each task should take, the sequence of steps to be followed in performing each task, and the steps to be taken by each worker in checking his or her own work. When improvements are suggested by solving problems on the assembly line as they occur or in the weekly Quality Circle meetings of Toyota’s teams of assembly line workers, those suggestions are evaluated by Toyota’s production engineers and then formally incorporated in revised task description documents. In addition to developing well-defined and documented process descriptions for routine, repetitive production tasks, some organizations have also created explicit knowledge management approaches to supporting more creative tasks like developing new products.

NOTES

In the Chrysler unit of DaimlerChrysler Corporation, for example, several “platform teams” of 300-600 development engineers have responsibility for creating the next generation platforms (A platform includes a system of standard component types and standardized interfaces between component types that enable “plugging and playing” different component variations in the platform design to configure different product variations) on which Chrysler’s future automobiles will be based. Each platform team is free to actively explore and evaluate alternative design solutions for the many different technical aspects of their vehicle platform. However, each platform team is also required to place the design solution it has selected for each aspect of their vehicle platform in a “Book of Knowledge” on Chrysler’s intranet. This catalog of developed design solutions is then made available to all platform teams to consult in their development processes, so that good design solutions developed by one platform team can also be located and used by other platform teams. Other firms have taken this explicit knowledge management approach to managing knowledge in product development processes even further. Fanuc Automation, one of the world’s leading industrial automation firms, develops design methodologies that are applied in the design of new kinds of components for their factory automation systems. In effect, instead of leaving it up to each engineer in the firm to devise a design solution for each new component needed, GE Fanuc’s engineers work together to create detailed design methodologies for each type of component the firm uses. These design methodologies are then encoded in software and computerized so that the design of new component variations can be automated. Desired performance parameters for each new component variation are entered into the automated design program, and GE Fanuc’s computer system automatically generates a design solution for the component. In this way, GE Fanuc tries to make explicit and capture the design knowledge of its engineers and then to systematically re-use that knowledge by automating most new component design tasks. 61


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2.7.3. Typical applications of tacit and explicit knowledge Knowledge databases and repositories (explicit knowledge) - storing information and documents that can be shared and re-used, for example, client presentations, competitor intelligence, customer data, marketing materials, meeting minutes, policy documents, price lists, product specifications, project proposals, research reports, training packs; Knowledge route maps and directories (tacit and explicit knowledge) - pointing to people, document collections and datasets that can be consulted, for example, ‘yellow pages’/’expert locators’ containing CVs, competency profiles, research interests; Knowledge networks and discussions (tacit knowledge) - providing opportunities for face-to-face contacts and electronic interaction, for example, establishing chat facilities/ ’talk rooms’, fostering learning groups and holding ‘best practice’ sessions. 2.7.4. Basic beliefs between tacit and explicit knowledge approaches Table 1.1 Basic beliefs between tacit and explicit KM approaches

2.7.5 Comparison of properties of Tacit Vs Explicit Knowledge Table 1.2 Comparison of properties of tacit Vs explicit knowledge

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2.7.6 Advantages and Disadvantages of Tacit versus Explicit Knowledge Approaches

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Like most alternative approaches to managing, each of the two knowledge management approaches we have discussed has both advantages and disadvantages. Let us now briefly summarize the main advantages and disadvantages of the two approaches. Advantages and Disadvantages of the Tacit Knowledge Approach Advantages 1. 2. 3. 4.

Relatively easy and inexpensive to begin. Employees may respond well to recognition of the (claimed) knowledge. Likely to create interest in further knowledge management processes. Important knowledge kept in tacit form may be less likely to “leak” to competitors.

Disadvantages 1. Individuals may not have the knowledge they claim to have. 2. Knowledge profiles of individuals need frequent updating. 3. Ability to transfer knowledge constrained to moving people, which is costly and limits the reach and speed of knowledge dissemination within the organization. 4. Organization may lose key knowledge if key people leave the organization. Advantages and Disadvantages of the Explicit Knowledge Approach Advantages 1. Articulated knowledge (explicit knowledge assets) may be moved instantaneously anytime anywhere by information technologies. 2. Codified knowledge may be proactively disseminated to people who can use specific forms of knowledge. 3. Knowledge that has been made explicit can be discussed, debated, and improved. 4. Making knowledge explicit makes it possible to discover knowledge deficiencies in the organization. Disadvantages 1. Considerable time and effort may be required to help people articulate their knowledge. 2. Employment relationship with key knowledge workers may have to be redefined to motivate knowledge articulation. 3. Expert committees must be formed to evaluate explicit knowledge assets. 4. Application of explicit knowledge throughout organization must be assured by adoption of best practices.

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2.7.7 Four modes of knowledge creation or conversion - Nonaka’s Knowledge Creation Framework According to Professor Ikujiro Nonaka, knowledge creation is a spiraling process of interactions between explicit and tacit knowledge. The interactions between the explicit and tacit knowledge lead to the creation of new knowledge. The combination of these two kinds of knowledge makes it possible to conceptualize four modes of conversion patterns. The four conversion patterns of knowledge are illustrated in Figure 1.2 below:

From tacit knowledge From explicit knowledge

To tacit knowledge Socialisation

To explicit knowledge Externalization

Internalization

Combination

Figure 1.3 onaka’s SECI Model •

Socialization: from tacit to tacit - Sharing experiences to create tacit knowledge, such as shared mental models and technical skills. This also includes observation, imitation, and practice. However, “experience” is the key, which his why the mere “transfer of information” often makes little sense to the receiver. Takes place between people in meetings or in team discussions.

•

Internalization: from explicit to tacit - Embodying explicit knowledge into tacit knowledge. Closely related to “learning by doing.” Normally, knowledge is verbalized or diagrammed into documents or oral stories. This implies taking explicit knowledge (e.g., a report) and deducing new ideas or taking constructive action. One significant goal of knowledge management is to create technology to help the users to derive tacit knowledge from explicit knowledge.

•

Externalization: from tacit to explicit - The quintessential process of articulating tacit knowledge into explicit concepts through metaphors, analogies, concepts, hypothesis, or models. Note that when we conceptualize an image, we express its essence mostly in language. Articulation among people through dialog (e.g., brainstorming).

•

Combination, from explicit to explicit - A process of systemizing concepts into a knowledge system. Individuals exchange and combine knowledge through media, such as documents, meetings, and conversations. Information is reconfigured by such means as sorting, combining, and categorizing. Formal education and many training programs work this way. This transformation phase can be best supported by technology. Explicit knowledge can be easily captured and then distributed/ transmitted to worldwide audience. 64



2.8 ORGANISATIONAL KNOWLEDGE CREATION

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Knowledge is an important element in the world of business and the ability to distribute and duplicate knowledge across a range of people is the key to its value in organizations. It can reduce time taken to learn new competencies and insights, and save significant costs in lost opportunities. People develop knowledge as an ongoing process through their work. Knowledge evolves as it is reshaped through encounters with new events, information or other people. It may reside within an individual as personalized knowledge, be accessible through others, or stored as a retrievable artifact. Artifacts derived from knowledge creation are facts, concepts, processes, procedures, and principles. These, in turn, are used to help create knowledge in others and are valuable mechanisms for sharing the outcome of knowledge creation. Organizational knowledge relies on collective and individual contributions. It evolves as others review, use and learn from the original knowledge sources. Organizations are increasingly regarding knowledge creation and innovation as core business, as more people spend most of their work time creating and innovating. In projects, meetings and thinktanks, their individual knowledge becomes a part of a collective activity that seeks to build a bank of knowledge for use by the organization. Figure 1.4 illustrates the five stages of organizational knowledge development: knowledge sourcing, knowledge abstraction, knowledge conversion, knowledge diffusion, and knowledge development and refinement. The process of knowledge development is dynamic and responsive, drawing cues and feedback from a range of sources throughout the stages. This feedback may influence subsequent knowledge construction as it provides further cues and information which are considered and evaluated. Let us see the detailed account of the phases of knowledge creation.

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Figure 1.4 Phases of organizational knowledge creation 2.8.1 Knowledge sourcing The identification of knowledge gap between what is known and what needs to be known is often the stimulus for the knowledge creation process. In response to the identification of a knowledge gap, the organization commonly reviews existing sources of guidance held by individuals or other organizational resources. This process of drawing together as many informed knowledge sources as possible is called knowledge sourcing. Sources to be tapped might include specialized and prior knowledge held by individuals within the organization, expert guidance from people such as consultants, organizational record or the firm’s intranet. Learning from previous experience is a significant source of guidance, particularly where the problem under investigation has significant resourcing implications. 66



Knowledge sourcing is an important stage of knowledge creation. The richness and accessibility of the available and known sources greatly influence the outcomes. For example, if an organization wanted to introduce a new customer promotional scheme, it might seek the appropriate sources of guidance from the following: • • • • • •

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Customer feedback Marketing expert’s opinion Previous promo schemes data and their success and failures Available secondary data ]Lessons from competitors similar schemes Contributions from employees concerned with such schemes

Sources of organizational knowledge Following are the few sources of knowledge which are crucial for any organization gain strategic competence. Customer knowledge In virtually every survey, customer knowledge tops the list as an organization’s most vital knowledge. Yet most organizations do not know as much about their customers as they think they do, nor do they integrate their various sources of customer knowledge that the organization already has. Appropriate feedback system may be created to get this valuable source of knowledge. Knowledge in process Normally in an organization an ad hoc activity gradually evolves into a process, that in many cases is automated and hence knowledge is embedded in a procedure or computer program. Generally, the generic high-level activities involve gathering and processing of information which is communicated with other people. This is a vital meta-knowledge that can help an organization to be more effective. Knowledge in people It is said that 90% organizational knowledge is in its people who is valuable and when it is shared, it becomes even more valuable to the organization as a whole. An important part of KM is therefore about creating an environment and culture in which this knowledge is facilitated to be accumulated and people are encouraged to share their knowledge with each other. Organizational memory Many organizations do not know what they already know. Knowledge gained is not recorded for use at another time or place. Effective knowledge programs will therefore put

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significant emphasis on capturing knowledge from every day work and from assignments. Decision diaries, reflection time at meetings and After Action Reviews (ARRs) are commonly adapted tools for this purpose. An ARR, for example, is a technique first developed in the US Army to capture lessons from battle field engagements, while they are still fresh in people’s minds which may be used for future. In this way, an organization can also conduct formal post-assignment reviews to derive lessons and put the knowledge gained into an accessible form for future assignments. Another useful technique is that of ‘knowledge refining’ with which a series of memos, e-mails or meeting minutes are collected for their relevant and reusable content, which is put into an evolving and structured knowledge base. Knowledge relationships This is concerned with depth of personal knowledge arising out of relationship of two people who worked together for a long time and know one another’s approach with regard to what to do and what not to do in situations. When firms reorganize, this knowledge is lost. With the growing need for collaboration with external partners and agencies, organizations need to do more to capture this knowledge and provide forums where these relationships cab be strengthened. 2.8.2 Knowledge abstraction After analyzing the sources of knowledge, the general principles and concepts are generated to guide the construction of the new knowledge. This process is called knowledge abstraction. Knowledge abstraction helps to frame the insights gained from knowledge sourcing and to extrapolate new knowledge from the basic guidelines and issues that have emerged. Where the knowledge seekers are highly expert, they will rely heavily on their own knowledge, with other sources simply validating or enriching that knowledge. Less experienced seekers will rely more heavily on external sources. Think back to the customer promo schemes mentioned before. The target population might be clarified, some approaches ruled out, and some broad principles confirmed. The abstraction of the various sources reduces the complexity of the factors to be considered, and enables the ideas to be converted into outcomes using a sound framework. The process of abstraction can take a long time – particularly if the knowledge involved is politically sensitive, complex or involves working through group consensus (committees). Unfortunately, many organizations do not provide sufficient to reflect and weigh the various sources before abstraction. Failure to carefully build some clear frameworks to guide the knowledge creation process can lead to faulty reasoning and poor outcomes. Knowledge workers need to recognize the importance of reflection and consideration in the knowledge creation process.

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2.8.3 Knowledge conversion

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From abstract foundations, knowledge converts into various forms of useful applications that can be tested and shared with others. Knowledge conversion describes the phase during which the various ideas and principles are refined into specific outcomes. Knowledge can be either codified or embodied. Codified knowledge is knowledge that can be recorded and accessed by others as required. It can be developed into artifacts, such as models, equations and guidelines. Embodied knowledge is the tacit knowledge of individuals. It can be shared through stories, metaphors or personal advice as required. Embodied knowledge is more difficult to access without ongoing engagement with the knowledge creators. Codified knowledge relating to the customer marketing scheme might be in the form of a marketing plan and implementation guidelines, whereas the embodied knowledge would be drawn from the guidelines and insights of the project leaders and experts. Many organizations typically rely on both the forms of knowledge conversion when creating new knowledge. 2.8.4 Knowledge diffusion Knowledge diffusion is the spread of knowledge once it is codified or embodied. In organizational settings, diffusion can occur through communication media such as newsletters, the Intranet, meetings, seminars etc., modeling of new practices, and demonstrations or coaching in specialized procedures. The success of knowledge diffusion depends on the level of previous knowledge held by the audience and the effectiveness of the channels available to share the knowledge. Diffusion occurs best when the recipients can understand and integrate the insights into their own mental constructs. Embodied knowledge, which draws on significant expertise, learning and experience, may be harder to transfer to others. Using the same example, the promotion of new promotional scheme might be disseminated in various ways via the Intranet, published guidelines and presentations relating to the scheme, and so on. The main goal is to share the knowledge with those who will most benefit. A forum of all employees in an organization, for example, is of little value to those who are not directly involved in the new scheme. 2.8.5 Knowledge development and refinement Knowledge is regularly reshaped and further tested through additional experience and feedback. This revolutionary process of knowledge development and refinement is one of the key features of knowledge management, ensuring the knowledge remains current and useful. However, this also place more challenges on organizations that seek to capture and hold knowledge for use by others; such organizations need to ensure that the created knowledge is constantly reviewed and updated to reflect any new understanding that has 69


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been acquired. Consider the promotional scheme again. A pilot study of the scheme may reveal some significant issues relating to the created process. The pilot study thus generates new knowledge to be converted and diffused. SUMMARY Knowledge is regarded as valuable commodity that is embedded in products, and in the tacit knowledge of highly mobile employees. The acquisition, creation, processing and dissemination of knowledge have become important for competitiveness in an organization. There are different kinds of knowledge that can usefully be distinguished. Knowwhat, or knowledge about facts, is nowadays diminishing in relevance. Know-why is knowledge about the natural world, society, and the human mind. Know-who refers to the world of social relations and is knowledge of who knows what and who can do what. Knowing key people is sometimes more important to innovation than knowing scientific principles. Know-where and know-when are becoming increasingly important in a flexible and dynamic economy. Know-how refers to skills, the ability to do things on a practical level. Organizational knowledge is the collective sum of human-centered assets, intellectual property assets, infrastructure assets, and market assets. It is processed information embedded in routines and processes that enable action. It is also knowledge captured by the organization system’s processes, products, rules and culture. Tacit and explicit knowledge are the two components of organizational knowledge. Tacit knowledge refers to the personal knowledge embedded in individual experience and involves intangible factors, such as personal beliefs, perspective, and the value system. Explicit knowledge refers to the contents that has been captured in some tangible form and can be articulated into formal language, including grammatical statements (words and numbers), mathematical expressions, specifications, manuals, etc. Knowledge creation is a spiraling process of interactions between explicit and tacit knowledge. Knowledge is an important element in the world of business and the ability to distribute and duplicate knowledge across a range of people is the key to its value in organizations. There is a need to understand the different phases of organizational knowledge creation and to recognize that each phase is influenced by the access to sources of guidance, and the encouragement to disseminate knowledge to others

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SHORT QUESTIONS 1. 2. 3. 4. 5. 6. 7.

NOTES

Define knowledge. Illustrate by example the possible relationship between knowledge and data. What is meant by organizational knowledge? What is tacit knowledge? What is explicit knowledge? Compare the properties of tacit ant explicit knowledge. What are the sources for knowledge?

LONG QUESTIONS 1. What are the differences between tacit knowledge and explicit knowledge? Give an example of each. 2. List down the various attributes of knowledge and support each with an example. 3. Describe how knowledge is formed in an organization? 4. Enumerate different application areas of tacit and explicit knowledge. 5. What are the advantages and disadvantages of tacit ant explicit knowledge? 6. Explain Nonaka’s knowledge creation framework. 7. Write a detailed account on knowledge abstraction, conversion and diffusion.

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UNIT III

KNOWLEDGE MANAGEMENT SYSTEMS 3.1 INTRODUCTION Today’s business environment witnesses decline in many of the well established organization, diminishing competitive power in the global economy coupled with and the need for organizational renewal and transformation forced many organization to feel the importance of organizational learning. Many senior managers are also convinced of importance in improving organizational learning. Knowledge management must enable organizational learning, not just by giving it direction, but also by permitting, encouraging and facilitating it. Through organizational learning knowledge management can be made into a day-to-day reality in the organization. 3.2 LEARNING OBJECTIVES After studying this Unit, you should be able to understand the following: • • • • • • • • •

Define organizational learning and skillets required for individuals Describe the characteristics of learning organization Outline the five learning disciplines Construct an architecture for organizational learning How to capture and codify knowledge Analyse how tacit knowledge is captured How knowledge repositories functions Know the KM application domains Define collaborative platforms and outline its features

3.3 KNOWLEDGE MANAGEMENT AND ORGANISATIONAL LEARNING Companies that build competitive advantage through effective information and knowledge management must continually refresh and update their intellectual capital. This is the process of organizational learning. Learning is primarily a process of acquiring, assimilating and internalizing inputs for effective and varied uses when required. Learning is the acquisition of useful new knowledge, ideas, skills and/or behaviour patterns. Learning 73


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can be from one’s own experience, from each other, and from customers, suppliers and business patterns. Applying the concept of learning to organizations, organizational learning can be described as the collective learning of the organization. While it does involve learning of individual employees, it is more than just the sum of learning of its individual members. Organizational learning is the process by which the organization acquires, retains and uses information and ideas for its development and for strengthening its self-learning and selfrenewing capacity. Organizational learning thus has the crucial and continuing responsibility for capitalizing on knowledge as the source and base of a leading competitive edge. Organizational learning as the means of acquiring and generating knowledge and skills (i.e., operational knowledge), hence, becomes a key internal driver of the externally focused enterprise strategy. Hence, each organization must build capabilities for managing knowledge and strengthening learning. It is the connection between knowledge and learning which establishes organizational focus and strategy. 3.4 THE CONCEPT OF ORGANISATIONAL LEARNING The term organizational learning refers to continuous improvement of existing approaches and processes and adaptation to change, leading to new goals and/or approaches. Learning needs have to be embedded in the way the organization works. The term embedded means that learning: • • • • •

Is a regular part of the daily work? Is practiced at personal, work unit, and organizational levels Results in solving problems at source Is focused on sharing knowledge throughout the organization Is driven by opportunities to affect significant c change and do better

Organizational learning is the capacity or processes within an organization to maintain or improve performance based on experience. Learning is a systems-level phenomenon, because it stays within the organization even if individuals change. Learning is as much a task as the production and delivery of goods and services. While companies do not usually regard learning as function of production, research on successful firms indicates that three learning-related factors are important for their success: (a) Well-developed core competencies that serve as launch point for new products and services, (b) An attitude that supports continuous improvement in the business’s value-added chain, (c) The ability to fundamentally renew or revitalize business function based on need.

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(d) These factors identify some of the qualities of an effective learning organization that diligently pursues a constantly enhances knowledge base. This knowledge allows for the development of competencies and lead to incremental or transformational change. In these instances, there is assimilation and utilization of knowledge and some kind of integrated learning system to support such “actionable learning”. Indeed, an organization’s ability to survive and grow is based on advantages that stem from core competencies that represent collective learning. These can be generalized as follows:

NOTES

Knowledge acquisition. This stage deals with the development or creation of skills, insights and relationships. Knowledge sharing. This stage involves the dissemination of the learning throughout the organization. Knowledge utilization. This stage provides the integration of learning so that it is broadly available and can be generalized to new situations. Sources for learning include learning at the individual level of an employee, employee ideas, research and development (R&D), customer input, best practice sharing and benchmarking. Learning at individual level Learning at the individual level can be conceptualized as the process of obtaining and retaining skills and information with relevant aptitude that leads to changes and improvements in action and decision making. The process of organizational learning is, however, less well understood than individual learning. All learning can be characterised as occurring at the individual level. The focus of an organization should be on improving the learning, skills and hence competitive advantage of individuals. However, to ensure their effectiveness, individuals have to be able to fully integrate with and be able to maximise the benefits of learning at the organizational level. In this way, the effective organization ensures that an individual’s actions and learning are both supported by, and providing support to, the organization as a whole. Acting together, the individuals that make up the organization are able to learn, work and compete better than they could on their own. Skill sets needed by individuals for organizational learning 1. Ability to understand the culture of the organization 2. Ability to let go of old myths 3. Ability to notice new patterns- language as an indicator • Multitasking • Miniaturization • Short-term memory overload • Low level depression and increasingly angry culture • Changes of speed 75


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4. Ability to develop a clear perspective/ open perspective • Ability to relax • Sense of humor - ability to laugh • Knowing your hishhtory • Insulate hot buttons and fears • Ability to scan for information • Pretend you are an anthropologist and examine what leaders reward, evaluate, and control; what they are paying attention to; and what are they measuring 5. Ability to generate energy with coaching and building self-esteem; ability to bring energy into a room. 6. Ability to learn forever 7. Ability to own your own career 8. Ability to create “safe” environment for others 9. Ability to see what’s coming and what’s leaving so you can make choices faster; faster response time 3.4.1 Definitions for organizational learning (a) “Organizational Learning occurs when the mental models, schemes or cognitive maps that guide behaviour are modified through recognition of a change in information concerning an organization’s environment”. (b) “Organizational Learning occurs through shared insights, knowledge and mental models”. (c) “Organizational learning occurring when individuals, acting from their own images and maps, detect a mismatch of outcomes to expectation which confirms or disconfirms organization theory-in-use” (d) “The transformation process that translates individual learning into organizational domain is termed organizational learning”. It is a process by which individuals share their insights, knowledge and ideas to develop a common understanding. Through this process of learning, organizations enrich their knowledge base, which helps them in knowledge generation and in the long run to face external challenges. An innovative or a product organization would strive to be a learning organization ‘skilled at creating, acquiring and transferring knowledge and modifying its behaviour to reflect new knowledge and insights’. Organizational learning is the development of new knowledge and insights that have the potential to influence behavior. Organizational learning occurs when members of an organization share associations, cognitive systems, and memories. Learning by organizations relies on the people and groups to serve as agents for the transfer of knowledge. Over time, what is learned is built into the structure, culture, and memory of the organization. Lessons (i.e., knowledge) remain within the organization even though individuals may change. The phrases organizational learning and learning organizations are used interchangeably. 76



3.4.2 Benefits of organizational learning

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Organizational learning can result in: 1. Enhancing value to customers through new and improved products and services; 2. Developing new business opportunities; 3. Reducing errors, defects, waste, and related costs; 4. Improving responsiveness and cycle time performance; 5. Increasing productivity and effectiveness in the use of all resources throughout the Organization; and 6. Enhancing the organization’s performance in fulfilling its public responsibilities and service as a good citizen 3.4.3 What is a ‘learning organization’? A learning organization is an organization which has in place systems, mechanisms and processes that are used to continually enhance its capabilities and those who work with it or for it, to achieve sustainable objectives - for them and the communities in which they participate. Learning – both individual and organizational – is the process by which knowledge assets are increased over time. Every organization learns. But, to be successful, managers must seek to align both individual and collective learning with the strategic intent of the firm. This means that as executive design their business strategies, they need to determine what, specifically – and when – their firms need to learn, and create mechanism to do so. For example, if an insurance firm is trying to make inroads into the investment management business, its executives will have to make sure that their firm learns the new business while continuing to advance its knowledge of the insurance business. A knowledge management strategy, therefore, may include hiring new talent, designing new projects, implementing job rotations, and altering organizational structures to facilitate the flow of the new knowledge between existing and new business. Key characteristics of learning organization 1. Team work and team learning. 2. Systemic thinking and mental models. 3. Free vertical and horizontal flow of information. 4. Education and training of the whole workforce. 5. Learning reward system for employees. 6. Continuous improvement of work. 7. Flexibility of employees and company strategies. 8. Decentralized hierarchies and participative management. 9. Constant experimentation. 10. Supportive corporate cultures. 77


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3.4.4 Orientation for effective knowledge dissemination Organizational learning does not always occur in the linear fashions implied by typical learning models. Learning may take place in planned or informal ways. Moreover, knowledge and skill acquisition takes place in the sharing and utilization stages. It is not something that occurs simply by organizing an ‘acquisition effort’. The following are some of the commonly employed orientation by organizations in their quest for effective knowledge dissemination. (a) Knowledge sources Organization needs to carefully assess their source of knowledge, i.e. they need to finalise the extent whether new knowledge is to be developed internally or seek inspiration in external ideas. This distinction is seen as the difference between innovation and adaptation or imitation. Both of these approaches have great merit as opposing styles rather than as normative or negative behaviors. (b) Learning at the individual level Learning at the individual level can be conceptualized as the process of obtaining and retaining skills and information with relevant aptitude that leads to changes and improvements in action and decision making. The process of organizational learning is, however, less well understood than individual learning. All learning can be characterised as occurring at the individual level. The focus of an organization should be on improving the learning, skills and hence competitive advantage of individuals. However, to ensure their effectiveness, individuals have to be able to fully integrate with and be able to maximise the benefits of learning at the organizational level. In this way, the effective organization ensures that an individual’s actions and learning are both supported by, and providing support to, the organization as a whole. This is described as the “creation of shared understandings”. Acting together, the individuals that make up the organization are able to learn, work and compete better than they could on their own. (c) Focus on products and processes Organizations need to decide whether they would prefer to accumulate knowledge about product and service outcomes or about the basic processes underlying various products. (d) Documentation Knowledge is viewed in personal terms as something an individual possesses by virtue of education or experience. This kind of knowledge is lost when a longtime employee leave an organization; processes and insights evaporate because they were not shared or made a part of collective memory. On the other hand, knowledge is defined in more objective, social terms, as being a consensually supported result of information processing. This calls for the development of organizational memory or a publicly documented body of knowledge. 78



(e) Knowledge dissemination

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An organization need to establish an atmosphere in which learning evolves or in which a more structured, controlled approach induces learning. In the more structured approach, the company decides that valuable insights or methods should be shared and used by others across the organization. It uses written communication and formal education methods or certifies learning through writing the procedure down. In the more informal approach, learning is spread through encounters between role models and gatekeepers who compellingly reinforce learning. In another approach, learning occurs when members of an occupational group or work team share their experiences in ongoing dialogue. (f) Organizational learning Organizational learning needs to encounter on methods and tools, to improve what is already being done or on testing the assumptions underling what is being done. Organizational performance problems are more likely due to a lack of awareness or inability to articulate and check underlying assumptions than to a function of poor efficiency. Generally, these learning capabilities reinforce each other. (g) Value-chaining Organization need to build an index of their core competencies and learning investments that need to be valued and supported. Learning investments include allocation of personnel and money to develop knowledge and skill over time, including training and education, pilot projects, developmental assignments, available resources, and so on. If a particular organization is heavily focused on heavy engineering, it would have a natural bias in favor of substantial learning investments in related areas. The value chain can be classified into two categories: internally directed activities of a ‘design and make’ nature, and those more externally focused of a ‘sell and deliver’ nature. The former include R&D, engineering, and manufacturing. The latter are sales, distribution, and service activities. (h) Skill development An organization need to develop both individual and group skills. In this way, an organization can assess how it is doing and improve either one of those skills. It can also develop better ways of integrating individual learning programs with team needs by taking a harder look at the value of group development.

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KM Viewpoint 1.1 EIU Study Survey: The Economic Intelligence Unit (EIU) in co-operation with IBM Consulting Group had conducted an intensive study of emerging Organizational Learning (OL) and Knowledge Management (KM) practices around the globe. Responses were received from 345 companies in 26 countries (1999). Typical OL activities undertaken are: • behavioral changes to improve teamwork; • changing individual and corporate behaviour, • facilitating ongoing, team based and collaborative management , • leading individual or team training activities, • assembly of multi-disciplinary teams to solve business problems. Learning Organizations are considered masters of managing change for financial gains OL, in its broadest sense, refers to a variety of practices and values that enable a company to explore continually new directions and anticipate or even lead change in the marke place and society at large. Benefits 1. Learning enhances a company’s speed, innovative-ness and adaptability Technological change, shorter product life cycle, market shifts and global competition affect some industries more than others, but all companies need to synthesiz information and generate knowledge faster. Learning addresses a company’s desire to better anticipate and adapt to changing market conditions, reach the market with mor innovative products faster than competitors and maximize responsiveness to customers needs. Learning organizations are effective not only at creating and/o acquiring new knowledge; buy also in applying that knowledge to continually improve their tasks and activities. 2. Learning builds shareholder value for the long term. Managerial accounting system that currently guide investment and strategy offer little insight into the value tha human know-how, creativity and experience add to products and services. Skandi and other companies now report intangible assets in their balance sheet. They recognize that learning is the key contributor to value addition, in the long run. Enabling factors 1. Formal business procedures must be balanced with the freedom to create Business organizations discourage people from learning all the time. Every tim someone tells you to do something a certain way because that is the standard way they are telling you not to learn. This type of over-prescription undermine learning. A Company’s official chain of command and formal busines procedures must co-exist with informal personal networks. Best leadership create a balance in the organization between reaping and sowing; production on on hand and building capacity, competence and personal relations on the other. 2. Every company has a different approach. There is no roadmap to becoming learning organization. 3. Culture is the key. A spirit of openness and enthusiasm for continues learning occurs, when leaders actively and continuously promote that values.4. Individual

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NOTES Element Organization Structure Availability of information Trust culture Communication Innovation Managers style Learning systems

Characteristics of a learning Organization Flat hierarchy, decentralized, Dynamic networks Systems in place to make information freely available High level of trust, Self mastery practiced Decentralized communication processes Innovation and risk taking encouraged Facilitator, Coaching style Continual learning and double loop learning

3.4.5 Characteristics of learning organization • • • • • •

They provide continuous learning opportunities. They use learning to reach their goals. They link individual performance with organizational performance. They foster inquiry and dialogue, making it safe for people to share openly. They embrace creative tension as a source of energy and renewal. They are continuously aware of and interact with their environment.

3.4.6 Characteristics of the Traditional organization Vs Learning organization Element

Traditional Organization Efficiency Effectiveness Control

Learning Organization

Distinctive Staff Skills

Excellence Organizational Renewal Facilitator Coach Top down approach Everyone is consulted Road map Learning map Hierarchy Flat structure Dynamic networks People who know People who learn (experts) Mistakes tolerated as par Knowledge is power of learning Adaptive learning Generative learning

Measurement System

Financial measures

Teams

Working groups Departmental boundaries

Both financial and non financial measures Cross functional teams

Shared Values Management Style Strategy/Action Plan Structure Staff Characteristics

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3.4.7 Facilitators for organizational learning The following are some of the key facilitators for organizational learning: 1. The presence of strong marketing research functions for effective environmental scanning. 2. Measures to ensure that feedback regarding organizational functions and processes are adequate. 3. Development of metrics to gauge the effectiveness of organizational learning systems. 4. Process of encouraging pilot testing and experimentation. 5. Availability of core subject matter, experts to provide leadership to learning activities. 6. Free flow of information within the organization. 7. Continuous learning within the organization. 8. Continuous process and system improvement and re-engineering. 9. Proper management support. 3.4.8 The five learning disciplines of Peter Senge In his book The Fifth Discipline, Peter Senge (1990) defined a learning organization as “… a place where people continually expand their capacity to create results they truly desire, where new and expansive patterns of thinking are nurtured, where collective aspiration is set free and where people are continually learning how to learn”. Peter Senge, in particular, posits the radically humanist idea that organizations should become places where people can begin to realize their highest aspirations. He talks of developing worker commitment not compliance; of building shared visions, not imposing a mission statement from above; of effectively reconciling individual and organizational objectives. Senge described the core of a learning organization’s work as based upon five learning disciplines, which represented lifelong programs of both personal and organizational learning and practice. These include: (1) Personal Mastery — Personal mastery is what Peter Senge describes as one of the core disciplines needed to build a learning organization. Personal mastery applies to individual learning, and Senge says that organizations cannot learn until their members begin to learn. Personal Mastery has two components. First, one must define what one is trying to achieve (a goal). Second, one must have a true measure of how close one is to the goal. Individuals who practice personal mastery experience other changes in their thinking. They learn to use both reason and intuition to create. They become systems thinkers who see the interconnectedness of everything around them and, as a result, they feel more connected to the whole. It is exactly this type of individual that one needs at every level of an organization for the organization to learn. Traditional managers have always thought that they had to have all the answers for their organization. The managers of the learning organization know that their staff has the answers. The job of the manager in the learning organization is to be the teacher or coach who helps unleash the creative energy in each individual. Organizations learn through the synergy of the individual learners. 82



(2) Mental Models — a mental model is one’s way of looking at the world. It involves each individual reflecting upon, continually clarifying, and improving his or her internal pictures of the world, and seeing how they shape personal actions and decisions. It is a framework for the cognitive processes of our mind. In other words, it determines how we think and act. A simple example of a mental model comes from an exercise described in The Fifth Discipline Fieldbook. Learning only comes from seeing the world the way it really is.

NOTES

(3) Shared Vision — what does it mean to have a shared vision? A shared vision begins with the individual, and an individual vision is something that one person holds as a truth. It means individuals building a sense of commitment within particular workgroups, developing shared images of common and desirable futures, and the principles and guiding practices to support the journey to such futures. The shared vision of an organization must be built of the individual visions of its members. What this means for the leader in the Learning Organization is that the organizational vision must not be created by the leader, rather, the vision must be created through interaction with the individuals in the organization. Only by compromising between the individual visions and the development of these visions in a common direction can the shared vision be created. The leader’s role in creating a shared vision is to share an own vision with the employees. This should not be done to force that vision on others, but rather to encourage others to share their vision too. Based on these visions, the organization’s vision should evolve. It would be naive to expect that the organization can change overnight from having a vision that is communicated from the top to an organization where the vision evolves from the visions of all the people in the organization. The organization will have to go through major change for this to happen, and this is where OD can play a role. In the development of a learning organization, the OD-consultant would use the same tools as before, just on a much broader scale. (4) Team Learning — this involves relevant thinking skills that enable groups of people to develop intelligence and an ability that is greater than the sum of individual members’ talents. It is a discipline that starts with “dialogue,” the capacity of members of a team to suspend assumptions and enter into a genuine “thinking together.” Team learning is vital because teams, not individuals, are the fundamental learning unit in modern organizations. (5) Systems thinking — this involves a way of thinking about, and a language for describing and understanding forces and interrelationships that shape the behavior of systems. It is a paradigm premised upon the primacy of the whole —the antithesis of the traditional evolution of the concept of learning in western cultures. This discipline helps managers and employees alike to see how to change systems more effectively, and to act more in tune with the larger processes of the natural and economic world. 83


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Once we embrace the idea that systems thinking can improve individual learning by inducing people to focus on the whole system, and by providing individuals with skills and tools to enable them to derive observable patterns of behavior from the systems they see at work, the next step is to justify why systems thinking is even more important to organizations of people. Here, the discipline of systems thinking is most clearly interrelated with the other disciplines, especially with mental models, shared vision, and team learning. 3.5 RCHITECTURE FOR ORGANISATIONAL LEARNING Learning Organisation is an organisation that purposefully takes steps to create architecture to enhance and maximize the potential for explorative and exploitative organizational learning to take place. Team-Based Structure - Teams are the best way of mixing energy with experience and for any organisation teams are good sources of attaining targets effectively and efficiently. Team based structures support continuous learning and pooling of experience and sharing knowledge. Looking at these benefits, a team-based structure is necessary for any organization aiming to become a learning organisation. Empowered Employees - Employee empowerment will make sure that employee take full responsibility for their actions and they work in an open environment this will also facilitate growth of employees and encourage innovation as well as instills the ability to think out of the box. Empowered employees will take more initiative & they will try to solve the problem where and when it will arise; this makes organizational climate more conducive to learning. Open Information - Information should be provided to everyone. Transparency in decision-making must be maintained. Open information builds trust and confidence of employees in the management and reduces the employee-management conflict. It also leads to pooling & sharing of experience and mutual learning. Even information considered obsolete or rudimentary may turn out to be of importance and may result into organizational growth. The Linkages Team based structure, empowered employees and open information all coexist and they are linked with each other as essentials. The team structure will facilitate sharing of common resources and objectives. Overall performance of the team or group will depend upon total of performances of each individual as well as team will make a coordinated effort to attain its targets or to perform effectively and efficiently. No organization can empower its employees with out sharing information with them so to empower employees the organization has to share information with employees and this connects open information with empowered employees. Employees who have information and who also posses the power to act and decide will definitely try their level best to improve the performance of the organization also they will be open towards learning & information 84



sharing. Over and above these elements, the most important ingredient for a learning organization is Knowledge Management- being able to capitalize on the knowledge members of the organization. The knowledge or enriched experience that might not be written down or codified in formal documents. As employees do their jobs, they gain knowledge about the tasks they perform and learn the best ways to get certain things done and solve specific problems. Through knowledge management, this information can be shared and used by other employees working in the same organization. Certainly, the people performing a certain job are likely to learn the most about it. Knowledge management seeks to share this learning and knowledge throughout an organization.

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Middle-Down-Up Management An integrative architectural framework that unites the concepts of learning organization and knowledge management is presented for the readers to get a meaningful view. The model, depicted in Figure 3.1, is based on Senge’s five “disciplines” of learning organizations: 1. Systems Thinking. A conceptual framework, a body of knowledge and tools that has been developed over the past fifty years, to make the full patterns clearer, and to help us see how to change them effectively. 2. Personal Mastery. The discipline of continually clarifying and deepening our personal vision, of focusing our energies, of developing patience, and of seeing reality objectively. 3. Mental Models. Deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action. 4. Building Shared Vision. The practice of shared vision involves the skills of unearthing shared “pictures of the future” that foster genuine commitment and enrollment rather than compliance. 5. Team Learning. The discipline of team learning starts with “dialogue,” the capacity of members of a team to suspend assumptions and enter into a genuine “thinking together”.

Figure 3.1 Middle-Down-Up Management.

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Learning occurs at three levels: individual (personal mastery), group (team learning), and organizational (building shared vision). Mental models underlie all learning. They can either impede it by going unnoticed or accelerate it by being reflected, surfaced and examined. On the other, learning may change mental models. The fifth discipline, Systems Thinking, integrates the other four by enhancing each of them. Adapting the middle-up-down management process of Nonaka and Takeuchi, let us propose middle-down-up approach. In this framework, middle managers play an important role by working as a “bridge” between the broad visions of the top management and the concrete realities of business that front-line employees confront. They figure out the strategic intentions of the top management and translate them into a conceptual framework comprehensible to their subordinates. By signaling their own priorities, assumptions, and ways of thinking and acting, leaders manifest espoused values. These conscious and explicitly articulated values, however, are not necessarily internalized by the organization but remain to be questioned, debated, and challenged in dialogue, until the team has a shared perception of the success based on these values, and the value goes through a process of cognitive transformation into a belief and, ultimately, and assumption. In this leadership process, the images and maps of the conceptual framework are then incorporated into organizational theory-in-use, and explicit knowledge is internalized into tacit knowledge. When people share common mental models congruent with the shared vision, they can be empowered: they will know how to operate in various business settings as long as the overall business reality remains invariant. On the contrary, “to empower people in an unaligned organization can be counterproductive”. Shared vision emerges from the personal visions of individuals in the management process, in which the mental models are manifested on the surface of the organizational culture, and the tacit knowledge is externalized into explicit knowledge. Revisiting this model, Figure 3.2 depicts how the levels of enterprise architecture correspond to the model.

Figure 3.2 Organizational Learning and Enterprise Architecture 86



On the strategic level, business activity is monitored (BAM) through the management process, exposing organizational theory-in-use, or actual behavior, in the form of real-time management dashboards facilitating strategic decision-making. The shared vision of the organization is built as a steering process of external adaptation and internal integration. The output of this process is the new and revised models describing the business processes on the highest level. Simulation capabilities are also employed as the means of optimizing the processes.

NOTES

The tactical level is about coordination and associated with team learning. The strategic intent of the top management is translated to unique end-to-end core business processes. These processes can be configured by composing underlying contextindependent services and coordinating the interplay of executable processes. Choreography is the prevalent means to describe relatively static collaborative processes; new concepts are emerging to address more dynamic collaborations. This is where the team learning occurs: the coordination of the collaborative effort requires a significant amount of dialogue between the process participants. Team learning also has an effect on tacit knowledge within the organization through the leadership process. The operational level embraces the operational and information model of the organization in the form of services. The services are context-independent, idempotent faculties optimized to perform their predefined function. Typically, orchestration describes the sequence and conditions in which the service accesses underlying resources, binding them to its execution context. Thus this level corresponds to personal mastery: the purpose of orchestration is to optimize resource utilization and streamline service efficiency against some performance measure defined by the management process. The model reflects the reality as perceived by the organization. It is the vast repository of “sources of truth” dispersed in enterprise information systems and databases, the knowledge of the organization. Thereby, it can be equated to mental models in the MiddleDown-Up model. 3.6 CAPTURING AND CODIFICATION OF KNOWLEDGE Knowledge capture is a process by which the expert’s thoughts and experiences are captured. In a broader view, knowledge capture may also include capturing knowledge from other sources such as books, technical manuscripts, and drawings. Knowledge has to be captured and codified in such a way that it can become a part of the existing knowledge base of the organization. Knowledge capture is a demanding mental process in which a knowledge developer collaborates with the expert to convert expertise into a coded program. Three important steps are involved: 1. Using an appropriate tool to elicit information from the expert 2. Interpreting the information and inferring the expert’s underlying knowledge and reasoning process 87


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3. Using the interpretation to build the rules that represent the expert’s thought processes or solutions.

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We need to capture both types of knowledge – explicit and tacit. Tacit knowledge management is the process of capturing the experience and expertise of the individual in an organization and making it available to anyone who needs it. The capture of explicit knowledge is the systematic approach of capturing, organizing, and refining information in a way that makes information easy to find, and facilitates learning and problem solving. The approach used to capture, describe, and subsequently code knowledge depends on the type of knowledge: explicit knowledge is already well described, but we may need to abstract and summarize this content. Tacit knowledge, on the other hand, may require much more significant up-front analysis and organization before it can be suitably described and represented. A wide variety of techniques may be used to capture and codify knowledge which is described here. 3.6.1 Capturing tacit knowledge Tacit knowledge capture requires free access to a cooperative and articulate expert. In most cases, the knowledge developer does not have the luxury of deciding on the expert. However, the developer must be able to identify real expertise and how well a particular expert’s know-how suits the project. (a) Expert Evaluation There are several indicators of expertise: •

Indicators of expertise o The expert commands genuine respect. o The expert is found to be consulted by people in the organization, when some problem arises. o The expert possesses self confidence and he/she has a realistic view of the limitations. o The expert avoids irrelevant information, uses facts and figures. o The expert is able to explain properly and he/she can customize his/her presentation according to the level of the audience. o The expert exhibits his/her depth of the detailed knowledge and his/her quality of explanation is exceptional. o The expert is not arrogant regarding his/her personal information.

•

Experts qualifications o The expert should know when to follow hunches, and when to make exceptions. o The expert should be able to see the big picture. o The expert should posse’s good communication skills. 88



o The expert should be able to tolerate stress.

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o The expert should be able to think creatively. o The expert should be able to exhibit self-confidence in his/her thought and actions. o The expert should maintain credibility. o The expert should operate within a schema-driven/structured orientation. o The expert should use chunked knowledge. o The expert should be able to generate enthusiasm as well as motivation. o The expert should share his/her expertise willingly and without hesitation. o The expert should emulate an ideal teacher’s habits. Experts levels of expertise Highly expert persons. Moderately expert problem solvers. New experts. Capturing single versus multiple experts’ tacit knowledge: To ensure the reliability and quality of the KM system, a prime consideration is whether to tap one expert or a panel of experts and this decision is based on several factor such as the complexity of the problem, the criticality of the project to the organization, the types of expert available, and the funds allocated for building the KM system. Each alternative has advantages and limitations. Advantages of working with a single expert: • Ideal for building a simple KM system with only few rules. • Ideal when the problem lies within a restricted domain. • The single expert can facilitate the logistics aspects of coordination arrangements for knowledge capture. • Problem related/personal conflicts are easier to resolve. • The single expert tends to share more confidentiality. Disadvantages of working with a single expert: • • • •

Often, the experts’ knowledge is found to be not easy to capture. The single expert usually provides a single line of reasoning. They are more likely to change meeting schedules. The knowledge is often found to be dispersed.

Advantages of working with multiple (team) experts: • Complex problem domains are usually benefited. 89


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• Stimulates interaction. • Listening to a multitude of views allows the developer to consider alternative ways of representing knowledge. • Formal meetings are sometimes better environment for generating thoughtful contributions. Disadvantages of working with multiple (team) experts: • • • • •

Disagreements can frequently occur. Coordinating meeting schedules are more complicated. Harder to retain confidentiality. Overlapping mental processes of multiple experts can result in a process loss. Often requires more than one knowledge developer.

(b) Developing Relationship with Experts Creating the right impression: The knowledge developer must learn to use psychology, common sense, and technical as well as marketing skills to attract the experts respect and attention. Understanding of the expert’s style of expression: Experts are usually found to use one of the following styles of expression: Procedure type:

These types of experts are found to be logical, verbal and always procedural.

Storyteller type:

These types of experts are found to be focused on the content of the domain at the expense of the solution.

Godfather type:

These types of experts are found to be compulsive to take over.

Salesperson type:

These types of experts are found to spend most of the time dancing around the topic, explaining why his/her solution is the best.

Preparation for the session: •

Before making the first appointment, the knowledge developer must acquire some knowledge about the problem and the expert.

•

Initial sessions can be most challenging/critical.

•

The knowledge developer must build the trust.

•

The knowledge developer must be familiar with project terminology d he/she must review the existing documents.

•

The knowledge developer should be able to make a quick rapport with the expert.

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Deciding the location for the session:

NOTES

•

Protocol calls for the expert to decide the location.

•

The expert is usually more comfortable in having his/her necessary tools and information available close to him/her.

•

The meeting place should be quiet and free of interruptions.

Approaching multiple experts: •

Individual approach: The knowledge developer holds sessions with one expert at a time.

•

Approach using primary and secondary experts: o

The knowledge developer hold sessions with the senior expert early in the knowledge capture program for the clarification of the plan.

o

For a detailed probing, he/she may ask for other experts’ knowledge.

• Small groups approach: o

Experts gather together in one place, discuss the problem domain, and usually provide a pool of information.

o

Experts’ responses are monitored, and the functionality of each expert is tested against the expertise of the others.

o

This approach requires experience in assessing tapped knowledge, as well as cognition skills.

o

The knowledge developer must deal with the issue of power and its effect on expert’s opinion.

(c) Fuzzy Reasoning & Quality of Knowledge Capture •

Sometimes, the information gathered from the experts via interviewing is not precise and it involves fuzziness and uncertainty.

•

The fuzziness may increase the difficulty of translating the expert’s notions into applicable rules.

Analogies/Uncertainties: •

In the course of explaining events, experts can use analogies (comparing a problem with a similar problem which has been encountered in possibly different settings, months or years ago).

•

An expert’s knowledge or expertise represents the ability to gather uncertain information as input and to use a plausible line of reasoning to clarify the fuzzy details.

•

Belief, an aspect of uncertainty, tends to describe the level of credibility.

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•

People may use different kinds of words in order to express belief.

•

These words are often paired with qualifiers such as highly, extremely.

Understanding experience: •

Knowledge developers can benefit from their understanding/knowledge of cognitive psychology.

•

When a question is asked, then an expert operates on certain stored information through deductive, inductive, or other kinds of problem-solving methods.

•

The resulting answer is often found to be the culmination of the processing of stored information.

•

The right question usually evokes the memory of experiences that produced good and appropriate solutions in the past.

Sometimes, how quickly an expert responds to a question depends on the clarity of content, whether the content has been recently used, and how well the expert has understood the question. Problem with the language: How well the expert can represent internal processes can vary with their command of the language they are using and the knowledge developer’s interviewing skills. The language may be unclear in the following number of ways: • • • •

Comparative words (e.g., better, faster) are sometimes left hanging. Specific words or components may be left out of an explanation. Absolute words and phrases may be used loosely. Some words always seem to have a built-in ambiguity.

(d) Interviewing as a Tacit Knowledge Capture Tool Advantages of using interviewing as a tacit knowledge capture tool: • • • •

It is a flexible tool. It is excellent for evaluating the validity of information. It is very effective in case of eliciting information regarding complex matters. Often people enjoy being interviewed.

Interviews can range from the highly unstructured type to highly structured type. • The unstructured types are difficult to conduct, and they are used in the case when the knowledge developer really needs to explore an issue. • The structured types are found to be goal-oriented, and they are used in the case when the knowledge developer needs specific information.

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• Structured questions can be of the following types:

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o Multiple-choice questions. o Dichotomous questions. o Ranking scale questions. • In semi structured types, the knowledge developer asks predefined questions, but he/she allows the expert some freedom in expressing his/her answer. Guidelines for successful interviewing: • • • •

Setting the stage and establishing rapport. Phrasing questions. Listening closely/avoiding arguments. Evaluating the session outcomes.

Reliability of the information gathered from experts: Some uncontrolled sources of error that can reduce the information’s reliability: • • • • •

Expert’s perceptual slant. The failure in expert’s part to exactly remember what has happened. Fear of unknown in the part of expert. Problems with communication. Role bias.

o Errors in part of the knowledge developer: validity problems are often caused by the interviewer effect (something about the knowledge developer colours the response of the expert). Some of the effects can be as follows • Gender effect • Age effect • Race effect o

Problems encountered during interviewing • Response bias. • Inconsistency. • Problem with communication. • Hostile attitude. • Standardizing the questions. • Setting the length of the interview.

o

Process of ending the interview: • The end of the session should be carefully planned. • One procedure calls for the knowledge developer to halt the questioning a few minutes before the scheduled ending time, and to summarize the key points of the session. 93


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• This allows the expert to comment a schedule a future session.

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• Many verbal/nonverbal cues can be used for ending the interview. o

Issues: Many issues may arise during the interview, and to be prepared for the most important ones, the knowledge developer can consider the following questions: • How would it be possible to elicit knowledge from the experts who can not say what they mean or can not mean what they say? • How to set up the problem domain. • How to deal with uncertain reasoning processes. • How to deal with the situation of difficult relationships with expert(s). • How to deal with the situation when the expert does not like the knowledge developer for some reason.

(e) Rapid Prototyping in interviews: • Rapid prototyping is an approach to building KM systems, in which knowledge is added with each knowledge capture session. • This is an iterative approach which allows the expert to verify the rules as they are built during the session. • This approach can open up communication through its demonstration of the KM system. • Due to the process of instant feedback and modification, it reduces the risk of failure. • It allows the knowledge developer to learn each time a change is incorporated in the prototype. • This approach is highly interactive. • The prototype can create user expectations which in turn can become obstacles to further development effort. 3.6.2 Other knowledge capture techniques Like any other professional, the knowledge developer must be well versed in the use of specialized knowledge capture tools. Each tool has a unique purpose, depending on whether the capture process revolves around a single expert or multiple experts. Let us examine other tools used in knowledge capture. (a) On-Site Observation (Action Protocol) •

It is a process which involves observing, recording, and interpreting the expert’s problem-solving process while it takes place.

•

The knowledge developer does more listening than talking; avoids giving advice and usually does not pass his/her own judgment on what is being observed, even

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if it seems incorrect; and most of all, does not argue with the expert while the expert is performing the task. •

Compared to the process of interviewing, on-site observation brings the knowledge developer closer to the actual steps, techniques, and procedures used by the expert.

•

One disadvantage is that sometimes some experts to not like the idea of being observed.

•

The reaction of other people (in the observation setting) can also be a problem causing distraction.

•

Another disadvantage is the accuracy/completeness of the captured knowledge.

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(b) Brainstorming •

It is an unstructured approach towards generating ideas about creative solution of a problem which involves multiple experts in a session.

•

In this case, questions can be raised for clarification, but no evaluations are done at the spot.

•

Similarities (that emerge through opinions) are usually grouped together logically and evaluated by asking some questions like: o What benefits are to be gained if a particular idea is followed? o What specific problems that idea can possibly solve. o What new problems can arise through this?

The general procedure for conducting a brainstorming session: o o o o

Introducing the session. Presenting the problem to the experts. Prompting the experts to generate ideas. Looking for signs of possible convergence.

• If the experts are unable to agree on a specific solution, they knowledge developer may call for a vote/consensus. Electronic Brainstorming •

Is a computer-aided approach for dealing with multiple experts?

•

It usually begins with a pre-session plan which identifies objectives and structures the agenda, which is then presented to the experts for approval.

•

During the session, each expert sits on a PC and gets themselves engaged in a predefined approach towards resolving an issue, and then generates ideas.

•

This allows experts to present their opinions through their PC’s without having to wait for their turn.

•

Usually the comments/suggestions are displayed electronically on a large screen without identifying the source. 95


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•

This approach protects the introvert experts and prevents tagging comments to individuals.

•

The benefit includes improved communication, effective discussion regarding sensitive issues, and closes the meeting with concise recommendations for necessary action.

•

This eventually leads to convergence of ideas and helps to set final specifications.

•

The result is usually the joint ownership of the solution.

Figure 3.3 The process of brainstorming (c) Protocol Analysis (Think-Aloud Method) •

In this case, protocols (scenarios) are collected by asking experts to solve the specific problem and verbalize their decision process by stating directly what they think.

•

Knowledge developers do not interrupt in the interim.

•

The elicited information is structured later when the knowledge developer analyzes the protocol.

•

Here the term scenario refers to a detailed and somehow complex sequence of events or more precisely, an episode.

•

A scenario can involve individuals and objects.

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•

A scenario provides a concrete vision of how some specific human activity can be supported by information technology.

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(d) Consensus Decision Making •

Consensus decision making usually follows brainstorming.

•

It is effective if and only if each expert has been provided with equal and adequate opportunity to present their views.

•

In order to arrive at a consensus, the knowledge developer conducting the exercise tries to rally the experts towards one or two alternatives.

•

The knowledge developer follows a procedure designed to ensure fairness and standardization.

•

This method is democratic in nature.

•

This method can be sometimes tedious and can take hours.

(e) Repertory Grid •

This is a tool used for knowledge capture.

•

The domain expert classifies and categorizes a problem domain using his/her own model.

•

The grid is used for capturing and evaluating the expert’s model.

•

Two experts (in the same problem domain) may produce distinct sets of personal and subjective results.

•

The grid is a scale (or a bipolar construct) on which elements can be placed within gradations.

•

The knowledge developer usually elicits the constructs and then asks the domain expert to provide a set of examples called elements.

•

Each element is rated according to the constructs which have been provided.

(f) Nominal Group Technique (NGT) •

This provides an interface between consensus and brainstorming.

•

Here the panel of experts becomes a Nominal Group whose meetings are structured in order to effectively pool individual judgment.

•

Idea writing is a structured group approach used for developing ideas as well as exploring their meaning and the net result is usually a written report.

•

NGT is an idea writing technique.

(g) Delphi Method • It is a survey of experts where a series of questionnaires are used to pool the experts’ responses for solving a specific problem. 97


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• Each expert’s contributions are shared with the rest of the experts by using the results from each questionnaire to construct the next questionnaire.

NOTES

Concept Mapping •

It is a network of concepts consisting of nodes and links.

•

A node represents a concept, and a link represents the relationship between concepts.

•

Concept mapping is designed to transform new concepts/propositions into the existing cognitive structures related to knowledge capture.

•

It is a structured conceptualization.

•

It is an effective way for a group to function without losing their individuality.

•

Concept mapping can be done for several reasons: o To design complex structures. o To generate ideas. o To communicate ideas. o To diagnose misunderstanding. • Six-step procedure for using a concept map as a tool: o Preparation. o Idea generation. o Statement structuring. o Representation. o Interpretation o Utilization. • Similar to concept mapping, a semantic net is a collection of nodes linked together to form a net. o A knowledge developer can graphically represent descriptive/declarative knowledge through a net. o Each idea of interest is usually represented by a node linked by lines (called arcs) which shows relationships between nodes. o Fundamentally it is a network of concepts and relationships.

(i) Blackboarding •

In this case, the experts work together to solve a specific problem using the blackboard as their workspace.

•

Each expert gets equal opportunity to contribute to the solution via the blackboard.

•

It is assumed that all participants are experts, but they might have acquired their individual expertise in situations different from those of the other experts in the group.

•

The process of blackboarding continues till the solution has been reached. 98



•

Characteristics of blackboard system:

NOTES

1. Diverse approaches to problem-solving. 2. Common language for interaction. 3. Efficient storage of information 4. Flexible representation of information. 5. Iterative approach to problem-solving. 6. Organized participation. 7. Components of blackboard system: 8. The Knowledge Source (KS): Each KS is an independent expert observing the status of the blackboard and trying to contribute a higher level partial solution based on the knowledge it has and how well such knowledge applies to the current blackboard state. 9. The Blackboard : It is a global memory structure, a database, or a repository that can store all partial solutions and other necessary data that are presently in various stages of completion. 10. A Control Mechanism: It coordinates the pattern and flow of the problem solution. 11. The inference engine and the knowledge base are part of the blackboard system. 3.7 KNOWLEDGE CODIFICATION After knowledge is captured, it is organized and codified in a manner amenable for transfer and effective use. Knowledge codification is organizing and representing knowledge before it is accessed by authorized personnel. The organizing part is usually in the form of a decision tree, a decision table, a frame, etc; Codification must be in a form and a structure that will build the knowledge base which must make it accessible, explicit, and easy to access. From a knowledge management perspective, codification means converting tacit knowledge to explicit knowledge in a usable form for the organizational members. From an information system view, codification is converting undocumented to documented information. Regardless of view, codification is making corporate-specific knowledge (tacit and explicit) visible, accessible, and usable for value-added decision making. The knowledge developer should note the following points before initiating knowledge codification: 12. Recorded knowledge is often difficult to access (because it is either fragmented or poorly organized). 13. Diffusion of new knowledge is too slow. 14. Knowledge is nor shared, but hoarded (this can involve political implications). 15. Often knowledge is not found in the proper form. 16. Often knowledge is not available at the correct time when it is needed.

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17. Often knowledge is not present in the proper location where it should be present. 18. Often the knowledge is found to be incomplete. 3.7.1 Codifying Knowledge • An organization must focus on the following before codification: o What organizational goals will the codified knowledge serve? o What knowledge exists in the organization that can address these goals? o How useful is the existing knowledge for codification? o How would someone codify knowledge? • Codifying tacit knowledge (in its entirety) in a knowledge base or repository is often difficult because it is usually developed and internalized in the minds of the human 3.7.2 Codification Tools and Procedures (a) Knowledge Maps •

Knowledge maps originated from the belief that people act on things that they understand and accept.

•

It indicates that self-determined change is sustainable.

•

Knowledge map is a visual representation of knowledge.

•

They can represent explicit/tacit, formal/informal, documented / undocumented, internal / external knowledge.

•

It is not a knowledge repository.

•

It is a sort of directory that points towards people, documents, and repositories.

•

It may identify strengths to exploit and missing knowledge gaps to fill.

•

Knowledge Mapping is very useful when it is required to visualize and explore complex systems.

•

Examples of complex systems are ecosystems, the internet, telecommunications systems, and customer-supplier chains in the stock market.

•

Knowledge Mapping is a multi-step process.

•

Key can be extracted from database or literature and placed in tabular form as lists of facts.

•

These tabled relationships can then be connected in networks to form the required knowledge maps.

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Figure 3.4 Knowledge Map A popular knowledge map used in human resources is a skills planner in which employees are matched to jobs. Steps to build the map:

(b

•

A structure of the knowledge requirements should be developed.

•

Knowledge required of specific jobs must be defined.

•

You should rate employee performance by knowledge competency.

•

You should link the knowledge map to some training program for career development and job advancement

Decision Table • •

It is another technique used for knowledge codification. It consists of some conditions, rules, and actions.

A phonecard company sends out monthly invoices to permanent customers and gives them discount if payments are made within two weeks. Their discounting policy is as follows: ‘If the amount of the order of phonecards is greater than Rs.35, subtract 5% of the order; if the amount is greater than or equal to Rs.20 and less than or equal to Rs.35, subtract a 4% discount; if the amount is less than Rs.20, do not apply any discount.” 101


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We shall develop a decision table for their discounting decisions, where the condition alternatives are ‘Yes’ and ‘No’. CONDITIONS AND ACTIONS

Paid within 2 weeks Order > Rs.35 Rs.20<= Order <= Rs.35 Order < Rs.20 5% discount 4% discount No discount

RULES

RULES

RULES RULES

1

2

3

4

Y Y N N X

Y N Y N

Y N N Y

N -

X

X

X

Figure 3.5 Decision Table (c) Decision Tree • It is also a knowledge codification technique. • A decision tree is usually a hierarchically arranged semantic network. A decision tree for the phonecard company discounting policy (as discussed above) is shown next.

Figure 3.6 Decision Tree

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(d) Frames •

A frame is a codification scheme used for organizing knowledge through previous experience.

•

It deals with a combination of declarative and operational knowledge.

•

Key elements of frames:

NOTES

o Slot: A specific object being described/an attribute of an entity. o Facet: The value of an object/slot. (e) Production Rules •

They are conditional statements specifying an action to be taken in case a certain condition is true.

•

They codify knowledge in the form of premise-action pairs.

•

Syntax: IF (premise) THEN (action)

•

Example: IF income is ‘standard’ and payment history is ‘good’, THEN ‘approve home loan’.

•

In case of knowledge-based systems, rules are based on heuristics or experimental reasoning.

•

Rules can incorporate certain levels of uncertainty.

•

A certainty factor is synonymous with a confidence level, which is a subjective quantification of an expert’s judgment.

•

The premise is a Boolean expression that should evaluate to be true for the rule to be applied.

•

The action part of the rule is separated from the premise by the keyword THEN.

•

The action clause consists of a statement or a series of statements separated by AND’s or comma’s and is executed if the premise is true.

•

In case of knowledge-based systems, planning involves:

•

Breaking the entire system into manageable modules.

•

Considering partial solutions and liking them through rules and procedures to arrive at a final solution.

•

Deciding on the programming language(s).

•

Deciding on the software package(s).

•

Testing and validating the system.

•

Developing the user interface.

•

Promoting clarity, flexibility; making rules clear.

•

Reducing unnecessary risk.

•

Role of inferencing:

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•

Inferencing implies the process of deriving a conclusion based on statements that only imply that conclusion.

•

An inference engine is a program that manages the inferencing strategies.

•

Reasoning is the process of applying knowledge to arrive at the conclusion. o Reasoning depends on premise as well as on general knowledge. o People usually draw informative conclusions.

(f

Case-Based Reasoning •

It is reasoning from relevant past cases in a way similar to human’s use of past experiences to arrive at conclusions.

•

Case-based reasoning is a technique that records and documents cases and then searches the appropriate cases to determine their usefulness in solving new cases presented to the expert.

•

The aim is to bring up the most similar historical case that matches the present case.

•

Adding new cases and reclassifying the case library usually expands knowledge.

•

A case library may require considerable database storage as well as an efficient retrieval system.

(g) Knowledge-Based Agents •

An intelligent agent is a program code which is capable of performing autonomous action in a timely fashion.

•

They can exhibit goal directed behaviour by taking initiative.

•

they can be programmed to interact with other agents or humans by using some agent communication language.

•

In terms of knowledge-based systems, an agent can be programmed to learn from the user behaviour and deduce future behaviour for assisting the user.

3.8 KNOWLEDGE MANAGEMENT INFRASTRUCTURE OR ARCHITECTURE Knowledge management infrastructure is a prerequisite to knowledge sharing which is viewed as a combination of people, technology and content. KM infrastructure is complete with a dedicated team, a fully functional technical infrastructure and, most importantly, increasing awareness of the criticality of knowledge sharing amongst all employees. These components are inseparable and interdependent as shown in Figure 3.7. People with knowledge provide content, relying on technology to transfer and share knowledge. This combination provides the efficiency and performance to managing the knowledge core of the organization.

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NOTES PEOPLE

TECHNOLOGY

CONTENT

Figure 3.7 Knowledge Management, a conceptual view The People Core •

By people, here we mean knowledge workers, managers, customers, and suppliers.

•

As the first step in knowledge architecture, our goal is to evaluate the existing information/ documents which are used by people, the applications needed by them, the people they usually contact for solutions, the associates they collaborate with, the official emails they send/receive, and the database(s) they usually access.

•

All the above stated resources help to create an employee profile, which can later be used as the basis for designing a knowledge management system.

•

The idea behind assessing the people core is to do a proper job in case of assigning job content to the right person and to make sure that the flow of information that once was obstructed by departments now flows to right people at right time.

•

In order to expedite knowledge sharing, a knowledge network has to be designed in such a way as to assign people authority and responsibility for specific kinds of knowledge content, which means:

Identifying knowledge centers After determining the knowledge that people need, the next step is to find out where the required knowledge resides, and the way to capture it successfully. Here, the term knowledge center means areas in the organization where knowledge is available for capturing. These centers supports to identify expert(s) or expert teams in each center who can collaborate in the necessary knowledge capture process. Activating knowledge content satellites This step breaks down each knowledge center into some more manageable levels, satellites, or areas. 105


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Assigning experts for each knowledge center o After the final framework has been decided, one manager should be assigned for each knowledge satellite that will ensure integrity of information content, access, and update. o Ownership is a crucial factor in case of knowledge capture, knowledge transfer, and knowledge implementation. o In a typical organization, departments usually tend to be territorial. o Often, fight can occur over the budget or over the control of sensitive processes (this includes the kind of knowledge a department owns). o These reasons justify the process of assigning department ownership to knowledge content and knowledge process. o Adjacent / interdependent departments should be cooperative and ready to share knowledge. The Technical Core •

The objective of the technical core is to enhance communication as well as ensure effective knowledge sharing.

•

Technology provides a lot of opportunities for managing tacit knowledge in the area of communication.

•

Communication networks create links between necessary databases.

•

Here the term technical core is meant to refer to the totality of the required hardware, software, and the specialized human resources.

•

Expected attributes of technology under the technical core: Accuracy, speed, reliability, security, and integrity.

•

Since an organization can be thought of as a knowledge network, the goal of knowledge economy is to push employees towards greater efficiency/ productivity by making best possible use of the knowledge they posses.

•

A knowledge core usually becomes a network of technologies designed to work on top of the organization’s existing network.

User Interface Layer •

Usually a web browser represents the interface between the user and the KM system.

•

It is the top layer in the KM system architecture.

•

The way the text, graphics, tables etc are displayed on the screen tends to simplify the technology for the user.

•

The user interface layer should provide a way for the proper flow of tacit and explicit knowledge.

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•

The necessary knowledge transfer between people and technology involves capturing tacit knowledge from experts, storing it in knowledge base, and making it available to people for solving complex problems.

•

Features to be considered in case of user interface design:

NOTES

o Consistency o Relevancy o Visual clarity o Usability o Ease of Navigation

Figure 3.8 The Transfer of Knowledge Authorized Access Layer •

This layer maintains security as well as ensures authorized access to the knowledge captured and stored in the organization’s repositories.

•

The knowledge is usually captured by using internet, intranet of extranet.

•

An organization’s intranet represents the internal network of communication systems.

•

Extranet is a type of intranet with extensions allowing specified people (customers, suppliers, etc.) to access some organizational information.

•

Issues related to the access layer: access privileges, backups.

•

The access layer is mostly focused on security, use of protocols (like passwords), and software tools like firewalls.

•

Firewalls can protect against: o E-mails that can cause problems. o Unauthorized access from the outside world. o Undesirable material (movies, images, music etc). o Unauthorized sensitive information leaving the organization. 107


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•

Firewalls can not protect against: o Attacks not going through the firewall. o Viruses on floppy disks. o Weak security policies.

Collaborative Intelligence and Filtering Layer •

This layer provides customized views based on stored knowledge.

•

Authorized users can find information (through a search mechanism) tailored to their needs.

•

Intelligent agents (active objects which can perceive, reason, and act in a situation to help problem solving) are found to be extremely useful in some situations.

•

In case of client/server computing, there happens to be frequent and direct interaction between the client and the server.

•

In case of mobile agent computing, the interaction happens between the agent and the server.

•

A mobile agent roams around the internet across multiple servers looking for the correct information. Some benefits can be found in the areas of: o Fault tolerance. o Reduced overall network load. o Heterogeneous operation.

•

Key components of this layer: o The registration directory that develops tailored information based on user profile. o Membership in specific services, such as sales promotion, news service etc. o The search facility such as a search engine.

•

In terms of the prerequisites for this layer, the following criteria can be considered: o Security. o Portability. o Flexibility o Scalability o Ease of use. o Integration.

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Knowledge-Enabling Application Layer (Value-Added Layer) •

This creates a competitive edge.

•

Most of the applications help users to do their jobs in better ways.

•

They include knowledge bases, discussion databases, decision support etc.

NOTES

Transport Layer •

This is the most technical layer.

•

It ensures to make the organization a network of relationships where electronic transfer of knowledge can be considered as routine.

•

This layer associates with LAN (Local Area Network), WAN (Wide Area Network), intranets, extranets, and internet.

•

In this layer we consider multimedia, URL’s, connectivity speeds/bandwidths, search tools, and consider managing of network traffic.

Middleware Layer • • •

This layer makes it possible to connect between old and new data formats. It contains a range of programs to do this job.

Repositories Layer •

It is the bottom layer of the KM architecture which represents the physical layer in which repositories are installed.

•

These may include legacy applications, intelligent data warehouses, operational databases etc. o After establishing the repositories, they are linked to form an integrated repository. o An integrated repository brings together all the knowledge available from the repositories. o The main advantage of an integrated knowledge repository is that the user does not care in which repository the knowledge resides. A conceptual model for an enterprise-wide integrated knowledge management system is shown in Figure 3.9.

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Figure 3.9 Integrated Knowledge Management System 3.9 REPOSITORIES A Knowledge Repository is a computerized system that systematically and continuously captures, organizes, categorizes and analyses an organization’s knowledge assets. The repository can be searched and data can be quickly retrieved. It is a collaborative system where people can query and browse both structured and unstructured information in order to retrieve and preserve organizational knowledge assets and facilitate collaborative working. The focus of such systems tends to be on storing unstructured, but nonetheless still explicit, forms of knowledge such as unwritten local rules and procedures. The aim is to be able to retrieve data in a context sensitive way rather than just through the use of simple keyword-based retrieval. The way core knowledge is shared with other members of the knowledge community is an important issue for organizations. The knowledge repositories act as the link between users and core knowledge, operating as a single point of entry to help people to find relevant information from many different organizational sources. A repository’s broad functions are to codify explicit knowledge in a logical manner and to direct the user to enabling sources (including people, organizational units or groups, web sites, policies and other avenues) which may guide and inform the knowledge seeker. The repository also acts as the vehicle for contributing new knowledge, and for requesting personalized services which keep the user updated on repository additions. In effect, a highly effective knowledge repository should serve as a single point of contact for all knowledge needs.

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3.9.1 Content of knowledge repository

NOTES

That there are four layers of organizational knowledge which needs to be shared through repository: 1. factual (terminology, specific details and elements); 2. conceptual (theories, models, principles and generalizations); 3. procedural (skills, algorithms, techniques and methods) and 4. meta-cognitive (knowledge about knowledge, i.e. learning, thinking, problem solving). These forms of knowledge can be presented in a number of ways to facilitate effective access with different needs. For example, users might seek guidance on the following: •

content, such as topics, projects or reports:

•

methodologies, such as research approaches, templates and data presentation

•

longitudinal developments to build an historical perspective.

They will have many different needs to be supported through the repository. A major challenge is the anticipation of those needs so that a successful outcome is generally possible. Each repository will be presented in a different way and with different content and features, as it supports a specific knowledge community. The users’ expectations and priorities, knowledge activities and core business priorities should all be reflected in the features of the repository. 3.9.2 Features of knowledge repository Knowledge repositories offer a range of options for users to explore, with the main menu offering access to identified knowledge sources in the organization and beyond. The repository may include the following: • • • • • • • • • • • • •

links to organizational and external sources search services to help users find required objects or sources reference materials and services discussion topics frequently asked questions (FAQs) case studies real-life examples a site where solution may be shared a help services to support users who are unfamiliar with the system a contribution channel to allow easy linkage of new materials a direct link to keywords which may help find sources an explanation of system scope and usage information on the main knowledge support officers 111


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A repository is unlikely to include all these features. Its design needs to reflect user needs and the knowledge that is most important to core business. An effective repository ensures users can draw from an appropriate array of options which support their most important knowledge activities. It cannot be all things to all workers. The selectivity of the content management system is its strength. Repositories need to be carefully developed to provide this selective but detailed guidance on what is known in the organization, and by whom. 3.9.3 The design of a knowledge repository The design of a knowledge repository reflects the two basic components of knowledge as an object: structure and content. Knowledge structures provide the context for interpreting accumulated content. If the repository is conceived as a “knowledge platform”, then many different views of the content may be derived from a particular repository structure. A high degree of viewing flexibility enables users to alter and combine views dynamically and interactively and to more easily apply the knowledge to new contexts and circumstances. At this point, knowledge-as-object becomes knowledge-as-process. The basic structural element is the knowledge unit, a formally defined, atomic packet of knowledge content that can be labeled, indexed, stored, retrieved and manipulated. The format, size and content of knowledge units may vary depending on the type of explicit knowledge being stored and the context of their use. The repository structure also includes the schemes for linking and cross-referencing knowledge units. These links may represent conceptual associations, ordered sequences, causality or other relationships depending on the type of knowledge being stored. To reflect the full range of explicit organizational knowledge, repositories should strive to record significant and meaningful concepts, categories, and definitions, (declarative knowledge), processes, actions and sequences of events (procedural knowledge), rationale for actions or conclusions (causal knowledge), circumstances and intentions under which the knowledge was developed and is to be applied (specific contextual knowledge), and the linkages among them. The repository should be indexed according to those concepts and categories, providing access paths that are meaningful to the organization. It should accommodate changes or additions to that knowledge (e.g., by linking annotations) as subsequent authors and creators adapt the knowledge for use in additional contexts. A knowledge platform may actually consist of several repositories, each with a structure appropriate to a particular type of knowledge or content. These repositories may be logically linked to form a composite or “virtual” repository, the content of each providing context for interpreting the content of the others. (Refer Figure 1.1) For example, product literature, best sales practices, and competitor intelligence for a particular market might be stored separately but viewed as though contained in one repository.

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NOTES

Figure 1.10 Composite Designs 3.9.4 The Knowledge Refinery The refinery represents the process for creating and distributing the knowledge contained in the repository. This process includes five stages: •

Acquisition. Information and knowledge is either created within the organization or can be acquired from many different internal and external sources.

•

Refining. Captured knowledge, before being added to the repository, is subjected to value-adding processes (refining) such as cleansing, labeling, indexing, sorting, abstracting, standardizing, integrating, and re-categorizing.

•

Storage and Retrieval. This stage bridges upstream repository creation to downstream knowledge distribution.

•

Distribution. This stage represents the mechanisms used to make repository content accessible.

•

Presentation. The value of knowledge is pervasively influenced by the context of its use. Capabilities should be provided for flexibly arranging, selecting, and integrating the knowledge content.

3.9.5 Repository lifecycle Knowledge repositories have a lifecycle that must be managed. Once created, they tend to grow, reaching a point where they begin to collapse under their own weight, requiring major reorganization. Their rejuvenation requires deleting obsolete content, archiving less active but potentially useful content, and reorganizing what is left. Content or topic areas may become fragmented or redundant. Reorganizing requires eliminating those redundancies, 113


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combining similar contributions, generalizing content for easier reapplication, and restructuring categories as needed. Successful knowledge management organizations proactively manage and reorganize their repositories as an ongoing activity rather than waiting for decline to set in before acting. 3.9.6 Repository structure For knowledge repositories to be meaningful, their structure must reflect the structure of shared mental models or contextual knowledge tacitly held by the organization. In most organizations, those structures are neither well-defined nor widely shared. Yet their explication is essential for effectively managing explicitly encoded organizational knowledge. This requires defining what is meant by a knowledge-unit and how that collection of knowledge units should be meaningfully indexed and categorized for ease of access, retrieval, exchange and integration. Creating “semantic consensus” even within common practice communities is often a difficult task, let alone across an entire organization. Different lexicons naturally emerge from different parts of an organization. Standards are in many ways counter to the culture of many organizations. However, the ability to integrate and share knowledge depends on some broadly meaningful scheme for its structure. Integration of knowledge across different contexts opens an organization to new insights. A practice community’s exposure to how its knowledge can be applied in other contexts increases the scope and value of that knowledge. Often the variety of experiences within a local community of practice is not great enough to fully understand some phenomenon. By being able to combine experiences across communities, the variation of experience is enlarged, as is the ability to learn from those experiences. For example, an imaging firm had created a standard means to capture and share sales techniques among its market segments. By sharing knowledge of how customers in different market segments made use of a particular product, salespeople in each territory were exposed to patterns, insights and selling opportunities they might not have perceived on their own. 3.10 KNOWLEDGE MANAGEMENT APPLICATIONS Based on the knowledge management architecture, knowledge processing can be segmented into two broad classes: integrative and interactive (Refer Figure 1.11), each addressing different knowledge management objectives. Together, these approaches provide a broad set of knowledge processing capabilities. They support well-structured repositories for managing explicit knowledge while enabling interaction to integrate tacit knowledge.

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Figure 1.11 Segments of knowledge processing Integrative Applications Integrative applications exhibit a sequential flow of explicit knowledge into and out of the repository. Producers and consumers interact with the repository rather than with each other directly. The repository becomes the primary medium for knowledge exchange, providing a place for members of a knowledge community to contribute their knowledge and views. The primary focus tends to be on the repository and the explicit knowledge it contains, rather than on the contributors, users, or the tacit knowledge they may hold. Integrative applications vary in the extent to which knowledge producers and consumers come from the same knowledge community. At one extreme, lies electronic publishing, wherein the consumers (readers) neither directly engage in the same work nor belong to the same practice community as the producers (authors). Once published, the content tends to be stable, and those few updates that may be required are expected to originate with authors. The consumer accepts the content as it is, and active feedback or modification by the user is not anticipated (although provisions could be made for that to occur). For example, the organization may produce a periodic newsletter, or the human resources department may publish its policies or a directory of employee skills and experience.

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At the other extreme, the producers and consumers are members of the same practice community or organizational unit. While still exhibiting a sequential flow, the repository provides a means to integrate and build on their collective knowledge. We can label these as integrated knowledge-bases. A best-practices database is the most common application. Practices are collected, integrated and shared among people confronting similar problems. Regarding the organizational roles for managing integrative applications, acquisition requires knowledge creators, finders, and collectors. Capturing verbal knowledge requires interviewers and transcribers. Documenting observed experiences requires organizational reporters. Surfacing and interpreting deeply held cultural and social knowledge may require corporate anthropologists. Refining requires analysts, interpreters, abstractors, classifiers, editors, and integrators. A librarian or “knowledge curator” must manage the repository. Others must take responsibility for access, distribution and presentation. Finally, organizations may need people to train users to critically interpret, evaluate and adapt knowledge to new contexts. Interactive Applications Interactive applications are focused primarily on supporting interaction among people holding tacit knowledge. In contrast to integrative applications, the repository is a byproduct of interaction and collaboration rather than the primary focus of the application. Its content is dynamic and emergent. Interactive applications vary by the level of expertise between producers and consumers and the degree of structure imposed on their interaction. Where formal training or knowledge transfer is the objective, the interaction tends to be primarily between instructor and student, or expert and novice, and structured around a discrete problem, assignment or lesson plan. We can refer these applications as distributed learning. In contrast, interaction among those performing common practices or tasks tends to be more ad hoc or emergent. We may broadly refer to these applications as forums. They may take the form of a knowledge brokerage - an electronic discussion space where people may either search for knowledge (e.g., “Does anyone know…”) or advertise their expertise. The most interactive forums support ongoing, collaborative discussions. The producers and consumers comprise the same group of people, continually responding to and building on each individual’s additions to the discussion. The flow continually loops back from presentation to acquisition. With the appropriate structuring and indexing of the content, a knowledge repository can emerge. A standard categorization scheme for indexing contributions provides the ability to reapply that knowledge across the enterprise. Interactive applications play a major role in supporting integrative applications. For example, a forum can be linked to an electronic publishing application for editors to discuss 116



the quality of the contributions, or to offer a place for readers to react to and discuss the publication. Best practice databases typically require some degree of forum interaction, so that those attempting to adopt a practice have an opportunity to discuss its reapplication with its creators.

NOTES

Regarding the organizational roles for managing interactive applications, acquisition requires recruiters and facilitators to encourage and manage participation in interactive forums so that those with the appropriate expertise are contributing. The refining, structuring, and indexing of the content often is done by the communicators themselves, using guidelines and categories built into the application, supplemented by a conference moderator. Assuring the quality of the knowledge may require quality assurance personnel such as subject matter experts and reputation brokers. Managing a conference repository over its lifecycle usually falls to a conference moderator. Others may be required to work with users to help them become comfortable and skilled with accessing and using the application. Composite Applications Complex knowledge management problems typically require multiple repositories segmented by a degree of interactivity, volatility of content, or the structure of the knowledge itself. Each repository may have a different set of processes and roles by which its content is created, refined and stored. Long-cycle knowledge may have a more formal review and approved process, while best practices may receive a more expedited editing, and discussion databases for rapid exchange may have no review process other than after-the-fact monitoring by a forum moderator. Further, use of knowledge repositories typically causes knowledge creation and use to become separated in time and space. Therefore, the knowledge must be continually evaluated to ensure that it applies to present context and circumstances. Repositories and their underlying management processes may, therefore, need to be segmented based on the volatility of their context as well as content. For example, the storage structures and processes for managing product knowledge in rapidly changing markets may differ significantly from managing that knowledge in stable markets. Segmenting these repositories and identifying any significant differences in their refinery processes is crucial for successful application, as is their integration to provide seamless access to their knowledge. 3.11 COLLABORATIVE PLATFORMS Collaborative platform is a tool that supports team members or other tools that share information and contribute to knowledge management system. The collaborative platform, along with the communications network services and hardware, provides the pipeline to enable the flow of explicated knowledge, its context, and the medium for conversations. Besides this, the collaborative platform provides a surrogate channel for defining, storing, moving, and linking digital objects, such as conversation threads that correspond to knowledge units. The collaboration platform enables the content of the KM system with a 117


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high degree of flexibility so that it is rendered meaningful, useful, and applicable across the many possible contexts of use. More importantly, the collaborative platform empowers the users. The user can either search for content - the pull approach to content delivery – or subscribe to content, that is, have content pushed to him or her. 3.11.1 Different features of platforms (a) Collaborative filtering Collaborative filtering or deduction, gathers knowledge on general user traits, and models this into a profile. A profile is compared to other profiles by detecting similarities and opposites. It then makes predictions upon these comparisons. Sharing of knowledge through peer recommendations is widely used mechanism distributing information. Collaborative filtering can be built into a KM system by deploying one of two possible mechanisms: 1. Active filtering: Users manually define filters and pointers to interesting content and share across their work group. 2. Automated filtering: Statistical algorithms make recommendations based on correlations between the user’s personal preferences and content ratings. Content ratings can be generated either automatically (such as those produced by measuring the average time all readers spent on reading the item) or by manually assigning an average rating (aggregated across multiple readers). (b

Community-centered collaborative filtering

Automated collaborative filtering might seem to be reasonable approach, but it will not provide the expected benefits or gain a sufficiently high level of commitment from its users if it ignores the community that it is built for. Separation of automated filtering from personal relationships limits its usefulness to a greater degree than one might expect. The network of existing social relationship between employees can be a valuable basis for improving the collaborative filtering process. Although anonymity of contributors is essential, anonymous reviews tend to carry less weight than do signed ones. This is especially true in collaborative communities where people know colleagues by name and reputation. Reputation, trust, and reciprocity come into the picture of collaborative process enhancers when contributions are signed. (c) Meta knowledge Meta knowledge implies knowing what you know and it is knowledge about knowledge. Knowledge inventories, knowledge maps and expertise directories are examples of meta-knowledge. When a request for information is sent to a computer-based repository or database, the system has no way of determining whether the information is known or present in its memory. For example, if a traditional database is confronted with a request

118



for information on two customers, only one of which exists in the database, the system will have to search exhaustively through all records before it can determine whether a record on the missing customer exist in the database. In the same vein, when a company is faced with an incoming glut of information, confusion often surrounds the determination of the presence or absence of that information. In other words, there is little that the company can do to figure out whether that information represents something truly new or unknown. Creation of meta knowledge is often extremely context dependent and requires the use of pattern recognition or analogical reasoning. Being able to extract meta knowledge from knowledge is a necessary characteristic of an effective KM system.

NOTES

(d) Accommodating multiple degrees of context The use of IT tools is necessary for effective sharing of knowledge through KM system when an organization shares an interpretive context. Most companies build on cross-functional teams – people with differing backgrounds, areas of expertise, organizational affiliations, and culture to solve problems, make decisions, and develop new products and services. In work groups where context is not well shared, knowledge tends to be primarily tacit in nature. Therefore, the significance of rich communications channels and a high degree of interactivity cannot be overemphasized. If loose social bonding exists between potential users of the system, ensure that rich communications (video conferencing, voice, multimedia support, and informal channels) are built in to the KM system as an integrated feature, not as a separate add-on component. (e) Technology choices When choosing a technology or a vendor, it is vital to consider whether that technology or that vendor will be there throughout the life of the system. It is also necessary to ensure that vendor’s technology is a market leader and ancillary products and services remain available. Can the technology deliver consistency that the application requires and it provide the quality is also important considerations? 3.11.2 Tools for collaborative platform Knowledge sharing is an important component for any business to move ahead. The benefits of knowledge management are tremendous if it is used as a catalyst for collaborative efforts. Collaborative tools play an important role in knowledge sharing. They help to foster relations between two business partners and provide access to all the relevant information that is shared on an ongoing basis. Companies are developing these collaborative tools to foster information sharing among employees. Let us analyse some of the commonly available tools and technologies used as collaborative platform.

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(a) Intranets It is certainly true that knowledge management is not a technology issue, effort must still be spent in providing a suitable environment to facilitate knowledge capture and sharing. For most organizations, this role is most easily taken on by the corporate intranet, the existing information resource that is available to most staff. Many intranets are valuable tools to support knowledge. Well-planned intranets make ideal platforms for knowledge management initiatives as employees use the intranet as a learning, collaborative platform if they have the confidence that it will consistently provide them with authoritative, validated and qualified knowledge in return. The organizational intranet can be optimized to support collaborative platform if changes are made to the existing content, publishing processes, and the information architecture of the intranet. (b) Portals A portal is a system of integrated applications, usually implemented through a web browser that offers a single gateway into a universe of information about a specific subject area. An organizational portal serves as an ideal tool that lets a member of an organization to select what information the member wishes to receive, distribute selected information to selected people, organize information and collaborate with others on how information should be organized. They are also capable of handling information from structured as well as unstructured data sources and include collaborative functions, which help put information into action and thus directly contribute to a KM framework within an enterprise. (c) Other collaborative tools Collaborative tools (groupware) are computer-based tools that help people work together and share information. They allow for virtual on-line meetings and data sharing. Some examples of collaborative tools include:

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NOTES

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Collaborative tools are great for bringing geographically dispersed teams together for virtual meetings. A benefit for process redesign teams is that they can now interact more easily with process experts in other locations. This can bring more information to the core team faster and can elicit important inputs that may have been missed just because it was inconvenient or expensive to transport the person to the session physically. Additionally, collaborative tools allow better change management by permitting the team to continuously communicate with the organization at large. 3.11.3 Collaborative knowledge applications (a) Collaborative technologies or tools such as instant messaging and video conferencing are being integrated into KM systems to provide seamless access to all types of information necessary for companies, and even departments within a company, to work together. When companies start using knowledge management as a catalyst for collaborative efforts— ranging from sharing the plans for a new product or an invoice that needs sorting out—the potential benefits are huge. For example, a buyer at a retail firm might be able to get an e-mail alert that a vendor has a concern about a particular purchase order. Together, the retailer and the vendor can view the document simultaneously—online, in real time—to work out the necessary changes. Once the purchase order has been adjusted, both parties can notify the appropriate people within their companies to view the updated purchase order and make the necessary scheduling changes. That notification can happen via e-mail, pager, cell phone or instant messaging, and in many cases the alerts can be triggered automatically. The KM system acts as both a communication hub and data repository. If a further discussion between the retailer and the supplier is necessary, a video conference might be arranged. That video could be stored on a secure Web site to be referred to later if necessary. Essentially, the parties involved in a project can set up a “virtual office” on the Web that provides access to all relevant information that is shared on an ongoing basis. Knowledge management needs to be built around transactions and Collaboration features of a knowledge management system help companies work together. (b) Sales forecasts can also be one of the most critical applications for collaborativebased knowledge management systems. (c) Companies are also integrating KM with their enterprise resource planning (ERP) systems, which are corporate wide systems used for tracking things such as inventory, financial data and even human resource information. (d) Collaborative KM also has the potential for greater sharing of information during the design of a new product. A cell phone maker, for example, can have dozens or even hundreds of component suppliers and work very closely with the top 10 maybe and get them involved in the new phone design, share documents and drawings and specifications to be sure they’ll be able to deliver. This can reduce time to market, and you can hopefully deal with quality issues upfront. 122



(e) The benefit of a Web-based collaborative KM system is that it does not require any specialized software to enable business partners to view documents and other files online; one can access information from a laptop while on move. These systems are now accessible through a standard Internet browser.

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3.12 CASE STUDY TCS sees synergy in Gen X tools A team of engineers at India’s largest IT services provider firm. Tata Consultancy Services (TCS) was working on a project for an important client. While it was cocoordinating work from three geographical units - Europe, South America and India - it was finding it difficult to collaborate through telephone or other voice means as there were language and pronunciation hurdles. It was then that a project manager suggested the use of a central instant messaging (IM) system. Not only could the team coordinate better but it could do so faster and with conviction. This is simply an instance of how the knowledge management (KM) system at TCS has undergone a sea of change over the last 20 years. It now uses tools that are popular among Generation ‘X’ such as IM, blogging, and jam sessions. TCS, for instance, uses a single system for IM worldwide. That’s not all, it uses multiple universal access technology, private IP telephony (where an employee can dial a seven-digit number and speak to anyone anywhere in the world), and video conferencing. “The latest technology was set up two years ago. We have been upgrading regularly. TCS’ knowledge management initiative has always kept pace with the latest technology available at the time. The current KM portal using the latest technology encourages sharing, and acts as a store-house of corporate knowledge,” says Anant Krishnan, Vice President and Chief Technology Officer, TCS. Many of the collaboration tools are yet to be integrated into the KM portal. Currently at TCS, the KM portal - build using Microsoft’s Sharepoint - uses 8-9 channels of communication to get the 100,000 plus employees involved. Other than these channels, the company also uses the ‘Just Ask’ system (embedded into the KM), collaboration tools, Blog platform and Idea Storm. The Idea Storm is a once-a-year event wherein 2-3 topics are posed by the corporate team on which ideas are invited by everyone. IM is clearly the most popular method with almost 1,000 online meets happening on the system everyday across the globe. Followed by Just Ask System, which could be a simple question and answer interaction to a detail discussion.

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However, it is blogging that has caught on quite rapidly. Almost 40,000-50,000 TCS staff blog on the official intranet, including Krishnan. “I use my blog as a means to gathering inputs on some problem I might face or on specific platform,” he says. For instance, within this is a system called TIP. It is an anytime open portal for product innovation and potential new ideas. “I get about 25,000 solutions a year on any given issue right from how TCS should innovate its buses to product innovation. Of this 15-20 are reasonable good product and services idea,” adds Krishnan. TCS has also initiated a feature called My Site. The system, embedded into the KM portal, allows each associate to have a personal page like facebook or orkut. Now, 8,00010,000 employees are using this. Krishnan opines that the immediate advantage of the KM portal is to get solutions to practical problems. “In the 80s KM were deployed with an ability to get tactical teams to work on programmes, today most interaction we see are on short run immediate practical solutions,” says Krishnan. Going ahead the IT behemoth will continue to invest in adopting social networking tools. It will add many more feature in its blogging systems, create Wiki’s among other tools. Krishnan believes as the company becomes larger and as the usage in business will multiply because of the sheer access this allows. Question: Critically analyse the case in the light of collaborative concepts and list the Tata’s collaborative initiatives. SUMMARY Companies that build competitive advantage through effective information and knowledge management must continually refresh and update their intellectual capital. This is the process of organizational learning. Applying the concept of learning to organizations, organizational learning can be described as the collective learning of the organization. Learning Organization is an organization that purposefully takes steps to create architecture to enhance and maximize the potential for explorative and exploitative organizational learning to take place. Knowledge has to be captured and codified in such a way that it can become a part of the existing knowledge base of the organization. Knowledge capture is a demanding mental process in which a knowledge developer collaborates with the expert to convert expertise into a coded program. After knowledge is captured, it is organized and codified in a manner amenable for transfer and effective use. Knowledge codification is organizing and representing knowledge before it is accessed by authorized personnel.

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Knowledge management infrastructure is a prerequisite to knowledge sharing which is viewed as a combination of people, technology and content.

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A Knowledge Repository is a computerized system that systematically and continuously captures, organizes, categorizes and analyses an organization’s knowledge assets. The repository can be searched and data can be quickly retrieved. It is a collaborative system where people can query and browse both structured and unstructured information in order to retrieve and preserve organizational knowledge assets and facilitate collaborative working. Collaborative platform is a tool that supports team members or other tools that share information and contribute to knowledge management system. The collaborative platform, along with the communications network services and hardware, provides the pipeline to enable the flow of explicated knowledge, its context, and the medium for conversations. SHORT QUESTIONS 1. Define organizational learning. 2. Distinguish between organizational learning and learning organization. 3. What are the characteristics of learning organizations? 4. Compare learning organization with traditional organization. 5. Explain knowledge codification in your own words. 6. Distinguish between decision table and decision tree. 7. How knowledge codifications differ from knowledge creation? 8. What is a knowledge map? 9. How does knowledge map differ from decision tree? 10. How would you identify expertise? 11. What is the interviewer effect? 12. Define brainstorming and how it differs from e-brainstorming? 13. What is protocol analysis? 14. What are the distinctive features of on-site observation? 15. Distinguish between protocol analysis and Delphi method. 16. Give the differences between blackboarding and electronic brainstorming? 17. What is concept mapping? 18. What is a knowledge repository? What are its contents? 19. What is knowledge refining? 20. Distinguish between intranet and extranet. 21. What is a portal? 22. What is bulletin board? 125


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LONG QUESTIONS 1. Describe in detail the individual’s role and contributions in organizational learning? 2. What is the commonly employed orientation by organizations for effective dissemination of knowledge? 3. Explain the five learning disciplines propounded by Peter Senge. 4. In your own words, define tacit knowledge capture. What makes it unique? 5. Working with multiple experts has definite benefits and limitations. Cite an example in which the use of multiple experts is a must. Explain your choice. 6. Use an example of your own to illustrate the conditions under which you would be willing to build a KM system based on single expert. Justify your decision? 7. Review briefly some of the problems encountered during an interview? 8. In what way is rapid prototyping related to interviewing? Be specific in your answer. 9. How is brainstorming conducted? Provide an example. 10. In what way does consensus decision making follow brainstorming? 11. Summarize the pros and cons of decision tables versus decision trees. Under what conditions would you use one tool over the other? 12. In your own words, explain knowledge codification. How does it differ from knowledge creation? 13. Present justification for knowledge codification. 14. Define the procedure to design a knowledge repository. 15. Write a detailed note on KM applications. 16. Define collaborative platform? What are its tools for information sharing?

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UNIT IV

KNOWLEDGE CULTURE IN ORGANISATION 4.1 INTRODUCTION The introduction of any new management system into an organization requires a change in culture. For example, the introduction of a customer-relationship management (CRM) system will demand culture change in terms of the way staffs interact with clients. But if any change to a new management system is to deliver value in the long term, then there needs to be a way of sustaining the culture – of making sure that behaviours stay changed, the processes are carried out and that people do what they are supposed to do. Introduction of KM in an organization is also not an exception to this and several researches suggests after review of KM critical success factors identified for its implementation that many factors have been important in implementation of a successful KM program. These factors include culture, infrastructure, technology and measures. A common element in many KM research frameworks and models is organizational culture. Refer the following figure 4.1.

Figure 4.1

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Source: Based on the American Productivity and Quality Center’s Model for Knowledge Management When firms invest numerous resources in their knowledge management infrastructure and do not see the returns later, managers begin to panic. When there are no signs of problems with the applications being used in the department, managers must examine the entire department. To be accurate, managers must assess the knowledge-sharing culture within their company. A knowledge sharing culture is an environment where individuals are willing to disseminate information regardless of the size of the organization or company. In order to do so, individuals must adhere to the norms, values, attitudes and beliefs established by the organization. When these aspects of the knowledge sharing are breached, information will not reach the intended audience and will thus cause a knowledge-transfer bottleneck. Definition of culture Culture is defined as, a) a pattern of basic assumptions, b) invented, discovered, or developed by a given group, c) as it learns to cope with its problems of external adaptation and internal integration, d) that has worked well enough to be considered valid and, therefore e) is to be taught to new members as the f) correct way to perceive, think, and feel in relation to those problems. Culture also” is [composed] of the values, competencies, and beliefs of a group of people that strongly influence whether and how organizational strategies are implemented.” Without the benefit of a culture that recognizes, encourages, and rewards KM activities, consistent performance of KM activities will not occur. Interaction and collaboration among employees is important when attempting to transmit tacit knowledge between individuals or convert tacit knowledge into explicit knowledge, thereby transforming it from the individual to the organizational level. Culture is important because it shapes assumptions about what knowledge is worth exchanging; it defines relationships between individual and organizational knowledge; it creates the context for social interaction that determines how knowledge will be shared in particular situations; and it shapes the processes by which new knowledge is created, legitimated, and distributed in organizations. Lack of technology does not prevent KM activity – it just means that KM activity must be accomplished in different ways. For example, employee suggestion programs are often developed using traditional methods (i.e., methods not involving information technology). Most organizations have sufficient technology to assist them in creating, sharing and documenting knowledge. Sophisticated software applications and other technology may help but are certainly not a requirement. Organized processes are more important. These processes require that the organizational culture value, encourage, and reward KM behavior. Thus a knowledge 128



culture is required where each individual recognizes and accepts knowledge sharing as a desirable behaviour.

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4.2. LEARNING OBJECTIVES After studying this Unit, you should be able to understand the following: •

What is organizational culture?

•

The relation between organizational culture and the business context and how does culture contribute to organizational innovation and success

•

Appreciate the contribution of organizational culture to the management of change

•

Discuss the key organizational culture enablers and the chief obstacles to effective knowledge sharing and KM

•

How to implement knowledge culture enhancement program

•

Describe the key components of a community of practice

•

Define the major roles and responsibilities in a community of practice

•

How CoP is developed and nurtured?

•

How to develop organizational memory?

4.3. ORGANISATIONAL CULTURES Organizational culture describes the collective perceptions, beliefs and values of employees in the workplace. Individuals learn their organizational culture from the day one he or she joins the organization and these learned experiences help them to interpret the work environment so that they can conform and operate effectively in that setting. They also interpret the work culture from a number of visible or implicit cues. The behavioral patterns that are encouraged, discouraged or allowed in an organization also reinforce a certain set of values. Each of these layers contributes to the socialization of new staff and the ongoing reinforcement of existing values, behaviours and priorities. Thus, culture is influenced at a number of levels, from the rules and values adopted by individuals to the alliances formed within the organization and hence it is rare for an organization to have a single uniform culture. Stories, interactions, anecdotes and shared reminiscences all contribute to the building of culture. Several factors have been identified as key influences on organizational culture, including the nature of team work, the climate and related morale, information flows across community, level of individual involvement in organizational processes, type and quality of supervision provided, and the quality of workplace interactions. Leadership can be a particularly powerful influence. A strong leader can enunciate, model and encourage different values through public displays, process re-engineering, strategic direction or ongoing encouragement.

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Culture may act as different ways in an organization which are as follows: (1) It act as a controlling mechanism which provides community members with a collective knowledge of the social expectations, (2) Culture can act as a ‘compass’, providing direction and guidance on the social values which underlie the organization, (3) Culture may also operate as ‘social glue’, seeking to achieve harmony, consensus and cohesion among the disparate members of the community, and (4) It also seeks to ensure both stability and predictable values which are sustained over a long period. Introduction of KM initiatives leads to a range of responses in the form of work patterns and values. Knowledge cultures are particularly susceptible to cultural influences, given the strong reliance on sharing. 4.3.1. Knowledge cultures Knowledge-intensive communities, which rely on service, knowledge and sharing of expertise, need to be concerned with the underlying values which are communicated and adopted by employees. Knowledge communities are characterized as open, communicative cultures which encourage sharing, tolerance, collaboration and trust. Following are some of the implicit values found necessary in collaborative knowledge cultures: (1) Regular communication across levels and organizational units, (2) Colleagues invitation for sharing and learning, (3) Working together is seen as a core activity, (4) Learning is incorporated into the work community and practice, (5) New ideas are welcomed and explored, (6) Innovative ideas and solutions are developed through combined efforts, (7) Openness, honesty and concern for others is encouraged, (8) Employees are kept informed of events, issues and innovations, and (9) Knowledge sharing is actively encouraged by supervision and leadership. Principles of knowledge culture Knowledge management is a value-driven process relying on shared knowledge, collaboration and trust, requiring an integrated approach to changing employee attitudes, gaining employee acceptance and sustaining knowledge sharing in the workplace. The organizational asset is in the minds of each individual and hence organizations need to demonstrate through word and action that they value what employees know. Knowledge flows should be encouraged since employees may operate from a basis of self-interest if the culture does not reinforce the knowledge values. Organizations should not attend more closely to the knowledge system than to the culture since KM relies on people who share and use knowledge to perform their work roles. The various organizational processes and 130



systems also need to be aligned so that the knowledge philosophy is reflected in the structures, practices, performance outcomes and rewards. Thus the knowledge philosophy needs to be embedded in the organizational culture and be evident in various ways to ensure its acceptance and adoption by every employee.

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4.3.2. Improving knowledge culture In order to improve a knowledge-sharing culture, a structured plan should be followed. Here are a few elements of a plan that should be taken into consideration by managers if they need to re-design their culture: • Stress the need to share • Promote trust • Beware of information overload • Have the correct tools • Change the sharers • Report small problems • Build a solid relationship with your vendor (a) Stress the need to share Although this aspect may seem elementary, it is often overlooked. From the moment an individual is brought into a knowledge management unit, he or she should know the importance of sharing the right information with the right people. With sharing being a norm for companies that depend on information to make sound business decisions, knowledge workers must be prepared to disseminate relevant data on an ad hoc basis. To do so, they must: •

Know how knowledge sharing has helped the company in the past through the use of case studies and best practices report

•

Be trained on the tool used to share information within the company

•

Be provided with “a cause-and-effect analysis” of disseminating information when it is needed

•

Be rewarded when information is shared

Individuals who are unable to see the need to share within the company may not be the most appropriate persons to work in the unit. (b) Promote trust One of the most crucial elements behind a solid knowledge-sharing culture is trust. If there is a lack of trust within the company among personnel, knowledge will be hoarded. Information that is in the hands of a few individuals can be dangerous. When only a selected

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few have access to knowledge, they become powerful individuals in the company and can influence decisions that are made by top management. To avoid this situation, managers must promote an environment where knowledge workers can trust their colleagues regarding what they have discovered and analyzed. The following strategies can be implemented to provide a safe and trusting department where information will not be hidden and used for someone’s own purposes. •

Select the right individuals. The department should not be made of individuals with their own respective goals. Instead, it should be made of individuals who can form a team to get tasks done. Team members who have been together for a long duration seem to build relationships based upon trust.

•

Assess the environment. Managers must discover why there is a lack of trust among colleagues. Finding out the root causes will lead to removing the barriers to trust. Obtaining the input from the personnel working in the unit can accomplish this goal.

•

Participate in team building exercises. Personnel should be removed from the working environment and be taken to a retreat to be involved in a series of teambuilding exercises. The exercises should mimic the processes that knowledge workers will carry out on a regular basis.

(c) Beware of information overload Information overload can hinder a knowledge-sharing culture. With the enormous amount of data flowing into a company and the limited amount of time that knowledge workers have per day, there is a limit to how much an individual can disseminate. Being constantly bombarded with information can cause individuals to share the bare minimum, while leaving the rest of the data in emails and databases. As a result, vital information will be held back from the individuals who need easy access to it. If information overload is threatening the culture, the following tips can be used to help improve the process of sharing information in a company. • Begin to filter information on the basis of keywords • Conduct more focus searches on the Web and databases • Readjust the approach used to gather information internally • Have a solid criteria to judge what is relevant to the department (d) Have the correct tools In order to have individuals contribute to a culture that promotes knowledge sharing, they must be given the right tools to deliver data within the company. By listening to the needs of the knowledge workers, managers should be able to evaluate what is needed to transform their department into an efficient unit that transfers data within a few clicks of a mouse. 132



To ensure that the individuals who will be sharing information throughout the company utilize the right tools, managers should consider: •

Investigating which of the present tools in the company are being used to share information

•

Discovering how the present tools can be used more efficiently to make information accessible

•

Continuing to obtain the best possible tools to assist individuals in their work of providing data to key decision makers

•

Finding the tools that will be the right fit with its users for the long term

•

Training personnel to use the applications to execute sharing tasks efficiently

•

Once the tools are obtained and utilized by the intended users, managers must constantly evaluate the performance of the applications and make the necessary modifications to ensure that the department is not encountering any difficulties distributing information.

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(e) Change the sharers If the situation should arise that individual(s) in the department are hindering the flow of data in the company, managers have the power to replace the individual(s). With substantiated claims, personnel can be repositioned within the department to ensure that the skilled individuals who are motivated to share are in the right place. Changing the sharers will breathe new life into the knowledge management unit and hopefully bring new ideas to the table. Making the necessary changes in personnel is a very delicate issue to tackle. Not wanting to be unfair when removing individuals from their present job, managers have to consider issues such as: •

Are the individuals unhappy with their current tasks within the department?

•

Are the individuals skilled enough to remain a part of the team?

•

What contributions have the individuals made over the past 6 to 12 months?

•

Can the company afford to make the necessary changes?

4.4. KNOWLEDGE CULTURE ENABLERS When building an effective knowledge culture, organizations need to have a range of strategies to ensure the values inherent in knowledge management are enacted (i.e. followed in practice) by each employee. A range of influences and people help with knowledge culture development, as they keep people informed of new initiatives, maintain their connection with organizational values and priorities, and encourage ongoing acceptance of important values. Hence knowledge culture enablers are those influences that contribute to the creation of an effective and positive knowledge community.

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Knowledge culture enablers operate over several levels of the organization. In particular, they help align the core values, organizational structures, systems and processes, and individual behaviours to build a positive and effective knowledge culture. Figure 4.2 provides a more detailed overview of those elements which may contribute to effective knowledge cultures. Each element is discussed below. In reviewing these enablers, it is important to recognize their strong interactions. The four levels all contribute in an integrated manner to the creation of an effective knowledge culture. CORE VALUES Collaboration Communication Interaction Innovation Adaptation Learning orientation Trust Knowledge is valued Knowledge is shared

STRUCTURAL SUPPORT

ENACTED VALUES

Organizational structure Transparent decision making Information access Problem solving Communication channels HRM

Models Leaders Opportunities to collaborate Encouragement to collaborate

INTERACTION WITH COLLEAGUES Quality of interaction Focus of interaction Mentorship Team behaviour Co-worker interaction

Figure 4.2 Knowledge Culture Enablers KNOWLEDGE CULTURE Core values. Knowledge communities rely on the collaboration and goodwill of their individual members to stimulate and enhance the knowledge context. As figure 4.2 shows, many core values may influence the knowledge culture. Core values are those values which are believed to be essential to the organization’s growth and achievement of its goal. In the case of a knowledge community, these might include collaborative orientation, open communication, innovation, flexibility, a learning orientation and a willingness to trust. The desired core values in the knowledge community need to be identified, encouraged and monitored. Knowledge based cultures need to nurture innovative and creative thinkers. Employees need to be encouraged to think outside their normal routine and to identify different ways of looking at issue. An effective knowledge culture encourages innovation, from the initial creative idea to the experimentation and sharing of insights with others. 134



Further, it needs to encourage employees to look beyond immediate needs when sharing and exploring knowledge potentials.

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Knowledge communities need to encourage flexible and adaptable behaviour. Organization routines and processes need to be flexible, seeking sound outcomes through a number of different mechanisms. Flexibility encourages people to seek opportunities to experiment and work towards creative alternatives. Knowledge workers need to be responsible for identifying the best ways of achieving the desired goals, with several workers possibly operating differently to achieve the same outcomes. A strong learning orientation is also desirable in knowledge cultures. Many organizations focus on outcomes, aiming to gain financially from each activity. A single minded focus on outcomes can be detrimental to knowledge management as it forces employees to get quick and measurable results. A learning orientation, on the other hand, emphasizes learning through experimentation, ongoing improvement, testing and evaluation to support the long term goals of the organization. Innovative communities rely heavily on learning orientation as they encourage creativity, experimentation and considered risk taking. Organizations need to ensure that they provide plenty of opportunities for learning in the workplace, and accept the diversity of outcomes which maybe generated. Employees will need to be consistently encouraged to work towards the development of their knowledge processes and to see that their contributions are valued. Knowledge cultures must consistently affirm the value placed on knowledge workers. For example, knowledge workers need opportunities to attend conferences, collaborate with others, gestate ideas, communicate and work across organizational boundaries. The ongoing recognition of the valued knowledge of employees is another way of recognizing the human capital in the organization. A simple example is the public acknowledgement of those who contribute to a project, or a celebratory function at the success of an innovation. This also affirms the importance of individual knowledge workers and reinforces the message that the organization is a learning culture. Knowledge intensive organizations need to encourage a strong communal focus to enhance collaboration and sharing across organizational boundaries and groupings. The communal nature of the organization communicates much about the underlying culture of the workplace. If the organization encourages isolationism, where people communicate only with those in their own section, there is less opportunity for cross fertilization of ideas and sharing of different perspectives. Communal interactions can lead to more opportunities to build stronger networks and sharing. Structural support As noted earlier, people interpret messages from their work environment to identify the behaviours and values which should be adopted. Structural support describes the 135


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organizational structure, systems and processes which the organization sponsors through resource allocation and public affirmation. Structural supports, which may include technological systems, human resource process and other forms of work related infrastructure, may operate as either barriers to or facilitators of knowledge cultures. For example, a structural arrangement that reinforces knowledge chains will limit the capacity to collaborate, as bottlenecks will occur. Enterprises that encourage knowledge hubs and network through structural arrangements and/or technological support will foster a stronger collaborative culture. Figure 4.2 lists a number of structural supports which help build knowledge cultures. Organizational transparency stimulates the knowledge culture by keeping employees informed of new and important initiatives which they may apply or contribute to. Open and accountable decision making, collaborative problem solving and planning, and wide sharing and accessibility of information contribute to the underlying culture. Openness breeds collaboration, as it increases the level of trust and the willingness to share. Allied to this openness is the need to encourage problem solving and exploration. In fact, some companies encourage the seeking of problems and their resolution through group deliberation and collaboration. This also affirms the importance and value placed on the knowledge contributions of individuals. To interact effectively, knowledge workers also require efficient and effective communication mechanisms that encourage and enable sharing across the knowledge community. These communication channels may be electronic (such as e-mail or the web site) or based on interpersonal, group or written communication. Communication channels strongly affect the capacity to share and to influence organizational commitment. Organizational communication channels need to encourage openness and network building, particularly in reducing structural boundaries which may operate. A further structural influence relates to the ways individual employees are managed. Human resources management systems are major cultural influences- they help with employee socialization, performance management, and reward and recognition. The level of control and coordination of staff activities also influences the culture. If staff is firmly directed into particular areas of activity, they may have less desire or capacity to experiment or socialize with areas beyond their stipulated roles. Thus, the human resources practices and systems are most important in directing the employee’s focus and priorities. Enacted values The organization culture is strongly influenced by the values which are reflected in actual practice, called enacted values. The real values demonstrated in everyday activities are strong evidence of the real culture which operates, and will be heeded either consciously or subconsciously by each member. 136



Cues and messages about the knowledge culture can be generated from many different sources, particularly from those who provide models of behaviour or hold leadership positions. Their public support of and demonstrated commitment to the values offer strong messages to others. Thus, the more people see the core values in practice, the greater the likelihood they will adopt and practice them

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Interaction with colleagues A further way of building the knowledge culture is through interaction with colleagues. As noted earlier, individuals are strongly influenced by people with whom they regularly interact. The quality and focus of that interaction play a major role in determining the strength of the knowledge culture in the smaller community. There are many aspects to interaction with colleagues. The communication processes which operate across the group can be significant in facilitating a particular culture. Mentorship, team behaviours, co-workers interaction and the presence of communities of practice all play a part in developing the culture. 4.5. IMPLEMENTING KNOWLEDGE CULTURE ENHANCEMENT PROGRAMS The introduction of a knowledge culture program can be exiting and challenging, as people seek to gain a good understanding of what is intended, why it needs to be done, and how it will better support the organization’s need. Every member of the program team needs to be aware of the intended processes, and their own roles, advocacy and leadership are important elements of knowledge culture intervention, as people are asked to review their existing values, work process and strategies. The program implementation process needs to operate from a number of broad principles. Communicating the program intentions and progress Communication is imperative. It keeps people informed and provides opportunities to share and discuss shifts, there are opportunities to overcome concerns and fears, discuss the feasibility of the strategies to be implemented, and develop further involvement and contribution. Every member of the organization will ultimately be affected by knowledge culture change programs, as they will affect values, processes and structural support. Regular communication reduces uncertainty and increases understanding and learning. Employees also need access to communication channels where they may offer feedback on the cultural and systematic changes. Many developmental processes are sabotaged by innuendo and gossip before they are even in the public domain. Effective change processes ensure that accurate information is available at all times. A program web site can be a useful way of ensuring good dissemination of the purpose, strategy and desired outcomes of the program. As the program evolves, the web site can also garner feedback on pilot group experiences and other contributor insights, which may help to allay concerns. 137


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Communication may also be in the form of open forums, public messages from the chief sponsor of the project, and focus group meetings in which the shifting knowledge focus and its implications may be discussed. These communication channels need to be maintained over the course of the program, so that members of the organization’s community can seek further affirmation and advice as the process continues. To achieve acceptance of and commitment to the planned intervention, the knowledge organization needs to effectively communicate the intended intervention, prepare members for the likely impact of any changes, publicize any time frames or activities, and promote the communication mechanisms available for both information and feedback. Pilot testing Cultural change programs rarely run smoothly as they seek to influence and persuade organizational members to adopt different values, attitudes and patterns of behaviours. Some changes may be enthusiastically embraced, but others may be bitterly opposed. The promotion of new values and processes without careful testing of the strategy can be high risk. Pilot tests of the planned changes can help identify possible problems. They also build expertise within the community which may be accessed in the second stage of the implementation. Further, they enable the development of case studies and real experts who can share their insights with others who follow. They also allow close support and analysis of the various processes by the program team. The time taken to undertake pilot studies is well rewarded in terms of success and the removal of problems. If need to be, a further pilot study might be done before large scale implementation. Participants in these initial test sites need to be both recognized and valued for the contribution they make. Accommodating difference within the knowledge culture Knowledge intensive communities encourage adaptive behaviours. It is important for members to make sense of the changes, as they test any proposed work or value enhancements and then, following their affirmation of the worth of the proposed changes, commit to trialing new behaviours or ideas. Thus, in keeping with the knowledge culture precepts, members of the knowledge community need to be encouraged to test any new strategies and communicate their insights and approaches that may be adopted. Adaptation can lead to some very different outcomes from those initially planned by the program managers and sponsors. Contributors may seek to shift the focus of the proposed cultural change, and to integrate their own existing preferences. When interventions are planned, they need to be open to renegotiation and adaptation as further insights are gained.

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Supporting planned cultural interventions

NOTES

Employees and other knowledge users need to be well supported during cultural intervention. Knowledge champions are particularly important. Members with significant roles may need to be provided with time release so they can give their full support to the initiative. Their positive outlook, knowledge of the full intervention plan, and response to difficulties will facilitate the smooth running of the program. A help desk can also be of great value during the initial implementation of key changes, as it gives users an easy access point for registering difficulties, ideas, suggestions and ongoing concerns. As the initiative takes root, users can be encouraged to share their ideas and insights with others, through mentoring or by communal sharing through a range of dissemination channels. Communal learning is an important element of the building of knowledge culturesit creates positive attitudes to the desired organizational approaches to knowledge management. Various networking options might be encouraged; including bulletin boards, list-servs, and support of frequently asked questions or frequently identified problems. Coping with issues as they arise is very important, as it assures users that their needs and experiences are of great concern. The prompt resolution of problems also ensures that negativity does not become a prevailing attitude. 4.6. MAINTAINING THE KNOWLEDGE CULTURE Each individual contributes to the organization’s prevailing knowledge culture. Events, messages and enacted values are reinterpreted constantly to ensure there is agreement between personal beliefs, professional behaviours and desired consequences. Knowledge communities rely on their members to maintain a culture of respectful interchange and collaboration. However, slippage can occur if the organization does not actively sustain the knowledge culture which has been established. A range of strategies can help maintain the knowledge culture. The socialization of new members, using both knowledge workers and official knowledge leaders is an important strategy, as it affirms the culture of the workplace immediately, and clarifies the values which should be evident in the new employee’s work practices. The development of reward and performance management systems which integrate knowledge values expectations are key aspects of ongoing support for the knowledge culture. The development and mentoring of new leaders and ongoing professional development of knowledge related competencies also send strong messages regarding the importance of these contributors. Similarly, the integration and constant improvement of existing knowledge systems and services (such as the knowledge help desk) can be of significant value in encouraging positive responses to the knowledge culture. Recognition of key knowledge workers, celebration of major knowledge advancements and strategies, and ongoing sharing of experiences in enhancing knowledge management all serve to reinforce the strong knowledge culture. An organizational developer who strives to maintain the knowledge culture throughout 139


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the community can be of great value. Larger organizations regard this role as an important full time commitment. The appointment of a coordinator of this culture can be one of the strongest affirmations of the importance of the knowledge culture. Supporting leader’s maintenance of the knowledge culture An important element of sustaining community is to ensure the leaders are well supported and nurtured. Knowledge champions play a significant role in sustaining positive and informed approaches to knowledge sharing across the knowledge community. Their leadership strategies also need to be supported as they seek to influence and guide the knowledge culture. Their role can be a demanding and consuming process, and these champions may not have extensive skills in leading guiding cultural change. Support may therefore operate in a number of ways. Certainly, briefing sessions at the start of initiatives are highly beneficial, as they offer guidance on the issues to be disseminated, and help build leadership networks. Opportunities to get together and share learning and concerns with other knowledge leaders can facilitate creative problem solving and maintain motivation. The support for leaders is an important element of the knowledge development strategy, since it ensures that there are strong and knowledgeable champions with a sound understanding of the strategic needs of the organization. Maintaining the cultural wellbeing of communities of practice Communities of practices (CoPs) benefit from organizational development support to help sustain their cultural wellbeing. Many start with a flourish, but gradually lose their impetus. Organizations which encourage CoPs have a responsibility to support the maintenance and ongoing development of groups identified as strategically important. Support may be in the form of guidance on how to develop and sustain a positive constructive CoP, or may more directly support particular groups with additional resourcing and expertise. There are some simple approaches to ensure a healthy, respectful and viable CoP. •

Clearly define the purpose or domain of the CoP so that the members have a good understanding of the focus, likely scope of activities and expectations of each contributor.

•

Facilitate the identification of potential members to encourage the connection of those with common interests, talents or expertise to contribute to the group.

•

Support key members with recognition in terms of workload, administrative or technological support, leadership development opportunities, or some initial seed funding to develop the group.

•

Support the group’s identification and development of its individual and group capabilities and identity. This support might consist of a designated meeting area, ongoing team development activities, or simply a chance to remove the group from the normal work routine. The stronger the organizational support, the greater the willingness of the group members to commit to such networks.

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•

Provide opportunities to interact across CoPs. This wider interaction can greatly help the various groups identify common interests, potential members and likely areas of collaboration.

•

Consider appointing a broker to act as a facilitator and group support agent. Brokers can help with the complex processes of translating, coordinating and suitably integrating the different perspectives of the various members. This can be particularly helpful when the participants find it hard to contribute the extra effort to maintain the CoP connection and focus. It can also reduce conflicts of interest.

NOTES

Knowledge cultures affect the way knowledge management operates in a particular organization. Better understanding of the ways cultures can be influenced enhances the building and sustaining of knowledge cultures. Greater recognition of the interactive nature of values and structural support has been particularly helpful in enhancing culture. 4.7. COMMUNITIES OF PRACTICE We now recognize knowledge as a key source of competitive advantage in the business world, but we still have little understanding of how to create and leverage it in practice. Traditional knowledge management approaches attempt to capture existing knowledge within formal systems, such as databases. Yet systematically addressing the kind of dynamic “knowing” that makes a difference in practice requires the participation of people who are fully engaged in the process of creating, refining, communicating, and using knowledge. We frequently say that people are an organization’s most important resource. Yet we seldom understand this truism in terms of the communities through which individuals develop and share the capacity to create and use knowledge. Even when people work for large organizations, they learn through their participation in more specific communities made up of people with whom they interact on a regular basis. These “communities of practice” are mostly informal and distinct from organizational units. However, they are a company’s most versatile and dynamic knowledge resource and form the basis of an organization’s ability to know and learn. 4.7.1. Defining Communities of Practice a. Communities of Practice (CoPs) are groups of people in organizations that form to share what they know, to learn from one another regarding some aspects of their work and to provide a social context for that work. b. Communities of practice are groups of people with common interest who meet to share their insights in order to develop better solutions to problems or challenges. Although the term “Community of Practice” is new, CoPs are not. Such groups have been around ever since people in organizations realized they could benefit from sharing their knowledge, insights, and experiences with others who have similar interests or goals.

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One of the best-known examples of a CoP was formed by the copy machine repair technicians at Xerox Corporation. Through networking and sharing their experiences, particularly the problems they encountered and the solutions they devised, a core group of these technicians proved extremely effective in improving the efficiency and effectiveness of efforts to diagnose and repair Xerox customers’ copy machines. The impact on customer satisfaction and the business value to Xerox was invaluable. Yet, for the most part, this was a voluntary, informal gathering and sharing of expertise, not a “corporate program” (however, once the company realized the value of the knowledge being created by this CoP, steps were taken to support and enhance the efforts of the group). Members of a community are informally bound by what they do together–from engaging in lunchtime discussions to solving difficult problems–and by what they have learned through their mutual engagement in these activities. A community of practice is thus different from a community of interest or a geographical community, neither of which implies a shared practice. A community of practice defines itself along three dimensions: • What it is about – its joint enterprise as understood and continually renegotiated by its members • How it functions - mutual engagement that bind members together into a social entity • What capability it has produced – the shared repertoire of communal resources (routines, sensibilities, artifacts, vocabulary, styles, etc.) that members have developed over time. Communities of practice also move through various stages of development characterized by different levels of interaction among the members and different kinds of activities. Communities of practice develop around things that matter to people. As a result, their practices reflect the members’ own understanding of what is important. Obviously, outside constraints or directives can influence this understanding, but even then, members develop practices that are their own response to these external influences. Even when a community’s actions conform to an external mandate, it is the community–not the mandate– that produces the practice. In this sense, communities of practice are fundamentally selforganizing systems. CoP groups function through discussion lists, web-site forums or other forms of virtual networking. 4.7.2. Communities of Practice in Organizations Communities of practice exist in any organization. Because membership is based on participation rather than on official status, these communities are not bound by organizational affiliations; they can span institutional structures and hierarchies. They can be found:

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•

Within businesses: Communities of practice arise as people address recurring sets of problems together. So claims processors within an office form communities of practice to deal with the constant flow of information they need to process. By participating in such a communal memory, they can do the job without having to remember everything themselves.

•

Across business units: Important knowledge is often distributed in different business units. People who work in cross-functional teams thus form communities of practice to keep in touch with their peers in various parts of the company and maintain their expertise. When communities of practice cut across business units, they can develop strategic perspectives that transcend the fragmentation of product lines. For instance, a community of practice may propose a plan for equipment purchase that no one business unit could have come up with on its own.

•

Across company boundaries: In some cases, communities of practice become useful by crossing organizational boundaries. For instance, in fast-moving industries, engineers who work for suppliers and buyers may form a community of practice to keep up with constant technological changes.

•

Communities of practice are not a new kind of organizational unit; rather, they are a different cut on the organization’s structure–one that emphasizes the learning that people have done together rather than the unit they report to, the project they are working on, or the people they know. Communities of practice differ from other kinds of groups found in organizations in the way they define their enterprise, exist over time, and set their boundaries:

•

A community of practice is different from a business or functional unit in that it defines itself in the doing, as members develop among themselves their own understanding of what their practice is about. This living process results in a much richer definition than a mere institutional charter. As a consequence, the boundaries of a community of practice are more flexible than those of an organizational unit. The membership involves whoever participates in and contributes to the practice. People can participate in different ways and to different degrees. This permeable 143

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periphery creates many opportunities for learning, as outsiders and newcomers learn the practice in concrete terms, and core members gain new insights from contacts with less-engaged participants.

NOTES •

A community of practice is different from a team in that the shared learning and interest of its members are what keep it together. It is defined by knowledge rather than by task, and exists because participation has value to its members. A community of practice’s life cycle is determined by the value it provides to its members, not by an institutional schedule. It does not appear the minute a project is started and does not disappear with the end of a task. It takes a while to come into being and may live long after a project is completed or an official team has disbanded.

•

A community of practice is different from a network in the sense that it is “about” something; it is not just a set of relationships. It has an identity as a community, and thus shapes the identities of its members. A community of practice exists because it produces a shared practice as members engage in a collective process of learning.

People belong to communities of practice at the same time as they belong to other organizational structures. In their business units, they shape the organization. In their teams, they take care of projects. In their networks, they form relationships. And in their communities of practice, they develop the knowledge that lets them do these other tasks. This informal fabric of communities and shared practices makes the official organization effective and, indeed, possible. Communities of practice have different relationships with the official organization. The table “Relationships to Official Organization” shows different degrees of institutional involvement, but it does not imply that some relations are better or more advanced than others. Rather, these distinctions are useful because they draw attention to the different issues that can arise based on the kind of interaction between the community of practice and the organization as a whole. Relationships to Official Organization Relationship

Challenges typical of the relationship

Definition

Invisible to the organization and Lack of reflexivity, awareness Unrecognized sometimes even to members of value and of limitation themselves Bootlegged

Only visible informally to a circle of people in the know

Getting resources, having an impact, keeping hidden

Legitimized

Officially sanctioned as a valuable entity

Scrutiny, over-management, new demands

Strategic

Short-term pressures, blindness Widely recognized as central to of success, smugness, elitism, the organization's success exclusion

Capable of redefining its Transformative environment and the direction of the organization 144

Relating to the rest of the organization, acceptance, managing boundaries ANNA UNIVERSITY CHENNAI


4.7.3. Importance of Communities to Organizations Communities of practice are important to the functioning of any organization, but they become crucial to those that recognize knowledge as a key asset. From this perspective, an effective organization comprises a constellation of interconnected communities of practice, each dealing with specific aspects of the company’s competency–from the peculiarities of a long-standing client, to manufacturing safety, to esoteric technical inventions. Knowledge is created, shared, organized, revised, and passed on within and among these communities. In a deep sense, it is by these communities that knowledge is “owned” in practice.

NOTES

Communities of practice fulfill a number of functions with respect to the creation, accumulation, and diffusion of knowledge in an organization: a) They are nodes for the exchange and interpretation of information. Because members have a shared understanding, they know what is relevant to communicate and how to present information in useful ways. As a consequence, a community of practice that spreads throughout an organization is an ideal channel for moving information, such as best practices, tips, or feedback, across organizational boundaries. b) They can retain knowledge in “living” ways, unlike a database or a manual. Even when they routines certain tasks and processes, they can do so in a manner that responds to local circumstances and thus is useful to practitioners. Communities of practice preserve the tacit aspects of knowledge that formal systems cannot capture. For this reason, they are ideal for initiating newcomers into a practice. c) They can steward competencies to keep the organization at the cutting edge. Members of these groups discuss novel ideas, work together on problems, and keep up with developments inside and outside a firm. When a community commits to being on the forefront of a field, members distribute responsibility for keeping up with or pushing new developments. This collaborative inquiry makes membership valuable, because people invest their professional identities in being part of a dynamic, forward-looking community. d) They provide homes for identities. They are not as temporary as teams, and unlike business units, they are organized around what matters to their members. Identity is important because, in a sea of information, it helps us sort out what we pay attention to, what we participate in, and what we stay away from. Having a sense of identity is a crucial aspect of learning in organizations. Consider the annual computer drop at a semiconductor company that designs both analog and digital circuits. The computer drop became a ritual by which the analog community asserted its identity. Once a year, their hero would climb the highest building on the company’s campus and drop a computer, to the great satisfaction of his peers in the analog gang. The corporate world is full of these displays of identity, which manifest themselves in the jargon people use, the clothes they wear, and the remarks they make. If companies want to benefit from people’s creativity, they must support communities as a way to help them develop their identities. 145


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Communities of practice structure an organization’s learning potential in two ways: through the knowledge they develop at their core and through interactions at their boundaries. Like any asset, these communities can become liabilities if their own expertise becomes insular. It is therefore important to pay as much attention to the boundaries of communities of practice as to their core, and to make sure that there is enough activity at these boundaries to renew learning. For while the core is the center of expertise, radically new insights often arise at the boundary between communities. Communities of practice truly become organizational assets when their core and their boundaries are active in complementary ways. To develop the capacity to create and retain knowledge, organizations must understand the processes by which these learning communities evolve and interact. We need to build organizational and technological infrastructures that do not dismiss or impede these processes, but rather recognize, support, and leverage them. 4.7.4. Developing and nurturing Communities of Practice Just because communities of practice arise naturally does not mean that organizations can’t do anything to influence their development. Most communities of practice exist whether or not the organization recognizes them. Many are best left alone–some might actually wither under the institutional spotlight. And some may actually need to be carefully seeded and nurtured. But a good number will benefit from some attention, as long as this attention does not smother their self-organizing drive. Whether these communities arise spontaneously or come together through seeding and nurturing, their development ultimately depends on internal leadership. Certainly, in order to legitimize the community as a place for sharing and creating knowledge, recognized experts need to be involved in some way, even if they don’t do much of the work. But internal leadership is more diverse and distributed. It can take many forms: a) The inspirational leadership provided by thought leaders and recognized experts b) The day-to-day leadership provided by those who organize activities c) The classificatory leadership provided by those who collect and organize information in order to document practices d) The interpersonal leadership provided by those who weave the community’s social fabric e) The boundary leadership provided by those who connect the community to other communities f) The institutional leadership provided by those who maintain links with other organizational constituencies, in particular the official hierarchy g) The cutting-edge leadership provided by those who shepherd “out-of-the-box” initiatives.

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These roles may be formal or informal, and may be concentrated in a core group or more widely distributed. But in all cases, leadership must have intrinsic legitimacy in the community. To be effective, therefore, managers and others must work with communities of practice from the inside rather than merely attempt to design them or manipulate them from the outside. Nurturing communities of practice in organizations includes:

NOTES

1) Legitimizing participation. Organizations can support communities of practice by recognizing the work of sustaining them; by giving members the time to participate in activities; and by creating an environment in which the value communities bring is acknowledged. To this end, it is important to have an institutional discourse that includes this less-recognized dimension of organizational life. Merely introducing the term “communities of practice” into an organization’s vocabulary can have a positive effect by giving people an opportunity to talk about how their participation in these groups contributes to the organization as a whole. 2) Negotiating their strategic context. In what Richard McDermott calls “doubleknit organizations,” people work in teams for projects but belong to longer-lived communities of practice for maintaining their expertise. The value of team-based projects that deliver tangible products is easily recognized, but it is also easy to overlook the potential cost of their short-term focus. The learning that communities of practice share is just as critical, but its longer-term value is more subtle to appreciate. Organizations must therefore develop a clear sense of how knowledge is linked to business strategies and use this understanding to help communities of practice articulate their strategic value. This involves a process of negotiation that goes both ways. It includes understanding what knowledge–and therefore what practices–a given strategy requires. Conversely, it also includes paying attention to what emergent communities of practice indicate with regard to potential strategic directions. 3) Being attuned to real practices. To be successful, organizations must leverage existing practices. For instance, when the customer service function of a large corporation decided to combine service, sales, and repairs under the same 800 number, researchers from the Institute for Research on Learning discovered that people were already learning from each other on the job while answering phone calls. They then instituted a learning strategy for combining the three functions that took advantage of this existing practice. By leveraging what they were already doing, workers achieved competency in the three areas much faster than they would have through traditional training. More generally, the knowledge that companies need is usually already present in some form, and the best place to start is to foster the formation of communities of practice that leverage the potential that already exists. 4) Fine-tuning the organization. Many elements in an organizational environment can foster or inhibit communities of practice, including management interest, reward systems, work processes, corporate culture, and company policies. These factors rarely determine whether people form communities of practice, but they can facilitate or hinder participation. For example, issues of compensation and recognition often come up. Because communities of practice must be self-organizing to learn effectively 147


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and because participation must be intrinsically self-sustaining, it is tricky to use reward systems as a way to manipulate behavior or micro-manage the community. But organizations shouldn’t ignore the issue of reward and recognition altogether; rather, they need to adapt reward systems to support participation in learning communities, for instance, by including community activities and leadership in performance review discussions. Managers also need to make sure that existing compensation systems do not inadvertently penalize the work involved in building communities. 5) Providing support. Communities of practice are mostly self-sufficient, but they can benefit from some resources, such as outside experts, travel, meeting facilities, and communications technology. A companywide team assigned to nurture community development can help address these needs. This team typically • provides guidance and resources when needed • helps communities connect their agenda to business strategies • encourages them to move forward with their agenda and remain focused on the cutting edge • makes sure they include all the right people • helps them create links to other communities Such a team can also help identify and eliminate barriers to participation in the structure or culture of the overall organization; for instance, conflicts between short-term demands on people’s time and the need to participate in learning communities. In addition, just the existence of such a team sends the message that the organization values the work and initiative of communities of practice. KM Viewpoint 4.1 Different members of an organization can take actions in their own domains to support communities of practice and maximize the benefits they can provide: • Line managers must make sure that people are able to participate in the right communities of practice so they sustain the expertise they need to contribute to projects. • Knowledge managers must go beyond creating informational repositories that take knowledge to be a "thing," toward supporting the whole social and technical ecology in which knowledge is retained and created. • Training departments must move the focus from training initiatives that extract knowledge out of practice to learning initiatives that leverage the learning potential inherent in practice. • Strategists must find ways to create two-way connections between communities of practice and organizational strategies. • Change managers must help build new practices and communities to bring about changes that will make a constructive difference. • Accountants must learn to recognize the capital generated when communities of practice increase an organization's learning potential. • Facilities managers must understand the ways in which their designs support or hinder the development of communities of practice. • Work process designers must devise process improvement systems that thrive on, rather than substitute for, engaged communities of practice. 148



4.8. DEVELOPING ORGANISATIONAL MEMORY‘ Organizational or corporate memories record the accumulated knowledge about the services and the products of an organization, with the purpose of supporting the continuous enhancement of knowledge-intensive work practices and of alleviating the risk of “corporate amnesia” due to experts taking away their knowledge when they leave.

NOTES

It is possible to build a corporate memory in a totally unstructured way: by maintaining all documents and recording all practices of an organization. This approach seems inexpensive; it involves, however, amassing a lot of irrelevant information that will need to be filtered later on. The opposite approach involves an intensive initial knowledge engineering effort leading to the construction of corporate knowledge bases and expert systems. Buckingham Shum proposes a middle way, which can be particularly viable for organizations of knowledge workers: the recording of relevant team activities through the use of hyper textual representations linking the different steps of the activities, highlighting the different options considered at each step and associating actions and decisions with role and competencies of the people involved. Such hyper textual representations are created and negotiated ex vivo by knowledge workers, rather than reconstructed post mortem by knowledge engineers; they record process knowledge related to knowledge-intensive problem-solving and decision-making activities. The negotiation aspect is very relevant, because explicit knowledge comes often dressed with a deceitful appearance of “objectivity” which in reality hides a specific point of view. Acknowledging the existence of this point of view and allowing for its negotiation is an important step towards getting organizations knowing themselves and making workers fully empowered. In this way, the negotiated point of view will effectively reflect the commitments of all involved stakeholders, and not just of single groups and individuals holding ``power’’ roles and positions in the organization. We can also describe instead a full-fledged knowledge engineering approach suitable for building corporate memories from the product knowledge of large manufacturing organizations such as automotive industries. Starting from the collections of documents about the products of these organizations (product specifications, instruction manuals, trouble shooting guides etc.), they show how to extract the explicit knowledge that is in there and integrate it with further explicit knowledge obtained by externalizing the tacit knowledge related to the context of use of the documents. The knowledge thus acquired is represented in the form of conceptual graphs that relate the different parts of the products, associate parts with properties and connect single actions for operating the products into complex plans corresponding to full operating instructions. They show then how the initial investment needed for building this type of knowledge bases pays off in a number of ways: by providing capabilities for automatic multilingual document generation, by providing a knowledge space of existing product knowledge to support the fast design of new products, by providing a language-independent semantic representation of product knowledge that could be used to enforce enterprise coherence for companies operating in multilingual and multicultural environments. 149


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The software engineering requirements for supporting this type of corporate memories, needed for the strong integration of corporate memories with existing IT infrastructures, with particular regard to existing capabilities for database management, document management and business process support. A corporate memory architecture that meets these requirements is necessary and the paradigm shift of corporate memories from artificial intelligence to a more general framework for IT integration is the need of the hour. SUMMARY Organizational culture describes the collective perceptions, beliefs and values of employees in the workplace. Culture penetrates to the essence of an organization. Individuals learn their organizational culture from the day one he or she joins the organization and these learned experiences help them to interpret the work environment so that they can conform and operate effectively in that setting. Culture is important because it shapes assumptions about what knowledge is worth exchanging; it defines relationships between individual and organizational knowledge; it creates the context for social interaction that determines how knowledge will be shared in particular situations; and it shapes the processes by which new knowledge is created, legitimated, and distributed in organizations. When building an effective knowledge culture, organizations need to have a range of strategies to ensure the values inherent in knowledge management are enacted (i.e. followed in practice) by each employee. Knowledge culture enablers are those influences that contribute to the creation of an effective and positive knowledge community. Communities of Practice (CoPs) are groups of people in organizations that form to share what they know, to learn from one another regarding some aspects of their work and to provide a social context for that work. Communities of practice structure an organization’s learning potential in two ways: through the knowledge they develop at their core and through interactions at their boundaries. Organizational or corporate memories record the accumulated knowledge about the services and the products of an organization, with the purpose of supporting the continuous enhancement of knowledge-intensive work practices. SHORT QUESTIONS 1. 2. 3. 4.

What do you mean by knowledge sharing culture? Define organizational culture. Define community of practice. Write a note on organizational memory.

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LONG QUESTIONS

NOTES

1. What is the culture of an organization? Why is it important to understand? 2. What are some of the key enablers and major obstacles to effective knowledge sharing that can be attributed to the overall organizational culture? 3. What are the various knowledge culture enablers? Explain. 4. How to cultivate knowledge culture in organizations? 5. Choose three organizational culture elements and consider how these might be different in a manufacturing community and knowledge community? 6. The chapter describes a number of knowledge culture features. Choose any four of these and outline how their absence might affect the knowledge community? 7. ‘Knowledge culture interventions should be centrally driven’. Discuss this statement. 8. Why do knowledge cultures need to be maintained? Whose responsibility is it? 9. How do you develop and nurture a CoP in an organization?

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UNIT V

KNOWLEDGE MANAGEMENT – LOOKING AHEAD 5.1. INTRODUCTION Many dimensions are involved in describing knowledge management tools. The following are some of the KM technologies as tools that • • • •

Enhances and enable knowledge generation, codification, and transfer. Generate knowledge to make knowledge available for others. Transfer knowledge to decrease problems with time and space when communicating in an organization.

KM technologies are classified according to the following scheme: 1. 2. 3. 4. 5. 6. 7. 8. 9.

Communication Collaboration Content creation Content management Adaptation E-learning Personal tools Artificial intelligence Networking

The knowledge capture and creation does not make extensive use of technologies but a wide range of KM technologies may be used to support knowledge sharing and dissemination as well as knowledge acquisition and application. Many tools and techniques are borrowed from other disciplines, and others are specific to KM. All of them need to be mixed and matched in the appropriate manner in order to address all the needs of the KM discipline, and the choice of tools to be included in the KM toolkit must be consistent with the organization’s overall business strategy.

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5.2. LEARNING OBJECTIVES After studying this Unit, you should be able to understand the following: •

Describe the key communication technologies that can be used to support knowledge sharing within an organization.

•

Illustrate the major advantages and drawbacks of synchronous versus asynchronous KM technologies.

•

Define data mining and explore its applications.

•

Compare and contrast different types of intelligent agents and show how they can be used to personalize KM technologies.

•

Define the difference between push and pull KM technologies.

•

Characterize the major groupware tools and explain how they would be implemented within an organization.

•

Understand the major components of a knowledge repository and explain how organizations make optimal use of one.

•

Examines the different stages of KM implementations and metrics for evaluating an initiative’s progress. Introduces a “KM measurement bell curve” and offers explanation of organizations’ ongoing assessment techniques.

•

Discuss the purpose of a knowledge audit and how to conduct a KM audit.

•

Identify the various career opportunities emerges in the field of KM and qualities and attributes required for knowledge career.

•

Analyse selected case studies in KM field.

5.3. KNOWLEDGE MANAGEMENT TOOLS AND TECHNIQUES Knowledge management tools are the ‘face and place’ as well as the ‘nuts and bolts’ of knowledge in the 21st century workspace which make data into knowledge. Knowledge management implementation requires a wide range of diverse tools that are responsible in the KM cycle. Technology is used to facilitate primarily communication, collaboration, and content management for better knowledge capture, sharing, dissemination and application. KM-enabling tools and techniques are also play a useful facilitating role in learning organizations, especially in dealing with the information overload that is plaguing most organizations that have launched an intranet, enterprise resource planning (ERP) or business intelligence system. Major categories of KM tools are presented here. 5.3.1. Knowledge capture and creation tools (a) Content Creation Tools It is predicted that content management systems (CMS) will become a “commodity” in the future. Many content management system projects fail owing to lack of good implementation standards and a lack of an understanding of usability issues. Technology154



only approaches will continue to generate unsuccessful projects. CMS should be handled in a strategic way. These failures provide a valuable source of learning. The move towards open standards would greatly assist the evolution of CMS, which is likely to proceed with the use of XML-based protocols for communicating with and between content management systems. Additional standards are needed for storing, structuring, and managing content. Eventually, content, documents, records, and knowledge management will converge, which will be of greatest benefit to organizations. As yet, there is no merged platform to accommodate such a convergence.

NOTES

Authoring tools, the most commonly used content creation tools, and range from the general (e.g. word processing) to the more specialized (e.g. web page design software). Annotation technologies enable short comments to be attached to specific sections of text document, often by a number of different authors (e.g. by making use of the track changes feature in Word). This allows a “running commentary” to be built up and preserved. Annotations may be public (visible to all who access and read the document) or private (visible to the author only). (b) Data Mining and Knowledge Discovery The data mining and knowledge discovery processes automatically extract predictive information from large databases based on statistical analysis (typically, cluster analysis). Using a combination of machine learning, statistical analysis, modeling techniques, and database technology, data mining detects hidden patterns and subtle relationships in data and infers rules that allow the prediction of future results. Raw data is analyzed in order to offer a model that attempts to explain the observed patterns. This model can then be used to predict future occurrences and to forecast expected outcomes. A large number of inputs are required, usually over a significant period of time, and the types of model produced range from “easy” to “almost impossible” to understand. Examples of easy-to-understand models are decision trees. Regression analyses are moderately easy to understand, and neural networks remain black boxes. The major drawback of the black box models is that it becomes very difficult to hypothesize about casual relationships. Variables may be correlated, but this relationship may not have any meaning or usefulness. For example, a major bank found a correlation between the state an applicant lived in and a higher percentage of defaults on loans given out. This finding should not be the basis for a policy that would automatically reject any applicants from their state. Reality checks are always needed with statistics before any conclusions can be drawn. Typical applications of data mining and knowledge discovery systems include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, credit risk analysis, and market basket analysis. However, there are usually a few gems to be

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mined with data mining applications. These are often unexpected correlations that upon further study yield some useful (and often actionable) insights into what is occurring. Data mining tools that are currently in use include: •

Statistical analysis tools (e.g. SAS).

•

Data mining suites (e.g. enterprise Miner).

•

Consulting/outsourcing tools such as EDS, IBM, and Epsilon. (Note that these are models, not just software).

•

Data visualization software that coherently presents a large amount of information in a small space. They make use of human information processing capabilitiesyour eyes- to detect patterns, for example, in a virtual reality or simulation environment where you can “walk around the data points”.

It is also possible to apply this technique and use these tools to mine content other than data-namely, text mining and thematic analysis and web mining-to look at what content, how often, for how long (e.g. number of hits), which is very helpful in content management. Similarly, skill mining or expertise profiling can be used to detect patterns in online curriculum vitae of organizational members. Expertise location systems can be automatically created based on the content that has been mined. Commercial software systems can also be used to mine e-mail data in order to determine who is answering what types of queries or themes. Organizational experts and expertise can be detected by looking at the patterns of questions and answers contained within the e-mails. The same caveat applies to all of these data mining applications: a human being is always needed in the loop in order to carry out “reality checks” (i.e. to verify and validate that the patterns do indeed exist and that they have been interpreted in a useful and valuable manner.) (c) Blogs A blog is a slang name for a web log. For the uninitiated, a web log is a popular and fairly personal content form on the Internet. A person’s web log is much like an open diary. It chronicles what a person wants to share with the world on an almost daily basis. A blog is a frequently updated, publicly accessible journal. Although the “blogosphere” started off as a medium for mostly personal musings, it has evolved into a tool that offers some of the most insightful information on the web. Furthermore, blogs are becoming much more common, as businesses, politicians, policy makers, and even libraries and library associations have begun to blog as a way of communicating with their patrons and constituents. everal librarians publish blogs that offer a wealth of information about social software and its uses. SNTReport.com focuses on the social software industry and how social software tools are being used to help people collaborate. Blogs not only offers a new way to communicate with customers, but they have internal uses as well. For example, large organizations can use a well formed blog to exchange ideas and information about web 156



development projects, training initiatives, or research issues. These questions and answers can be cross-indexed and archived, which helps build a knowledge network among the participating members. Most importantly, the price of setting up a well formed, secure blog and leverage it into a knowledge and content management tool is a pittance when compared to the cost of other, proprietary solutions.

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At present, the majority of blogs are published exclusively in text. The next generation of blogs, however, will implement audio and video elements, bringing a sophisticated multimedia blend to the medium. Blogs are collections of articles or stories arranged in reverse chronology and are generally updated more frequently than regular web pages. Just like any other information on the net, there is no guarantee of authority, accuracy, or lack of bias. In fact, personal blogs are frequently biased and can be good sources of opinion and information from the “man on the street”. Because blogs can be updated on the fly, they frequently have access to unfiltered information faster from war zones and sites of natural disasters than the mainstream media outlets. Blogs are also good sources of unfiltered information on either faulty or very useful products. In the beginning, blogs appeared in search results alongside regular web pages. Since blogs are technologically any different from other web pages (that is, they are HTML, XML, java script, etc. - it is their format, not their coding that is different). Spiders and bots (or web crawlers, knowledge robots) automatically search for information online and collect posts (i.e. messages that are submitted to a computerized messaging system) the same way as they collect other online information. Search engines that place greater value on sites that are recently and frequently updated and are highly linked tend to rank blog posts very highly. Because the barrier to publication is so low in blogs, arguably much lower than that for standard web pages, these high rankings were introducing a lot of noise into online searches. The odds are that if you have searched on a controversial topic in the past year you have run across several archived blog posts. Recently, most major search engines have altered their algorithms to push blogs down in the search results. Engines that only return two results from any one site use this feature to limit the impact of blogs on the search results. Blog searching breaks down into atleast two categories: (1) information from within blogs/across blogs or (2) addresses of feeds from blogs so that you may subscribe in your aggregator (i.e. a piece of software or a remotely hosted service that periodically reads a set of news sources, such as blogs, identifies what is new, and displays them on single page). Feeds and blogs are two different concepts, but they are closely linked because most blogs have feeds and many feeds are generated by blogs. Just as in other web search tools, there are search engines and directories. At this time, blog search engines are where general search engines were before the Google Age: there are many competing smaller products, but no product dominates the scene. 157


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(d) Content management tools Content management refers to the management of valuable content throughout the useful lifespan of the content. Content lifespan will typically begin with content creation, handle multiple changes and updates, merging, summarization, and other repackaging, and will typically end with archiving. Metadata (information about the content) is used to better manage content throughout its useful lifespan. Metadata includes such information as source/ author, keywords to describe content, date created, date changed, quality, best purposes, annotations by those who have made use of it, and an expiry or “best before” date where applicable. It is also useful to include attributes such as storage medium, location and whether or not it exists in a number of alternative forms (e.g. different languages). XML is increasing being used to tag knowledge content, and taxonomies serve to better organize and classify content for easier future retrieval and use. XML (eXtensible Markup Language) gives you the ability to structure and add relevance to chunks of information (that is why many CM solutions use XML), and in theory to exchange data more easily between applications (e.g. with your suppliers, customers, and partners). However, you may all use the same words (tags), but if each of you defines and applies them differently, then we remain in the land of Babel. Common agreed schemas are essential. Keep tags with developments on the schemas and metadata standards in your field. Taxonomies are hierarchical information trees for classifying information, analogous to the library subject catalog. They can help overcome differences of language usage in different part of an organization and even clarify the use of different languages. Traditionally, taxonomy development is manually intensive in that it is created and maintained by people. The growing problem of information overload means that taxonomies are receiving significant attention. But how do you cope with the evolution of terms whose meanings seem to change from one year to the next? Automatic (or semiautomatic) classification of information objects uses software such as natural language analyzers, text summarizers, and other technology to understand some of the meaning- the concepts- behind blocks of text, and to tag and index it appropriately to aid subsequent retrieval. Automated classifiers find patterns in textual content, produce categories, and classify the content using these categories. Personal capital is a term coined to explain a divergence from the traditional notion of capital, which is an asset “owned” by an organization. In fact, the future of KM will blur the boundaries between the individual, the group or community, and the organization. KM will become a pervasive part of how we conduct our everyday business lives. Personalized KM (PKM) will gain increasing importance given the ever-increasing momentum of information overload with which we must deal. In other words, some of the key principles, best practices, and business processes of KM that have to date been focused at the organizational level will filter down to be used by individuals managing their own personal capital. 158



PKM and traditional knowledge management differ depending on whether an organizational or personal perspective is adopted. Tools for personal information management are impressive and, if you think about e-mail and portals, are already widely used. Newer tools such as blogs, news aggregators and instant messaging, represent a new toolset for PKM.

NOTES

Personal portals- which were once known as “enterprise” portals- are now focused n needs of the individual- all a person’s information and application needs harmoniously brought together into a preferred arrangement on the desktop. This is mass customization in front of your eyes. Again, the aims are laudable, but reality and theory are often miles apart. PKM brings many of the key principles of KM to bear on the personal productivity and specific work requirements of a given knowledge worker. Definitions of PKM revolve around a set of core issues: managing and supporting personal knowledge and information so that it is accessible, meaningful, and valuable to the individual; maintaining networks, contacts, and communities; making life easier and more enjoyable; and exploiting personal capital (Higgison, 2004). On an information management level, PKM involves filtering and making sense of information and organization paper and digital archives-mails, and bookmark collections. 5.3.2. Knowledge sharing and dissemination tools Although there is a distinction between communication technologies (such as telephone and e-mail) and collaboration technologies (such as workflow management), it is very difficult to draw a line between the two. Communication and collaboration are invariably intertwined, and it is quite difficult to establish where one ends and the other begins. Both types of tools have been grouped under the category of groupware or collaboration tools. Although all organizational members will make use of communication and collaboration, including project teams and work units, communities of practice will be particularly active in making use of many, if not all, of the communication and collaboration technologies described in this section. (a) Groupware and Collaboration Tools Groupware represents a class of software that helps groups of colleagues (workgroups) attached to a communication network (e.g. Local Area Networks [LANs]) to organize their activities. Typically, groupware supports the following operations: • • • • • •

Scheduling meetings and allocating resources E-mail Password protection for documents Telephone utilities Electronic newsletters File distribution 159


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The most commonly used communication technologies include the telephone, fax, videoconferencing, teleconferencing, chat rooms, instant messaging, phone text messaging (SMS), internet telephone (voice over IP or VOIP), e-mail, and discussion forums. Communication is said to be dyadic when it occurs between two individuals (e.g. a telephone call). Teleconferencing, on the other hand, may have more than two participants interacting with one another real time. Videoconferencing introduces a multimedia component to the communication channel as participants can not only hear (audio) but also see the other participants (audiovisual). Desktop videoconferencing is similar but does not require a dedicated videoconferencing facility. Simple and inexpensive digital video cameras can be used to transmit images. The visual component is especially useful when demonstrations are presented to all participants. Chat rooms are text-based but synchronous. Participants communicative with one another in real time via a web server that provides the interaction facility. Instant messaging is also real-time communication, but in this case participants sign on to the instant messaging system and they can immediately see who else is online or “live” at that same time. Messages are exchanged through text boxes. The SMS (Short Messaging System) allows text messages to be sent via a cellular phone rather than through the internet. E-mail continues to be one of the most frequently used communication channels in organizations. Although e-mail messaging is dyadic, it can also be used in a more broadcast mode (e.g. group mailings) as well as in an asynchronous group discussion mode (by forwarding previous discussion threads). Communication technologies are almost always integrated with some form of collaboration, whether it be planning for collaboration or organizing collaborative work. Collaboration technologies are often referred to as groupware or as workgroup productivity software. It is technology designed to facilitate the work of groups. This technology may be used to communicate, cooperate, coordinate, solve problems, compete, or negotiate. Although traditional technologies like the telephone qualify as groupware, the term is ordinarily used to refer to a specific class of technologies relying on modern computer networks, such as e-mail, newsgroup, videophones, or chat. Groupware technologies are typically categorized along two primary dimensions 1. Whether users of the groupware are working together at the same time (“realtime” or “synchronous” groupware) or different times (“asynchronous” groupware). 2. Whether users are working together in the same place (“colocated” or “face-toface”) or in different places (“non-colocated” or “distance”). Following are the different categories of taxonomy of groupware: 1. Electronic mail and messaging 2. Group calendaring and scheduling 160



3. Electronic meeting systems 4. Desktop video, real-time synchronous conferencing 5. Non-real-time asynchronous conferencing 6. Group document handling 7. Workflow 8. Workgroup utilities and development tools 9. Groupware services 10. Groupware and KM frameworks 11. Groupware applications 12. collaborative Internet-based applications and products

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E-mail is by far the most common groupware application (besides, of course, the traditional telephone). Although the basic technology is designed to pass simple messages between two people, even relatively basic e-mail systems today typically include interesting features for forwarding messages, filing messages, creating mailing groups, and attaching files with a message. Other features that have been explored include automatic sorting and processing of messages, automatic routing, and structures communication (messages requiring certain information). Newsgroup and mailing lists are similar in spirit to e-mail systems except that they are intended for messages among large groups of people instead of one-to-one communication. In practice, the main difference between newsgroups and mailing lists is that newsgroup shows messages to users only when they are explicitly requested (an “ondemand” service), while mailing lists deliver messages as they become available (an “interrupt-driven” interface). Workflow systems allow documents to be routed through organizations by means of a relatively fixed process. A simple example of a workflow application is an expense report in an organization: an employee enters an expense report and submits it, a copy is archived and then routed to the employee’s manager for approval, the manager receives the document, electronically approves it, and sends it on, and the expense is registered to the group’s account and forwarded to the accounting department for payment. Workflow systems may provide features such as routing, development of forms, and support for differing roles and privileges. Hypertext is a system for linking text documents to each other, with the web being an obvious example. Whenever multiple people author and link documents, the system becomes group work, constantly evolving and responding to other’s work. Some hypertext systems include capabilities for seeing who else has visited a certain page or link, or at least seeing how often a link has been followed, thus giving users a basic awareness of what other people are doing in the system. Page counters on the web are a crude approximation of this function. Another common multi-user feature in hypertext (that is not found on the 161


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web) is allowing any user to create links from any page, so that others can be informed when there are relevant links not known to the original author. Group calendars allow scheduling, project management, and coordination among many people and may provide support for scheduling equipment as well. Typical feature detect when schedules conflict or find meeting times that will work for everyone. Group calendars also help to locate people. Typical concerns are privacy (users may feel that certain activities are not public matters) and completeness and accuracy (users may feel that the benefits of the calendar do not justify the time it takes to enter schedule information). Collaborative writing systems may provide both real-time and non-real-time support. Word processors may provide asynchronous support by showing authorship and by allowing users to track changes and make annotations to documents. Authors collaborating on a document may also be given tools to help plan and coordinate the authoring process, such as methods for locking parts of the document or linking separately authored documents. Synchronous support allows authors to see each other’s changes as they make them, and usually needs to provide an additional communication channel to the authors as they work (via videophones or chat systems). Synchronous or real-time groupware is exemplified by shared workplaces, tele- or videoconferencing, and chat systems. For example, shared whiteboards allow two or more people to view and draw on a shared drawing surface even from different locations. This system can be used, for instance, during a phone call, where each person can jot down notes (e.g. a name, phone number, or map), or people can work collaboratively on a visual problem. Most shared whiteboards are designed for informal conversation, but they may also serve structured communications or more sophisticated drawing tasks, such as collaborative graphic design, publishing, or engineering applications. Shared whiteboards can indicate where each person is drawing or pointing by showing telepointers, which are color-coded or labeled to identify each person. Video communications systems allow two-way or multiway calling with live video, providing essentially a telephone system with an additional visual component. Cost and compatibility issues limited the early use of video systems to scheduled videoconferencing meeting rooms. Video is advantageous when visual information is being discussed, but may not provide substantial benefit in most cases where conventional audio telephones are adequate. In addition to supporting conversations, video may also be used in less direct collaborative situations, such as by providing a view of activities at a remote location. Chat systems permit many people to write messages in real time in a public space. As each person submits a message, it appears at the bottom of a scrolling screen. Chat groups are usually formed by listing chat rooms by name, location, number of people, topic of discussion, and so on.

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Many systems allow for rooms with controlled access or with moderators to lead the discussion, but most of the topics of interest to researchers involve issues related to unmoderated real-time communication, including anonymity, following the stream of conversation, scalability with number of users, and abusive users.

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Although chat-like systems are possible using nontext media, the text version of chat has the rather interesting aspect of having a direct transcript of the conversation, which not only has long term value, but also allows for backward reference during conversation, making it easier for people to drop into a conversation and still pick up on the ongoing discussion. (b) Wikis Wikis are web-based software that supports concepts such as open editing, which allows multiple users to create and edit content on a website. A wiki site grows and changes at the will of the participants. People can add and edit pages at will, using a Word-like screen, without knowing any programming or HTML commands. More specifically, a wiki is composed of web pages where people input information and then create hyperlinks to another page or new pages for more details about a particular topic. Anyone can edit any page and add, delete, or correct information. A search field at the bottom of the page lets you enter a key word for the information you want to find. Today, two types of wikis exist: public wikis and corporate wikis. Public wikis are developed first and are freewheeling forums with few controls. In the last year or two, corporations have been harnessing the power of wikis to provide interactive forums for tracking projects and communicating with employees over their in-house intranets. An example of wiki is wikipedia, a free encyclopedia written, literally, by thousands of people around the world. Wikis exist for thousands of topics, and if one does not exist for your favorite subject, you can start one on it and add it to the list. Wikis support new types of communications by combining internet applications and websites with human voices. A public wiki survives thanks to the initiative, honesty, and integrity of its users. Sites can be vandalized, derogatory remarks- called “flames”- can be posted, and misinformation can be published. However, a vandalized site can be restored, a flame can be erased, and information can be corrected by anyone who knows better. The community polices itself. Corporate wikis differ from public wikis in that they are more secure and have many more navigation, usage, and help features. Corporate wikis are used for project management and company communications as well as discussion sites and knowledge databases. For example, a wiki can be established for a particular project, with the project team given access to update the status of tasks and add related documents and spreadsheets. Its central location makes it easy to keep everyone informed and up to date regardless of their home office, location or time zone. A wiki is more reliable than continually e-mailing updates back and forth to the team members, it is faster than e-mail since updates are available 163


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instantly, and it is more efficient than e-mail since each team member does not have to maintain his or her own copies. Managers like wikis because they allow them to see what progress the team is making or what issues it is facing without getting involved or raising concern (e.g. a new way of project management reporting). For security reasons, corporations usually buy wiki software rather than lease space on the internet, and they set up the wiki behind the company’s firewall as a part of the intranet or as an extranet if customers or vendors are allowed access. Also, corporations look for wiki software that has authorization and password safeguards, “rollback” versions so that information can be restored to its former state, and easy uploads capabilities for documents and images. Some wikis notify users when new information is added; this is an especially nice feature for corporate projects where fast responses are required. (c) Networking technologies Networking technologies consist of intranets (intraorganizational networks), extranets (interorganzational networks), knowledge repositories, knowledge portals, and web-based shared work places. Knowledge repositories can be defined as an online computer based storehouse of expertise, knowledge, experiences, and documentation about a particular domain of expertise. In creating a knowledge repository, knowledge is collected, summarized, and integrated across sources. Such repositories are sometimes referred to as experiences bases or corporate memories. The repository can either be filled with knowledge through passive collection – where some people in the organization are scanning communication processes to detect knowledge. There are three types of knowledge repositories: 1. External knowledge repositories (such as competitive intelligence) 2. Structured internal knowledge repositories (such as research report and productoriented market material). 3. Informal internal knowledge repositories (such as “lesson learned”). A knowledge repository differs from a data warehouse and an information repository primarily in the nature of the content that is stored. Knowledge content will typically consist of contextual, subjective, and fairly pragmatic content. Content in knowledge repositories tends to be unstructured. Knowledge repositories also tend to be more dynamic than other types of architectures because the knowledge content is continually updated and splintered into varying perspectives to serve a wide variety of different users. To this end, repositories typically end up being a series of linked mini-portals distributed across an organization.

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Most repositories contain the following elements: 1. Declaration knowledge (e.g. concepts, categories, definitions, assumptionsknowledge of what)

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2. Procedural knowledge (e.g. processes, events, activities, actions, manualsknowledge of how or know-how) 3. Casual knowledge (e.g. rationale for decisions, for rejected decisions-knowledge of why) 4. Context (e.g. circumstances of decisions, informal knowledge, what is and what is not done, accepted, etc. - knowledge of care-why.) The knowledge repository is the one-stop-shop for all organizational users providing access to all historical, current, and projected valuable knowledge content. All users should be able to connect to and annotate content, connect to others who have come into contact with the content, as well as contribute content of their own. The interface to the repositories should be user-friendly, seamless, and transparent. Personalization in the form of personalized news services through push technologies, in the form of mini-portals for each community of practice, and so forth will help maintain the repository in a manageable state. To this end, use of a term such as knowledge warehouse should be strongly discouraged. The knowledge repository should instead be visualized as a lens that is placed on top of the organization’s data and information stores. The access and application of the content of a repository should be as directly linked to professional practice and concrete actions as possible. The knowledge repository typically involves content management software tools such as a Lotus Notes platform and will be run as an intranet within the organization, with appropriate privacy and security measures in place. Knowledge portals provide access to diverse enterprise content, communities, expertise, and internal and external services and information. Portals are a means of sorting and disseminating organizational knowledge such as business processes, policies, procedures, documents, and other codified knowledge. They typically feature searching capabilities through content as well as through pull technologies (intelligent agents) may exist. Communities can be accessed via the portal for communication and collaboration purposes. There may be a number of services that users can subscribe to as well as webbased learning modules on selected topics and professional practices. The critical content will have the best practices and lessons learned that have been accumulated over the years and to which many organizational members have added value. The purpose of a portal is to aggregate content from a variety of sources into a onestop-shop for relevant content. Portals enable the organizations to access internal and external knowledge that can be consolidated, analyzed, and used as inputs to decision 165


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making. Ideally, portals will take into account the different needs of the users and the different sorts of knowledge work they carry out in order to provide the best fit with both content and the format in which the content is presented (the portal interface). Knowledge portals link people, processes, and valuable knowledge content and provide the organizational glue or common thread that serves to support knowledge workers. First generation portals were essentially a means of broadcasting information to all organizational members. Today, they have evolved into sophisticated shared workplaces where knowledge workers cannot only contribute content and share content but also acquire and apply valuable organizational knowledge. Knowledge portals support knowledge creation, sharing, and use by allowing a high level of bidirectional interaction with users. Portals serve to promote knowledge creation by providing a common virtual space where knowledge workers can contribute their knowledge to organizational memory. Portals promote knowledge sharing by providing links to other organizational members through expertise location systems. Communities of practice will typically have a dedicated space for their members on the organizational portal and their own membership location system included in the virtual workspace. The portal organizes valuable knowledge content using taxonomies or classification schemes to store both structured and unstructured contents. Finally, portals support knowledge acquisition and application by providing access to the accumulated knowledge, know-how, experience, and expertise of all those who have worked within that organization. 5.3.3 Knowledge acquisition and application tools A number of technologies play an important role in how successful knowledge workers are in acquiring (i.e. understanding) and applying (i.e. making use of) knowledge content that is made available to them by the organization. E-learning systems provide support for learning, comprehension, and better understanding of the new knowledge to be acquired. Tools such as electronic performance support systems (EPSS), expert systems, and decision support systems (DSS) help knowledge workers to better apply knowledge on the job. Adaptive technologies can be used to personalize knowledge content push or pull. Recommender systems can detect similarities or affinities between different types of users and make recommendations of additional content that others like them have found to be useful to acquire and apply. Knowledge maps and other visualization tools can help to better acquire and apply valuable knowledge, and a number of tools derived from artificial intelligence can at least partially automate processes such as text summarization, content classification and content selection. E-learning applications started out as a computer based learning (CBT) and web based training (WBT) applications. The common feature is the online learning environment provided for learners. Courses can now be delivered via the web or the company intranet. The particular knowledge and know-how to be acquired can be scoped and delivered in 166



a timely fashion in order to support knowledge acquisition. E-learning technologies also greatly increase the range of knowledge dissemination because knowledge that has been captured and coded or packaged as e-learning can be easily made available to all organizational members, regardless of any time or distance constrains.

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Decision support systems are designed to facilitate groups in decision making. They provide tools for brainstorming, critiquing ideas, putting weights and probabilities on events and alternatives, and voting. Such systems enable presumably more rational and evenhanded decisions. Primarily designed to facilitate meetings, they encourage equal participation by, for instance, providing anonymity or enforcing turn-taking. Visualization technologies and knowledge mapping are good ways of synthesizing large amount of complex content in order to make it easier for knowledge workers to acquire and apply knowledge. Artificial intelligence (AI) research addressed the challenges of capturing, representing, and applying knowledge long before the term knowledge management entered popular usage. AI developed automated reasoning systems that would make use of explicit knowledge representations in order to provide expert level advice, troubleshooting, and other forms of support to knowledge workers. Expert systems are decision support systems that do not execute an a priori program but instead deduce or infer a conclusion based on the inputs provided. Natural language processing also grew out of AI research. Linguistic technologies resulted in automating the parsing (breaking into subsections) and analysis of text. Common applications today are voice interfaces or natural language queries that can be typed in to search databases. Similar AI technologies can also be applied to analyze and summarize text or automatically classify content. Many of the automated reasoning capabilities studied in AI research are encapsulated in autonomous pieces of software code, called intelligent agents or software robots (“softbots”). These agents act as proxies for knowledge workers and can be tasked with information searching, retrieving, and filtering functions. (a) Intelligent Filtering Tools Intelligent Agents can generally be defined as software programs that assist their user and act on his or her behalf: a computer program that helps you in newsgathering, acts autonomously and on its own initiative, have intelligence and can learn, improving its performance in executing its tasks. These agents are autonomous computer programs, where their environment dynamically affects their behavior and strategy for problem solving. They help users deal with information. Most agents are internet based- that is, software programs inhabiting the Net and performing their functions there.

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The following features define a true Intelligent Agent: 1. Autonomy: the ability to do most of their tasks without any direct assistance from an outside source, which includes human and other agents, while controlling their own actions and states. 2. Social ability: the ability to interact with, when they deem appropriate, other software agents and humans. 3. Responsiveness: the ability to respond in a timely fashion to perceived changes in the environment, including changes in the physical world, other agents, or the internet. 4. Personalizability: the ability to adapt to its user’s needs, by learning from how the user reacts to the agent’s performance. 5. Proactivity: the ability of an agent to take initiatives by itself, autonomously (out of a specific instrument by its users) and spontaneously, often on a periodical basis, which makes the agent a very helpful and time saving tool. 6. Adaptivity: the capacity to change and improve according to the experiences accumulated. This has to do with memory and learning: an agent learns from its user and progressively improves in performing its tasks. The most experimental bots even develop their “own” personalities and make decisions based on past experiences. 7. Cooperation: the interactivity between agent and user, which is fundamentally different from the one way working of ordinary software. Many knowledge management applications make use of intelligent agents. This range includes personalized information management (such as filtering e-mail), electronic commerce (such as locating information for purchasing and buying), and management of complex commercial and industrial processes (such as scheduling appointments and air traffic control). These tasks/applications can generally be grouped into five categories: 1. Watcher agents: look for specific information. 2. Learning agents: tailor to an individual’s preferences by learning from the user’s past behavior. 3. Shopping agents: compare “the best price for an item”. 4. Information retrieval agents: help the user to “search for information in an intelligent fashion”. 5. Helper agents: perform tasks autonomously without human interaction. In the age of computers, information, whether useful or useless, is readily available on the internet. So much data is available that we often claim to be “overloaded with information”. Having too much data can cause as much trouble as having no data, as we must sift through so much information to get what we need. Let us categorize this information overload problem into two divisions:

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1. Information filtering: we must go through an enormous amount of information to find the small portion that is relevant to us.

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2. Information gathering: there is not enough information available to us, and we have to search long and hard to find what we need. Information filtering is a particularly important function in KM because users need a way of filtering this data into a more manageable situation. Knowledge workers need information in a timely manner as it can greatly affect their success. Tasks that are redundant or routine need to be minimized by some individuals who can otherwise spend their time more productively. Some companies receive so much e-mail that they have to employ clerical workers to sift through the flood of e-mail, answering basic queries and forwarding others to specialized workers. Others use intelligent filtering software such as GrapeVine for Lotus, which reads a preestablished “knowledge chart” to determine who should receive what mail. Intelligent agent services can supplement but not replace the value of edited information. As information becomes more available, it becomes more and more crucial to have strong editors filter that information. There is so much content out there that the tools that filter content are going to be as important as the content itself. An end user, required to constantly direct the management process, contributes to information overload. But having agents to perform tasks as such searching and filtering can ultimately reduce the information overload to a degree. An electronic mail filtering agent called Maxims, which is a type of learning agent. The program “learns to prioritize, delete, forward, sort, and archive mail messages on behalf of a user”. The program monitors the user’s actions and treats these actions as a lesson on what to do. Depending upon threshold limits that are constantly updated, Maxims will guess what the user will do. Upon surpassing a degree of certainty, it will start to suggest action for the user to take. News agents are designed to create custom newspapers from a huge number of web newspapers throughout the world. The trend in this field is toward autonomous, personalized, adaptive, and very smart agents that surf the Net, newsgroups, databases, and so on and deliver selected information to their users. “Push” technology is strictly connected to news bots developments, consisting basically in the delivery of information on the web that appears to be initiated by the information server rather than by the client. Information overload is a world wide problem today, but Intelligent Agents help reduce this problem. Using them to filter the oncoming “traffic” of the “information highway” can help reduce cost, effort and time. Yet the development of Intelligent Agents is still in its infancy. As it gains in popularity and use, we can expect to see more sophisticated and better developed Intelligent Agents.

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Information studies research has examined information seeking behavior for over five decades now and can serve as an excellent theoretical basis for the study of the Internet as an information source and Intelligent Agents as mediators in this digital environment using a case study to explore how knowledge workers made use of internet based information systems, found that information studies theory provides an appropriate framework for examining internet based information seeking behaviours. The knowledge workers use the web to find information external to their organizations as part of their daily work life. A typology of different complementary modes of using the web as an information source was identified and described. (b) Adaptive technologies Adaptive technologies are used to better target content to a specific knowledge worker or to a specific group of knowledge workers who share common work needs. Customization refers to the knowledge workers “manually” changing their knowledge environment- for example, selecting user preferences to change the desktop interface, specifying certain requirements in content to be provided to them (language, format), or subscribing to certain news or listserv services. Personalization, on the other hand, refers to the automatic changing of content and interfaces based on the observed and analyzed behaviors of the intended end user. For example, many MS office applications offer the option of dynamically reordering popdown menu based on frequency of usage (the ones used most often will be displayed on top). One way of automatically personalizing knowledge acquisition makes use of recommender systems. Recommendations regarding content that is likely to be considered useful and relevant by a given knowledge worker may be based on a user profile of that knowledge worker (e.g. with themes checked off), or the recommendation may be based on affinity groups. Affinity groups make use of similarity analysis of users in order to develop groups of individuals who appear to share the same interests. Amazon, for example, uses affinity groups when, after ordering a book online, visitors to the site are provided with information on related books that others who have bought the same book have also purchased. Communities of practice are affinity groups to some extent, and personalization technologies are often used to target or push certain types of content that are of interest to a given community. Community profiles ca be established just as individual profiles and can be used in the same moment in order to better adapt content and interfaces to the community members. 5.3.4. Strategic implications of KM tools and techniques Tools and techniques are a means and not an end in themselves. First, the business objectives must be clearly identified, and then a consensus must be reached on priority 170



application areas to be addressed. For example, an initial KM application will typically be some form of content management system on an internally managed intranet site. This is a good building block for subsequent application such as yellow pages or expertise finders and groupware tools to enable newly connected knowledge workers to continue to work together.

NOTES

A number of the techniques presented here address the phenomenon of emergence that can help discover existing valuable knowledge, experts, communities of practice, and other valuable intellectual asses that exist within an organization. Once this is done, the intellectual assets can be better assessed, leveraged, and employed. The KM tools and techniques have an important enabling role in ensuring the success of KM applications. 5.4. KNOWLEDGE MANAGEMENT AND MEASUREMENTS “Measurement is the assignment of numerals to things according to any determinative, non-degenerate, rule”. Determinative means the constant assignment of numerals given constant conditions. Non-degenerate means allowing for the possibility of assignment of different numerals under varying conditions. In knowledge management measurement, we are trying to select and/or formulate those concepts useful in measuring and influencing knowledge management performance. Measuring knowledge management (KM) is not simple. Determining KM’s pervasiveness and impact is analogous to measuring the contribution of marketing, employee development, or any other management or organizational competency. It is nonetheless a necessity if KM is to last and have significant impact in an organization. American Productivity and Quality Council (APQC) focused on how some of the most advanced early KM adopters implement a knowledge management initiative, mobilize resources, create a business case, and measure and evolve their KM programs. This has helped to identify measurement approaches and specific measures in use, and how impact measures and is impacted by the evolution of KM. The need for measurement of KM follows a bell curve pattern through the life cycle of a business life cycle. In the earliest stages of knowledge management implementation, formal measurement rarely takes place, nor is it required. As KM becomes more structured and widespread and companies move into stages two, three, and four, the need for measurement steadily increases. As KM becomes institutionalized—a way of doing business—the importance of KM-specific measures diminishes, and the need to measure the effectiveness of knowledge-intensive business processes replaces them.

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Figure 5.1 Knowledge Measurement Stage 1 – Enter and Advocate Stage The fire to manage knowledge starts with the spark of inspiration. There has to be a new source of energy or interest to cause KM to appear in the option set for the organization. Someone must become inspired with the vision of what it would be like if the organization could effectively support human knowledge capture, transfer, and use. Energized by his or her vision, this champion begins to search for opportunities to share the vision with others and to find opportunities to demonstrate the value of KM to the organization. The central task for the champion at this stage is to create a vision that inspires others to join in the exploration of how managing knowledge might contribute value to the enterprise and its people. Measures Appropriate for Stage 1 The value of embarking on the KM journey needs to be understood by members of management—more in theory at this stage than in quantitative numbers. The most effective way of convincing them may be to find the greatest areas of “K-spots” within your organization. Find redundant efforts, discover areas where knowledge is lost, and find points of frustration in your employee base. It is important to expose the need for knowledge management at this stage. Interviewing key stakeholders helps uncover KM needs and exposes areas of lost time, effort, and therefore money. Making comparisons with similar industries that have successfully implemented KM also can convince skeptics. If the competitor has gained recognition for its KM efforts and has seen its productivity jump and operating costs plummet, then the organization implementing KM likely found a good candidate to use as proof of KM’s power.

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Stage 1 is the time for advocating the potential of KM to the stakeholders and after that more concrete measures will be necessary.

NOTES

Stage 2 – Explore and Experiment Stage During the second stage of KM implementation, a practical definition of knowledge management is formulated within an organization and consideration of its applicability is made. The movement can start from several isolated, grassroots knowledge-enabling activities and develop into a cross-corporate vision and strategy. The development of several successful knowledge-enabling practices and pilots can be the catalyst to draw positive senior management attention. Further, it allows organizational sponsors to realize and consequently support the formation of a cross-functional team that can bring alignment. At this point in the process, negotiations for some corporate funding can add additional resources to the scarce and limited funds from the local teams. Toward the end of this stage, the pilots’ focus begins to center on specific knowledge management ideas and principles in order to demonstrate concepts and capabilities. Measures Appropriate for Stage 2 The emergence of a need for measurement in Stage 2 is felt as interest about KM escalates in several parts of the organization. These measures can appear in three main categories: anecdotal (war stories, success stories, etc.), quantitative (growth), and qualitative (mainly extrapolation from anecdotal). It is appropriate to begin this section by identifying what should not be measured in Stage 2. Since most management initiatives are driven by financial results, the instinct is to identify quantifiable financial measurements such as productivity increases, increased sales, reduced overhead, etc. Knowledge management will generate these financial measurements and others, but not in the early stages. Measurement of financial returns or results should not be undertaken at this point except as byproducts of other concurrent efforts. Simply stated, if the organization is measuring for financial returns when your organization is at this particular juncture, then it is measuring the wrong thing. Focus should be on meaningful measures that concentrate on exploring the various opportunities in the organization for implementing knowledge management practices, developing the organization’s knowledge management strategies, measuring the progress toward organizational awareness, and experimenting with different knowledge management concepts and concentrate on developing and selling the concept and then measure against the plan. Examples of Stage 2 Measures Simple measures are critical at this stage. Examples of potential measurements include:

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Measure for Progress: Measure the progress you make in developing and growing sponsorship and support from top management. (a) Measure the Gap As part of your early work in Stages 1 and 2, you should have completed an assessment or knowledge map of your organization to determine what practices you currently have in place and what you are missing. As part of this assessment, you should attempt to identify what, if any, measurements are currently being used. You will at some point need to determine the value of that measurement and whether it can be used going forward. The existing measurement can, at a minimum, provide you with a benchmark for future measurements. (b) Measure Against a Benchmark Benchmarking with other organizations can be a persuasive tool and can lead to executive sponsorship. Since most successful KM initiatives are grassroots or organizational (department/division) and not corporate (top-down) in origin, measurement within the various division/department is crucial. (c) Measure Your Cultural Readiness It is important at this stage to build the foundation to develop a knowledge-sharing culture. Critical practices that foster employee information exchange, teamwork, collaboration, and trust development can be built upon through crediting the contributors. Teams that operate in this manner, their norms, practices and insights needs to be observed and incorporated into other teams. Document stories to encourage role model behavior. Stage 3 – Implementation Stage This stage signals the formal implementation of a knowledge management initiative. The goal of Stage 3 is to provide evidence of knowledge management’s business value by conducting pilots and capturing lessons learned that can be transferred and used to help the organization better implement KM on a larger and expanding scale. The framework for communities of practice begins to be formalized at this stage, and funding and support are derived from a mix of central resources as well as the donation of time, people, and money from within organizations that are enthusiastic about enabling knowledge sharing. Measures Appropriate for Stage 3 There is a convergence at Stage 3 of the three main categories of measurement that exist in the early stages of KM implementation: anecdotal, quantitative, and qualitative. The degree of rigor and refinement becomes more defined and focused on business strategy in Stage 3. The key here is to begin to ensure that direct business value is perceived by the organization as a result of the knowledge-enabling projects. It is important to establish a

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mechanism to capture the hard and soft lessons learned in the knowledge management pilots, as these will be the building blocks for the later KM stages.

NOTES

Having a predefined taxonomy on the classification of lessons learned can be helpful in developing conclusions and identifying areas desirable for replication throughout an organization. In addition, during the acceleration of knowledge management scale-up, establishing measures for the various components of a knowledge management initiative is beneficial. These measures include process dimensions, culture dimensions, content dimensions, information technology dimensions, and people dimensions. Examples of Stage 3 Measures a. Measure the Business Value: Both the hard and soft business value derived from each pilot should be documented. Then beginning should be made to map measurements of specific business goals, such as improved clock speed. This does not necessarily need to be rigorous at this point. Extrapolation of anecdotal measurements into more solid quantifiable measurements occurs. Can the pilot results be duplicated in other parts of the organization? Time saved equals direct labor cost, which is easy to figure. Effort needs to be put into determining the ancillary costs associated with time savings. Some potential areas are resource redistribution; support staff cost reductions, and improved time to market. b. Measure the Retention of Knowledge: Measure the amount of information contributed to the knowledge base over time against retrieval and reuse. Quantifiable measurements are not enough; they must be balanced with qualitative data to ensure an accurate, full picture. Unlike in previous stages, the number of hits to a Web site is not good enough. Specific measures and issues to be considered may include the following: •

Time spent per hit. This can reveal if individuals entering the site are actually reviewing its content (indicates quick review and rejection vs. what would constitute an individual actually digesting some content). This would have to be correlated with the number of individuals using it for an extended period of time and repeat users.

•

Are the IP addresses those of repeat users? The intent for this measurement is to track repeat customers. Repeat customers indicate two things—either specific information is of repeated use to them or they find value in the additional information continually added to the application.

•

How often is a site visited?

•

What percentage of total hits represents repeat users? Value can be measured by repeat business.

•

What is the threshold for indicating a repeat user is a steady customer? Someone may sample a site several times but will stop visiting if they fail to get the results they seek.

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c

Measure the Cultural Impact: In Stage 3, the issues surrounding the potential for measuring the cultural side of knowledge management need to be addressed. Considerable effort needs to be placed on determining:

• • • •

the types of measurements the potential value of the measurements the cost for measuring vs. the value of measuring processes

In selecting measures, consideration should be given to if and how the cultural side of KM can be measured in Stage 3. (i) Anecdotal stories. As stated earlier, stories can form the basis for extrapolation of quantitative data. This is not necessarily the only or best means of using anecdotal measurements, but considering the intrinsic value of the anecdote can be important. (ii) Performance review. Another means of measuring cultural impact is through the performance review process. Individuals can be rated by their peers (360-degree feedback) on three major knowledge-sharing points listed below. This can be implemented in Stage 3 because there are formal (if only pilot) applications in place. As part of these applications feedback on the usefulness of the knowledge provided is essential. 1. Do they share their knowledge in an open and constructive way? 2. Do others find their knowledge of value and use it? What results are gained from it? 3. Do they use others’ knowledge and apply it to improve operations? This can be measured somewhat by traditional business measurement tools. (iii) Public and private recognition and rewards for individuals and teams: Though an organisation advocates team building and sharing of knowledge, incentives for individual contributions are still required. A reward or recognition system properly implemented can provide quantitative measurements. (iv)Measure the Effectiveness of Sharing Communities: Document the effectiveness of communities of practices (CoPs). Based on the findings, determine essential elements that contribute to coherent and effective CoP. Draw correlations against CoPs that have not been as successful. Extract lessons learned and best practices from these correlations and use them to build new CoPs and improve existing ones. (v) Measure the Ownership of Capture and Compilation: What are the costs involved in capturing information in a usable manor? This includes not only the capturing but also the indexing. If the information is not retrievable it is of little value. Quantifiable measurement of the time required to capture the information in a usable manner is applicable. This can be critical in evaluating the impact of a pilot project. Is the cost of the capture process too high in comparison to the value of the captured information or knowledge? 176



Consider storytelling as an example. Here are some of the factors to be considered. •

Creating the storytelling environment (either electronic production or live storytelling)

•

If live, what is the time commitment of participants (storyteller and audience)?

•

If electronic, what are the production costs?

•

Are the storage and distribution costs insignificant?

•

How much responsibility is there on the individual to capture his information in a usable manor? This includes not only the capturing but also the indexing. If the information is not retrievable, it is of little value.

•

Does the measurement of capture and compilation warrant effort?

NOTES

(vi) Measure Project Management Effectiveness and Intended Results: Successful pilots will contribute to building organizational support and future funding. To ensure that projects are managed effectively, it is beneficial to track the projects. Was a formal methodology employed? Was a time line established and progress tracked? Were project objectives and expectations clearly stated and measured? Measure the performance of the pilots themselves against the intended results or hypothesis. Measurements can be quantitative, qualitative, or anecdotal. Measuring cost in your pilots can provide critical information for determining program direction and strategy. If properly set up, measurements can enable a KM team to rethink its priorities in an efficient and timely manner, allowing for shifting resources to strengthen the potential for success. Can the capturing of lessons learned from your pilots be used for measurements? The obvious answer is yes. An organization can quantify these in two basic ways: number submitted and number referenced. •

A qualitative measurement can be reached through a feedback measurement system such as Eureka’s thumbs-up or -down method of capturing the value of a tip to a user. Other measurements can be made using the number of times a lesson was used or through a feedback system allowing the capture of users’ comments.

Stage 4 – Expand and Support Phase When an organization reaches Stage 4, KM has proved valuable enough to be officially expanded to become part of the organization’s funded activities. Demand for KM support by other parts of the organization tends to be high, providing additional evidence of its value. Pilot results are an added benefit. High visibility and the authority to expand are a mixed blessing; the added visibility of costs and resources devoted to KM will require more formal business evaluation and ROI justification and unless unforeseen factors derail the efforts, KM is on its way to being considered a strategic and necessary competency. Measures Appropriate for Stage 4 Since organizations at Stage 4 are undertaking multiple projects in diverse areas of the business, it becomes necessary to evaluate the fitness of the knowledge areas in relation to the whole organization. Evaluating a knowledge area project might require examining 177


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many areas of fitness that, in aggregate, help the organization determine whether the projects in its KM portfolio are of high impact and beneficial to the success of the company. Project criteria may include: •

Proficiency. Has a process become world-class because of KM, or has it made only mediocre improvement?

•

Diffusion. Has KM been properly executed? Is the project and knowledge managed well? Is it well understood?

•

Codification. Because codifying knowledge is expensive, should the organization limit that? Is that limitation visible and understood?

•

Openness for combination/innovation. Is the knowledge described in jargon that no one understands? Is the knowledge base open to other disciplines? Does the project generate questions to the organization to help it grow?

Justification measures can be difficult when the organization is trying to decide whether to adopt KM as part of the ongoing corporate strategy. The question of measurement must often be restated at this stage. The organization has to not only measure how knowledge area projects perform but also evaluate how it feels the business key indicators are linked to the knowledge areas. This can be easier if the business owner decides what needs to be improved through a project before embarking on it. When the improvements occur, he or she can communicate the causal linkages between where the business started and where it ended up because of the concentration on creating a viable knowledge project. At this stage, it is important to tap into the values of the organization and determine whether a culture shift is occurring. Personal performance reviews can be a useful avenue to determine whether managers support knowledge sharing and give employees a chance to show their ability to share. Then questions can be asked of employees to determine whether management really does support knowledge sharing. Targeted questions such as “How do you support creation and innovation?” can also help determine employee mindset. Although most corporate KM programs have been well-established and “proven” by Stage 4, it is still important to show that KM is working and will work going forward. To estimate ROI, add the costs of a community (including labor, meetings, and facilities) and then define how much effort is spent on KM by knowledge management experts. Then decide how much effort has been saved by sharing solutions in the community. Another way to approach ROI estimation might be by looking at sub communities and their generation of solutions in terms of community projects. If a group needs a solution and embarks on a knowledge-creation effort, determine how much has been saved in time to market, competitive positioning, etc.

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Stage 5 – Institutionalizing Knowledge Management

NOTES

In some ways, Stage 5 is the continuation of Stage 4 to its logical conclusion of full enterprise-wide deployment. However, Stage 5 differs from Stage 4 in three fundamental ways: •

It does not happen unless KM is embedded in the business model.

•

The organization structure must be realigned.

•

Evidence of knowledge management competency becomes part of the formal performance evaluation.

Sharing and using knowledge become part of the organization’s “way of doing business” as well as an expected management competency. In the relatively young arena of KM, only a few organizations have reached this stage. As in Stage 4, Stage 5 measures are not used to prove value. They are used to check progress and monitor the continued evolution of the culture. KM can no longer be called an initiative or project at this stage, but becomes the backbone on which the organizational business processes are built on. 5.5. KNOWLEDGE MEASUREMENT TECHNIQUES This section outlines a non-financial measurement system for intangible assets. 5.5.1. Intangible asset measurement It is widely accepted that intangible (knowledge or intellectual) assets are the major drivers of corporate value and growth in most economic sectors, but the measurement of these assets has eluded so far managers, accountants, and financial analysts valuing investment projects. The value of knowledge or the intellectual capital of any organization and the efficiency and performance of the associated KM systems cannot be measured by the conventional tools and techniques in existence. There is no difference between monetary measures and other measures though monetary measurement is objective and guided by definitions and standards. As of today, there exists no system that uses money as a measurement tool. Most organizations measure some of their intangible assets and they use non-monetary measures for particularly measuring operational efficiency. Manufacturing companies measure “output per hour” as a basis. Hospital and hotel measure bed utilization, school measure student’s performance in terms of marks, employee satisfaction and retention as a measure of competence by most business organizations. How are The Intangibles Metrics Computed? Why measure intangible assets? Evaluating profitability and performance of business enterprise, by say, return on investment, assets or equity (ROA, ROE) is seriously flawed since the value of the firm’s major asset— intangible capital—is missing from the 179


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denominator of these indicators. Measures of price relatives (e.g., price-to-book ratio) are similarly misleading, absent the value of intangible assets from accounting book values. Valuations for the purpose of mergers and acquisitions are incomplete without an estimate of intellectual capital. Resource allocation decisions within corporations require values of intangible capital. These and other uses create the need for valuing intangible assets, in practically all economic sectors. Intangible (knowledge) assets, such as new discoveries (drugs, software products, etc.), brands or unique organizational designs (e.g., Internet-based supply chains) are by and large not traded in organized markets, and the property rights over these assets are not fully secured by the company, except for intellectual properties, such as patents and trademarks. The risk of these assets (e.g., drugs or software programs under development not making it to the market) is generally higher than that of physical assets.1 Accordingly, many, particularly accountants and corporate executives, are reluctant to recognize intangible or intellectual capital as assets in financial reports, on par with physical and financial assets. While such attitude concerning balance sheets may be understandable, it does not satisfy the need to seek information about and value of intangible assets. Some have attempted to gauge the value of intangible assets from the difference between the company’s capital market value and its book value (the balance sheet value of net physical and financial assets). This approach is unsatisfactory because it is based on two flawed assumptions: (a) that there is no mispricing in capital markets, and (b) that balance sheet historical values of assets reflect their current values. The market-minus-book approach to valuing intangibles is also unsatisfactory because it is circulatory. One searches for measures of intangibles value in order to provide new information to managers and investors. What is the use of a measure (market-minusbook) that is derived from what investors already know (market and book values)? There is obviously a need for a different approach to estimating the value of intangible assets. Some of the approaches are as follows: Direct Intellectual Capital methods (DIC). Estimate the rupee-value of intangible assets by identifying its various components. Once these components are identified, they can be directly evaluated, either individually or as an aggregated coefficient. Market Capitalization Methods (MCM). Calculate the difference between a company’s market capitalization and its stockholders’ equity as the value of its intellectual capital or intangible assets. Return on Assets methods (ROA). Average pre-tax earnings of a company for a period of time are divided by the average tangible assets of the company. The result is a company ROA that is then compared with its industry average. The difference is multiplied by the company’s average tangible assets to calculate an average annual earning from the

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Intangibles. Dividing the above-average earnings by the company’s average cost of capital or an interest rate, one can derive an estimate of the value of its intangible assets or intellectual capital.

NOTES

Scorecard Methods (SC). The various components of intangible assets or intellectual capital are identified and indicators and indices are generated and reported in scorecards or as graphs. SC methods are similar to DIS methods, expect that no estimate is made of the rupee-value of the Intangible assets. A composite index may or may not be produced. 5.5.2. Intangible assets monitor Intangible asset monitor is a method for measuring intangible assets and a presentation format that displays a number of relevant indicators for measuring intangible assets in a simple manner. The choice of indicators depends on the company strategy. The format is particularly relevant for knowledge organizations. The intangible assets monitor appears similar to balanced score card, however, there are significant differences between the two. The intangible assets monitor can be integrated in the MIS. The most important areas to cover are growth/renewal, efficiency, and stability. The purpose is to get a broad picture: so one or two indicators in each category could be designed. Normally, organizations are interested in indicators that indicate change, i.e. growth, and renewal as well as efficiency and stability measures. Efficiency and effectiveness Although often used as synonyms, efficiency and effectiveness measure different things. Efficiency measures utilisation, i.e. how well an organization is using its capacity, regardless of what it produces. A criterion of efficiency, often used by consultancy firms is billable time; time billed to clients, as a proportion of time available. This measures how much time consultants are paid for. It is a simple and good indicator of short term profitability because it measures capacity usage, but it says nothing about what the consultants accomplish in that time. The needs of the various parties concerned may, of course, differ; shareholders are interested in dividends; customers are interested in service levels, and quality. Firms should, therefore, employ different efficiency measures, for different audiences. ROI (return on invested capital) is a criterion of efficiency popular in financial circles. It measures profit generated by the capital invested in a company, or a project and is thus a very important indicator of efficiency, to both creditors and the owners of the invested capital. For shareholders, the most important figure is what they earn after tax, in the form dividends on the capital they have put into the company; the return after tax on their own equity, often shortened ROE. The management must also track the return on the firm’s total capital, and on particular investment projects, so that they can control their allocation of capital. Unfortunately, this technique cannot be applied to intangible assets, so various income statements, and nonmonetary measurements, must be used instead to calculate efficiency. 181


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Effectiveness measures how well an organization is satisfying the need of those it serves. It is more difficult to measure also because one must often go outside one’s own organization. Measuring customer satisfaction for instance, an important indicator of an organization’s effectiveness relies on customer polls. Therefore effectiveness is seldom measured. Even if it is not practically possible to measure effectiveness, it is never-the-less valuable to think in effectiveness terms. What gives the most revealing picture of performance? To focus on the costs of people or on the revenues they bring in? Cost focus is efficiency oriented, revenue focus is effectiveness oriented.

Intangible Assets External Structure Indicators

Indicators of Growth Organic Growth.

Internal Structure Indicators

Competence Indicators

Indicators of Growth Investment in IT Investments in Internal Structure

Indicators of Growth Competence Index Number of Years in the Profession. Level of Education. Competence Turnover.

Indicators of Renewal/Innovation Indicators of Organization Enhancing Renewal/Innovation Customers. Image Enhancing Customers Proportion of new Sales to new customers products/services New processes implemented

Indicators of Efficiency/Utilization Profitability per Customer. Sales per Customer. Win/Loss Index.

Indicators of Efficiency/Utilization Proportion of Support Staff

Indicators of Renewal/Innovation Competence-Enhancing Customers. Training and Education Costs. Diversity Indicators of Efficiency/Utilization Proportion of Professionals. Leverage Effect. Value Added per Employee. Value Added per Professional. Profit per Employee. Profit per Professional.

Indicators of Risk/Stability Indicators of Risk/Stability Satisfied Customers Index. Values/Attitudes Index Indicators of Risk/Stability Proportion of Big Professionals Turnover. Age of the organization. Customers. Relative Pay. Support Staff Turnover. Age Structure. Seniority Rookie Ratio. Devoted Customers Ratio. Seniority. Frequency of Repeat Orders.

Figure 5.2 Intangible Assets Monitor

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5.5.3. IC Rating

NOTES

IC rating can be said to constitute value creating factors not shown in traditional balance sheets, but which are of critical importance to a company’s long-term profitability. IC Rating is a way of measuring intellectual capital from a new perspective and with a new approach focus on the assets that in fact decide the ability of knowledge based companies to create value for its interest groups. An IC Rating provides management with a foundation for optimizing the competitiveness of the organization by functioning as: •

A foundation of a modern business control system with clear and measurable goals for maximizing future profitability. This analysis can be repeated in order to measure the goal achieved.

•

A basis for improvement and change activities which can be used on both management and operational levels. The area of improvement can be identified after which decisions about changes can be made.

•

A structured image of value creating assets that can be used in market communication (investor relations, annual reports) as well as within the organization where the tool creates a new basis and a new language for internal aspects important to business activity.

5.5.4. Balanced Scorecard Balanced Scorecard (BSC) is a management system devised by Robert Kaplan of Harvard Business School and David Norton which uses a ranch of “leading and lagging” indicators for evaluating the progress of a business towards fulfillment of its strategic goals. A company’s performance is measured by indicators covering four major focus perspectives: (1) financial perspective; (2) customer perspective; (3) internal process perspective; and (4) learning perspective. The indicators are based on the strategic objectives of the firm. The BSC is a proven approach to strategic management that imbeds the long-term strategy into the management system through the mechanism of measurement. The BSC translates vision and strategy into a tool that effectively communicates strategic intent and motivates and tracks performance against the established goals. A vision describes the ultimate goal and a strategy is a shared understanding about how that goal is to be reached. The BSC provides a medium to translate the vision into a clear set of objectives. These objectives are then further translated into a system of performance measurement that effectively communicates a powerful, forward-looking, strategic focus to the entire organization. In contrast to traditional, financially based measurement systems, the BSC glues an organization’s focus on future success by setting objectives and measuring performance from four distinctive perspectives. The learning perspective directs attention to the basis of 183


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all future success – the organization’s people and infrastructure. Adequate investments in these areas are critical to long term success. The development of a true learning organization supports success in the next BSC perspective, the internal process perspective. The internal process perspective focuses attention on the performance of the key internal processes which drive the business. Improvement in internal processes now is a key lead indicator of financial success in the future. However, in order to translate superior processes into financial success, companies first please their customers. The customer perspective considers the business through the eyes of a customer, so that the organization retains a careful focus on customer needs and satisfaction. Finally, the financial perspective measures the ultimate results that the business provides to its shareholders. Together, these four perspectives provide a balanced view of the present and future performance of the business. Business intelligence and Internet technology are the foundations of BSC systems. BI systems take ground-level data – such as delivery time, sales figures, length of customer service calls, etc. – and translate into a company-wide BSC summery which keep track of the successful and unsuccessful goals of the organization. Internet technology makes the system accessible to anyone in the business from anywhere. Organizational implementation A company initiates a BSC system by setting strategic goals in each of the four quadrants described below: • • • •

Customer satisfaction Internal business processes Learning Financials

It then assigns metrics that can be measured to determine whether the business is meeting its goals. The grades are based on metrics that put measurable value on factors usually considered too vague to quantify. The loaded BI system can extract that data from existing systems, process it, determine whether the company is meeting customer satisfaction goals, and issue a grade on the corporate scorecard. In the ultimate BSC environment, there are different scorecards for everyone in the business, and for the business itself, universally accessible via the organizational intranet on the Internet. This makes the BSC a potent system for communicating strategic goals. Executives can view a scorecard on their desktops that displays business’s strategic goals. If they require information about a goal, they can drill down and obtain more minute details. Much of the detail comes from individual employees, who enter data and notes about what is happing on the front lines into personalized scorecards. These scorecards also tell them hoe their performance matches their goals.

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Measurement

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Measurement is a critical component of any management system. Most managers recognize its vital role in communication, incepting and tracking the achievement of an organization’s strategy. Despite this recognition, most organizations do not operate with a measurement system that adequately fills all these roles, because they consist of many financial indicators. Today’s measurement systems focus organizations on past performance and encourage a short-term view of strategy, failing to provide the long-term strategic management capabilities that today’s organizations need. The BSC has been quickly accepted by the business world; it is easy to see the value of a focused set of performance measurements. A good BSC should convey the details of the organization’s strategy. The following three criteria help to determine if the performance measures are in tune with the organizations strategy. 1. Cause and Effect Relationships: Every measure selected for a BSC should be part of a chain of cause and effect relationships that represent the strategy. 2. Performance Drivers: Measures common to most companies within an industry are known as “lag indicators”. Examples include market share or customer retention. The drivers of performance (known as “lead indicators”) tend to be unique because they reflect what is different about the strategy. A good BSC should have a mix of lead and lag indicators. 3. Financial Linkage: Most organizations are preoccupied with goals such as quality, customer satisfaction and innovation. While these goals are frequently strategic, they also must translate into measures that are ultimately linked to financial indicators. Organizational BSC design There are two essential ingredients to the successful design of a balance scorecard. 1. An architect who has a framework, philosophy, and a methodology for designing and developing the new management system. 2. A client who will be totally engaged and assume ultimate ownership of the project, understanding that the person must live with the results long after the architect withdraws. The client is the executive team of the business organization. The BSC and the management system which will be built around it are, ultimately, the responsibility of the executive team. Without their active sponsorship and participation, a BSC project should not be attempted, because it is bound to fail. Methodology: The approach should include the capture and translation to measurement of an organizational strategy across a wide variety of strategic and operational situations. The following approach can be employed in designing a BSC measurement system.

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Measurement architecture: An organization must develop a distinct business strategy. A business strategy and a BSC that describes it are not random. The architecture of a BSC has several dimensions which must be incorporated into Scorecard design. A good design process will recognize these dimensions and provide a framework to guide the architect and the executive team in their thinking about the strategy. There are frameworks that describe that describe the strategy and represent the foundation on which a complex design is based. Whether operating a growing, mature, or maturing business, executive teams use this framework to anchor their financial objectives. Similar frameworks for the customer and the learning perspectives give both the architect and the clients a common ground from which to consider the setting of strategic objectives. Development of strategic objectives: In general, the management groups in well managed organizations lack a shared understanding about the overall strategy of the organization and the relative roles of different groups within the organization keeps the team agreeing on priorities. The second step of the development process is designed to build consensus among the members of the executive team around the long-term strategic priorities of the organization. To achieve this goal, each executive team member is interviewed individually to capture his or her implicit and explicit strategies for the business. The personal visions are then synthesized into feedback that is reviewed at an executive workshop. During this session, the executive team learns about where there is and is not a consensus about their strategy and discusses unresolved issues. Ultimately, a coherent group vision for the organization emerges in the form of 10 top priority objectives. Design measures: With the prioritized strategic objectives agreed upon by the executive team, the next step is the selection of measures to track the achievement of these objectives. Sub-team working sessions focus on the development of measures for a subset of the objectives, finalizing the working of objectives and searching for measures appropriate for tracking each objective. At the end of this step, the sub-teams synthesize their recommendations into a united “strategic story” in consonance with the strategic objectives and measures; thereby concluding the design of the BSC measurement system. Implementation plan: For a BSC measurement system to create value, it must be integrated into the management system of the organization. The final step of the process entails three primary tasks: 1. Identifying the current practices in various management processes 2. Evaluating opportunities for integrating the BSC into the management process 3. Developing an implementation plan This step typically reviews the client’s approach to data reporting and review, management meetings and decision-making, strategic learning, strategic communication, personal objective setting, planning and budgeting.

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Performance measurement: A performance measurement system enables the organization to ensure its tracking along an appropriate path as it moves from its current state to a future state. The vision and mission statements are the foundation of an effective performance measurement system. With the direction and a reason for existing in place, quantitative objectives can be defined to determine progress towards the vision. Several measurement concepts should be considered as the measurement system is designed: the balanced control panel, linking the vision to individual and group activities, and the PDSA cycle as a control system. The BSC tightly integrates the key business measures into a few manageable metrics, so that management has the necessary data to quickly assess the health of the organization along several fronts. It is characterized by a control panel similar to that found in automobiles or airplanes. Managers leading the organization use the gauges on the control panel to assess and modify action over time. The BSC has four basic measurement areas: 1. 2. 3. 4.

NOTES

Customer connectivity Internal process efficiency and effectiveness Individual and group innovation and learning Financials.

The BSC provides a holistic view of the short and long-term health of the organization, by having metrics established in each of the basic elements with financial performance being the ultimate lagging indicator. 5.5.5. Implementation Barriers Even with the best known tools and techniques for installing a measurement system, many attempts fail. Here are the some of the barriers to implementation of measurement systems. 1. Lack of leadership at the top 2. Abandoning the effort of measurement when initial problem in execution is felt 3. Resistance from individuals from the fear of specific and measurable objectives to achieve 4. Fear of cultural change in organization owing to the measurement system 5. Non-availability of data and its integrity while measurement 6. Unnecessary variation to the measurement system due to varying formats between operation and between review periods 7. Standardization itself would be a factor contributing to resistance among employees. 5.6. KNOWLEDGE AUDIT The knowledge audit (K-Audit) is a systematic and scientific examination and evaluation of the explicit and tacit knowledge resources in the company. The K-Audit investigates and analyses the current knowledge-environment and culminates, in a diagnostic 187


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and prognostic report on the current corporate ‘knowledge health’. The report provides evidence as to whether corporate knowledge value potential is being maximized. In this respect the K-Audit measures the risk and opportunities faced by the organization with respect to corporate knowledge. Knowledge audit is a systematic examination and evaluation of organizational knowledge health, which examines organization’s knowledge needs, existing knowledge assets/resources, knowledge flows, future knowledge needs, knowledge gap analysis as well as the behavior of people in sharing and creating knowledge. In one way, a knowledge audit can reveal an organization’s knowledge strengths, weaknesses, opportunities, threats and risks. A knowledge audit should also include an examination of organization’s strategy, leadership, collaborative, learning culture, technology infrastructure in its various knowledge processes. In order to transform an organization into a learning organization and ensure an effective knowledge management strategy, a knowledge audit should be conducted, which will provide a current state of knowledge capability of the organization and a direction of where and how to improve that capability in order to be competitive in this fast changing knowledge era. The first stage in adopting a knowledge strategy is performing an audit of existing data, information and knowledge contained within the organization. This section will cover four main areas of the knowledge audit: The aims and objectives of the audit. The key tasks involved. Process mapping. The audit outcomes. 5.6.1. Aims and objectives There are three broad aims of a knowledge audit: • • •

Leveraging the organisation’s knowledge. Creating new knowledge or promoting innovation. Increasing collaboration and hence enhancing the skill level of employees.

The objectives of a knowledge audit are: 1. Study and develop a deeper understanding of existing communities (groups that share resources, provide support and show reciprocity) content (forms and combinations of words, images and pictures) and conversations (exchanges of sentiments, observations, opinions, or ideas). 2. Identify opportunities to add value to current communities, content and conversations. 188



3. Develop a knowledge management strategy that delivers on the identified opportunities.

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4. K-audit helps an organization to clearly identify what knowledge is needed to support overall organizational goals and individual and team activities. 5. It gives tangible evidence of the extent to which knowledge is being effectively managed and indicates where improvements are needed. 6. It explains how knowledge moves around in, and is used by, that organization. 7. It provides a map of what knowledge exists in the organization and where it exists, revealing both gaps and duplication. 8. It provides an inventory of knowledge assets, allowing them to become more visible and therefore more measurable and accountable. 9. It provides vital information for the development of effective knowledge management programmes and initiatives that are directly relevant to the organization’s specific knowledge needs and current situation. 10. It helps in leveraging customer knowledge. Most commonly, knowledge audits result in the following outcomes: • Development of a knowledge repository; • Forming and nurturing communities of practice. However, there are many others to explore. 5.6.2. Key tasks It is possible to separate a knowledge audit into seven key tasks: Create a data, information and knowledge systems database: This involves creating an inter-relational database with tables for: •

each section of the organization;

•

data, information and knowledge repositories

•

types of communication, such as, face-to-face, analogue and digital systems.

1) Identify areas of organizational quick gain: This can be used as a way of demonstrating to key players that you are committed to high levels of achievement in the short as well as the medium and long-term. 2) Perform process mapping: It is important to ‘map’ key processes as well as key players within the organization. There are a number of software tools that can be used for such mapping including MS Project and MS Visio. It is possible to take mapping a stage further by using XML image maps to illustrate processes over Intranets, Internets and extranets. 3) Organise focus groups: The composition of such groups needs to be balanced between differing levels of seniority, front/back office and differing locations. Focus 189


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groups are an important means of keeping on track. Well-balanced focus groups can be used again over time.

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4) Design and pilot knowledge needs survey: The importance of a pilot project is that it sets an achievable object in the foreseeable future, say, six to twelve months. Senior managers are often very keen on pilots as, if they fail to work, resources used are limited and lessons learnt can be recorded quickly. 5) Organise feedback session: This is particularly important where you have a project steering group for the audit. This steering group, through its involvement with the strategy, will feel empowered and capable of enthusing and empowering others. An effective steering group should consist of: •

Chair: An operational Director

•

Representatives: One from each Section

•

Quality Minutes: Rotate between members

•

Regular Meetings: Monthly and ad hoc

•

Email List: Discussion List for core, active and peripheral members

•

Intranet Presence: Tracking progress

•

Monitoring and Evaluation Procedures: Internal consultant

6. Draft strategy: This should demonstrate key findings, be well analyzed and the data should be arrayed in an accessible format. 5.6.3. Process mapping Process mapping is a simple exercise. It helps an organisation to know where to start making improvements that will have the biggest impact. A good definition of a process describes it as a series of connected steps or actions to achieve an outcome. A process has the following characteristics: 1. 2. 3. 4. 5.

A starting and end point. A purpose or aim for the outcome. Rules governing the standard or quality of inputs throughout the process. It is usually linked to other processes. It can be simple and short, or complex and long.

Process mapping is one of the most powerful ways for multi-disciplinary teams to understand the real problems from the individual’s perspective, and to identify opportunities for improvement. A map will give you: 1. A key starting-point to any improvement project, large or small. 2. The opportunity to bring together multi-disciplinary teams from primary, secondary, and tertiary organizational levels to create a culture of ownership, responsibility and accountability 190



3. An overview of the complete process – helping staff to understand, often for the first time, how complicated the systems can be.

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4. An aid to help plan effectively where to test ideas for improvements that are likely to have the most impact on the project aims 5. Brilliant ideas – especially from staff who don’t normally have the opportunity to contribute to service organization, but who really know how things work 6. An event that is interactive, that gets people involved and talking 7. An end product – the map – which is easy to understand and highly visual rocess mapping is also easy, creative and fun. 5.6.4. Outcomes of knowledge audit The outcome of a knowledge audit tends to be marked by the production of a document. This document should be made available in both hard and soft copy. It should be accessible both as a dynamic Intranet site and interactive CD ROM. 5.6.5. Components of a Knowledge Audit A Knowledge audit can have the following components (not necessarily need to be in order): A. B. C. D.

Knowledge need analysis Knowledge inventory analysis Knowledge Flow analysis Knowledge mapping

K-Needs Analysis

K-Inventory Analysis

K-Flows Analysis

K-Mapping

Figure 5.3. K-Audit Components A. Knowledge Needs Analysis (K-Needs Analysis) The major goal of this task is to identify precisely what knowledge the organization, its people and team possess currently and what knowledge they would require in the future in order to meet their objectives and goals. Knowledge need analysis can help any organization to develop its future strategy. Amrit Tiwana suggested the following figure to explain the Knowledge-Strategy Link.

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Figure 5.4. Strategic K Gap analysis The K-need analysis can also measure the staff skills and competency enhancementneeds and opportunities for training and development, corporate knowledge culture-practices such as knowledge sharing attitude, collaboration, team spirit, rewards and recognitions & staff relationship with their superiors, peers and subordinates. B. Knowledge Inventory Analysis (K-Inventory Analysis) Knowledge inventory is a knowledge stock taking to identify and locate knowledge assets and resources throughout the entire organization. This process involves counting, indexing, and categorizing of corporate tacit and explicit knowledge. Knowledge inventory analysis comprises of 2 entities: Physical (Explicit) Knowledge inventory and Corporate Experts (sources of tacit knowledge) inventory. (a) Physical (Explicit) Knowledge inventory of an organization: •

Numbers, types and categories of documents, databases, libraries, intranet websites, links and subscriptions to external resources

•

Knowledge locations in the organization, and in its various systems

•

The organization and access of the knowledge (how knowledge resources are organized and how easy is it for people to find and access them)

•

Purpose, relevance and quality of knowledge (why do these resources exist, and how relevant and appropriate they are for that purpose, are they of good quality up to date, reliable, evidence based, making sense, relevance to the organization)

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•

Usage of the knowledge (are they actually being used by whom, when, what for and how often)

•

(b) Corporate Experts (sources of tacit knowledge) inventory:

•

Staff directory and their academic and professional qualifications, skill & core competency levels and experience

•

Training and learning opportunities

•

Future potentials-leadership potential

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The K-inventory analysis may involve a series of surveys and interviews in order to get relevant answers to the above questions on both tacit and explicit knowledge that an organization may hold and have. By making comparison between knowledge inventory and the earlier analysis of knowledge needs, an organization will be able to identify gaps in their organization’s knowledge as well as areas of unnecessary duplication. (C) Knowledge Flows Analysis (K-Flows Analysis) Knowledge flow analysis look at knowledge resources move around the organization, from where it is to where it is needed. In other words, it is to determine how people in an organization find the knowledge they need, and how do they share the knowledge they have. The knowledge flow analysis looks at people, processes and systems: •

Analysis of people: examine their attitude towards, habits and behaviors concerning, and skills in knowledge sharing, use and dissemination.

•

Analysis of process: examine how people go about their daily work activities and how knowledge seeking, sharing, use and dissemination form parts of those activities, existence of policies and practices concerning flow, sharing and usage of information and knowledge, for example, are there any existing policies such as on information handling, management of records, web publishing etc? Or are there other policies that exist that may directly or indirectly affect or relate to knowledge management, which may act as enablers or barriers to a good knowledge practice?

•

Analysis of system: examine technical infrastructure: for example, information technology systems, portals, content management, accessibility and ease of use, and current level of usage. To what extend those existing systems facilitate knowledge sharing and flow, and help to connect people within the organization.

An analysis of knowledge flows will allow an organization to further identify gaps in their organization’s knowledge and areas of duplication; it will also highlight examples of good practice that can be built on, as well as blockages and barriers to knowledge flows and effective use. It will show where an organization needs to focus attention in their knowledge management initiatives in order to get knowledge moving from where it is to where it is needed.

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(D) Knowledge Mapping (K-Mapping) The knowledge map is a navigation aid to explicit (codified) information and tacit knowledge, showing the importance and the relationships between knowledge stores and dynamics. The knowledge map, an outcome of synthesis, portrays the sources, flows, constraints and sinks (losses or stopping points) of knowledge within an organization. There are two main approaches to knowledge mapping: 1. Mapping knowledge assets and resources- the map shows what knowledge exists in the organization and where it can be found (holders of the knowledge-knowledge creator, collector, connector, users and knowledge critics, and data repositories) 2. Mapping knowledge flows- the map shows how knowledge moves around the organization from where it is to where it is needed. Deliverables of a knowledge audit Common approaches and tools that can be applied to conduct a knowledge audit are: Site observation, questionnaire-based surveys, face to face Interviews, focus group discussion, forums. A knowledge audit could be divided into four parts: background study, data collection, data analysis and data evaluation. So the deliverables of a knowledge audit could be: A list of knowledge items (K-needs & current K-assets) in the form of spreadsheets a) A knowledge network map which shows the flow of knowledge items b) A social network map that reveals the interaction among staff on knowledge sharing These deliverables will help an organization in identifying the gap between “what is” at present and “what should be” in the future from a KM perspective. 5.7. KNOWLEDGE CAREERS The revolution in the field of knowledge is gradually leading to the establishment of a knowledge society, a knowledge economy, and knowledge organizations with knowledge workers, in the process giving a strong momentum to the all-pervasive concept of ‘Knowledge Management’. As the KM field expands, organizations increasingly rely on ‘knowledge workers’ to generate, classify, manage, and distribute tacit and explicit knowledge. Knowledge career offers extensive opportunities in the filed of KM and we are seeing the emergence of specialist knowledge professionals. Variety of new titles and job responsibilities appearing in a variety of functions - knowledge engineer, knowledge editor, knowledge analyst, knowledge navigator, knowledge gatekeeper, knowledge brokers, knowledge handyman, knowledge asset manager, knowledge steward or shepherd etc. And these do not include the facilitation and coaching roles nor the functional job titles which are assuming the leadership role in many companies.

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Knowledge careers is therefore a highly confidential, executive level recruiting competence for organizations interested in formalizing knowledge strategy and operations capabilities. Organizations are relying on people with specific training in information and knowledge systems coupled with a strong functional expertise to occupy the various positions being thrown up. This section presents the various career opportunities that exist in the organizations employing KM initiatives.

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5.7.1. Organizational knowledge role classification As organizations become more knowledge-based, new knowledge roles are emerging and the roles of existing knowledge workers are changing. All roles require more knowledge creation (creativity) and knowledge-sharing. Successful knowledge-based companies depend upon how successful individual knowledge workers create and apply new ideas productively and efficiently (i.e., how they innovate). This requires new roles, new skills and new ways of developing organization capabilities that continuously improve, such as through organizational learning. Let us present first a classification system that divides knowledge professionals into eight categories based on skills required. This classification help potential candidates to determine what positions are appropriate for their skills and also aware of the tremendous amount of potential and opportunities available in the field of KM. Knowledge and Innovation Professionals Individuals have strong background in shaping and formulating knowledge-based programs. Many have developed best practices for global Fortune 1000 Companies. Most are highly skilled in a variety of disciplines including business process improvement, innovation, performance measurement & modeling, case history, facilitation, strategic integration and developing best practices. Chief Knowledge Officers are part of this group as are consultants. Knowledge Management Professionals Knowledge Management Professionals have expertise in implementation. They ensure a company gains from management of knowledge. They are involved in all phases of Innovation (Knowledge creation, knowledge acquisition, knowledge sharing, knowledge conversion, knowledge commercialization. Career background may be in any functions, e.g. Finance, Human Resources, Quality, IT, R&D, Manufacturing, Sales, Service). Knowledge Catalogers, Researchers and media Specialists These are contributors whose skills are web site, internet and intranet developers, librarians, catalogue specialists, content developers, communicators, software designers and developers, middle managers and others who create the knowledge networks and links. 195


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Knowledge and Competitive Intelligence Professionals Emphasis focuses on competitive intelligence. Heavy research, the ability to create and develop solid positions, on line research savvy mixed with the ability to cogently and concisely present ideas in a clear and concise format are well developed skills. Writing and presentation skills are strong. Knowledge and Strategic Integration Professionals Composed of top strategists, thinkers, planners, marketers, and individuals with senior management experience. These folks make planning and strategy the engine for business improvement and growth. Knowledge Academicians, Theorists and Visionaries This group focuses primarily on discussion within an academic setting and developing and testing models and applications. Visionaries are thought leaders who are frequently well in front of the practice. These individuals make outstanding speakers and can stimulate your organizations thinking. Knowledge facilitators, trainers and Corporate Educators These individuals focus on learning and education in a corporate setting. Many have created outstanding models and programs for linking external and internal audiences, designing and developing curriculums, implementing distance learning and creating customtailored courses for executives and senior managers. Knowledge and Expert Systems Professionals One facet of knowledge and knowledge management is expert systems and how to institutionalize corporate knowledge. Individuals in this area include Systems specialists, Technologists, Chief Information Officers, Technology Transfer Specialists, Expert Systems Engineers, Project managers and others who primarily focus on information technology. 5.8. CLASSIFICATION OF KNOWLEDGE MANAGEMENT CAREERS The following section presents the classification of career opportunities in the field of knowledge management as well as the various requirements of specific positions in KM enabled organizations. The specific responsibilities are highlighted. Some of the career opportunities are as follows: Managerial positions (a) Chief Learning Officers (CLO) (b) Chief Knowledge Officers (CKO) (c) Knowledge Managers (d) Knowledge Initiative Managers 196



(e) (f) (g) (h)

Knowledge Management Experts Knowledge Transfer Experts Knowledge Engineers Knowledge Strategist

NOTES

Technical positions (a) (b) (c) (d)

Knowledge Analyst Knowledge Mapping Specialists Knowledge Content Creators Knowledge-Base Architects and Administrators

Non-Management Positions (a) Librarians (b) Cybrarians (c) Information Brokers 5.8.1. The qualities & attributes of CKO The Chief Knowledge Officer (CKO) needs to broadly possess two major attributes - leading and managing qualities. He needs to be an entrepreneur and a strategist who can understand the implications of using KM to transform organizations. At the same time he needs to be a consultant to listen to other people’s ideas, incorporate them and nurture them if they fit the knowledge vision. As for managing qualities, he needs to be techno-savvy. The CKO has to understand which technologies can contribute to capturing, storing, exploring, and in particular sharing of knowledge. His second competence lies more in the management of tacit knowledge. His role here is more of creating a social environment that stimulates and encourages knowledge creation and exchange. The desired qualifications for a CKO are a post graduation in Human Resource Management though it is not mandatory. A graduate study in Humanities-sociology, psychology, economics, history or political science is very helpful and essential. The qualities required by the CKO are multidisciplinary in nature. In this respect the CKO’s role is perhaps deeper than the CEO’s and is often broader than the CIO’s (Chief Information Officer) can or has the time to be. The CKO’s primary focus is on the intangible assets as against the CFO’s (Chief Financial Officer) focus on tangible assets. To rise to the level of CKO one needs to have considerable ability in all fields of functionaries (as mentioned below) and have the additional qualifications of people management and group dynamics.

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5.8.2. Knowledge Management Analyst The job of a knowledge management analyst is to understand the proper collection, storage and presentation or dissemination of research or intellectual capital that is created with a research facility, hospital or other type of care facility. Without the use of knowledge management analyst the facility may inadvertently lose money, funding, or access to other research options because of poor management of the information. A knowledge management analyst must be able to understand what is the best possible market for the information or research, as well as make recommendations to the governing bodies of the research facility as to what is the most opportune way to present the data. In addition the knowledge management analyst works closely with the research grant writers and other individuals involve in preparing data collections and assessments for publication and dissemination. The knowledge management analyst may also work to develop relationships with other research facilities and enhance the ability to share information through networking or other group processes. A high level of communication, ability to work with others as well as understanding the various data collection processes is essential. The knowledge management analyst may work onsite at the research facility or may work off-site with link up through the internet. Usually the knowledge management analyst will have regular contact with the facility even if they work primarily from another location. Most knowledge management analyst’s positions require Bachelor level training in business administration, mathematics, statistics, bioinformatics or other related field. In addition experience in working with data collection programs such as Oracle, is strongly favored. A knowledge management analyst must have several years in the research field with most having an average of 10 years experience. Strong ethical understanding as well as a comprehensive knowledge of regulations, laws and protocols regarding information dissemination is critical for a knowledge management analyst. 5.8.3. Knowledge Architect Position description A Knowledge Architect is a SME with additional responsibilities including the structural of organizational knowledge-bases and maintaining the even flow of the current development process. This position also liases with the product and development managers to help determine the direction of the product.

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Primary duties •

Ensure the proper coverage of a domain area by, for example, locating and including FAQs and common problems.

•

Maintain an even flow of symptoms to be further analyzed through research, including analyzing and processing licensed content.

•

Ensure a logical and user-friendly structure for knowledge-base to allow easy-tofind solutions.

•

Ensure the quality of the structure by performing structural level quality assurance tasks.

•

Maintain broad knowledge of all the related domain areas.

•

Assist in product planning by working with product and development managers, as well as customers and in-house SMEs.

NOTES

Secondary duties •

Maintain an in-depth understanding of the various knowledge-base platforms.

•

Assist in packaging and releasing each edition of the content product, including requesting and attaching module icons, helping with release notes, etc.

Required skills •

Broad knowledge of all domains areas for the designated product, if applicable, and in-depth knowledge of designated domain areas.

•

Ability to plan multiple projects.

•

Ability to analyze and translate user requirements.

•

In-depth knowledge of the platforms with which the content product is integrated.

Job levels •

Level 1: 1-3 years of experience using the above skills; Expert in a minimum of 2 domain areas

•

Level 2: 3-5 years of experience; 3-5 domain areas

•

Level 3: more than 5 years of experience; More than 5 domain areas

5.8.4. Knowledge Strategist Position description The knowledge strategist functions as a consultant in all phases of the KM consulting practice. This involves working with clients to design and develop processes/applications/ systems that improve the client organization’s ability to leverage information and expertise.

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Primary duties Responsibilities include conducting on-line assessments of client’s requirements needs, synthesizing, summarizing and generating recommendations, developing presentation material, generating client proposals, as well as assisting in selling organizational services. This position also includes, assisting clients in implementing KM systems, creating a business environment that is conducive to knowledge sharing, and increasing the speed and productivity of key business processes within the organization. Required skills •

A minimum of 3-5 years of experience delivering on-site business consulting services to Major Corporation and implementing successful business solutions.

•

Ability to work well in all levels in an organization.

•

Exceptional relationship building track record.

•

Demonstrated ability to manage projects.

•

Understand/capacities to sell consulting services and have a successful track record of selling ideas to clients and co-workers.

•

Broad understanding of IT systems and leading edge software, including webbased technologies.

•

Formal management qualifications desired.

5.8.5. Knowledge Manager As the primary leader of the Knowledge Management team, the Knowledge Manager (aka KM) is primarily responsible for managing the organization’s knowledge assets. Depending on the depth and breadth of a particular organization, this team member may be part of a small, focused group, within the IT department of a relatively small company, or, in a large corporation, the KM may wear one of many hats common to more lateral organizations. Among the responsibilities of the Knowledge Manager is to manage the creation and delivery of IT (and/or business) knowledge, and, to support the utilization of this accumulated information by both the internal and external end-user communities. This may include any or all of the following duties and capabilities: a. Understanding the end-user’s information needs, b. Coordinating who is responsible for each knowledge asset, c. Where appropriate, communicating knowledge requirements to service providers, d. Planning and managing the delivery of knowledge projects, communicating the availability of knowledge to the end-user community, e. Monitoring the use of the knowledge assets and measuring the business value of the knowledge to the end-user community. 200



Position description

NOTES

The primary broad objective of this role is to define and manage the organizational KMS. Primary duties •

To define the requirements for KM at divisional/departmental level within organizations.

•

Define and implement the KM tools required to support these needs.

•

Define operational requirements for managing KM tools.

•

To ensure proper operation of the KM tools.

Required skills •

Extensive experience (5 years +) in software systems development, and operations, preferably within the telecommunications or IT industry.

•

Previous experience in KM tools deployment and operations.

•

Proven capability to work in an international multi-cultural multilingual environment.

•

Capability to manage relationship with users, integrators, and suppliers in a distributed environment.

5.8.6. Research Analyst/Manager Position description Under the direction of the category manager, the research analyst is responsible for researching and cataloging specific industry, functional, or topic areas on the internet with a business focus. Primary duties The research analyst is responsible for developing the controlled vocabulary for their area, as well as contributing to other standards of organization and control. Cataloging will include assigning subject headings as well as writing abstracts and reviews. The research analyst can progress to the level of a category expert by understanding all of the business resources available on the internet within their area of responsibility. Required skills •

MLIS, MLS, or equivalent with minimum of two years professional experience within a specific industry or industries, or other college graduate with research experience and minimum three years experience within a specific industry or industries.

•

Sound knowledge of information resources within a specific industry (more than one industry preferable) and most possess knowledge of business information needs. 201


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•

Excellent analytical, organizational, and communication skills.

•

Thorough knowledge of the internet and its available resources is a must, as well as a comfortable level of technical knowledge.

•

Educational background in business is a plus.

5.8.7. Knowledge Management Consultant Position description Partner with clients to help create the environment, the KM process and organization, the technology infrastructure, and the KM applications. Primary duties The incumbent would be primarily responsible for the architecture, design, and creation of new infrastructure or the improvement and enhancement of existing infrastructure. In addition the individual would also be responsible for the development of systems to implement specific business processes using tools and technologies of KM. The role also involves assisting in managing the knowledge sharing strategies and organizational processes both internal and external. Required skills •

Minimum 2 years of KM or electronic performance support experience in planning, implementing, and supporting KM initiatives and strategies.

•

Qualifications should include strong planning, design, relationship, communication, project management, and management of technical teams.

•

Must have a strong user-focus and a passion for solving business problems using technological solutions.

•

Experience in KM tools and software selections.

•

Bachelors Degree (preferably in Information Systems, Computer Science, or Engineering)

•

Strong desire to work in the management consulting industry.

5.8.8. Media Specialist Position description General, business, and specialty publications indicate that the demand for special librarians or knowledge catalogers is increasing qualitatively and quantitatively. Companies are hiring these skilled professionals to perform conventional information functions as well as branch into other areas like information architecture for web sites.

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5.8.9. Senior Market Intelligence Librarian

NOTES

Position description This position would be responsible for providing human and database infrastructure support to employees and members to facilitate effective access to marketplace information for development of business intelligence and product innovation. This will include management of proprietary and syndicated research and innovation results. Primary duties The primary responsibilities include strategic marketing and market research library management which includes report cataloging, database administration, and on-line research. This is an addition to the responsibilities for the administration of organizational repositories including managing the idea submissions, database administration, employee web-site administration, and participant communication. Required skills • • • • •

College degree or equivalent. Degree in business, market research or library science specialization preferred. Candidates must have strong project management and organizational skills. Excellent communication skills. Experience in database administration and web site development.

5.8.10. Ontologist/Knowledge Engineer Position description This position calls for a proven track record developing timely and usable solutions to complex problems with experience in building ontologies and knowledge representation systems besides the following: • • • •

Software development experience. One + years experience in building ontologies for commercial use Experience in e-commerce systems. Effective oral and written communication.

Primary duties • • • • •

Assist in the development and implementation of schema for classification across multiple domains. Assist in development of automatic classification methods. Work with SME’s in multiple industries. Work with domain experts internal to the company. Undertake ontology maintenance procedures. 203


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Required skills • • • • • • • • •

Two +years experience as an ontologist. Knowledge of computational classification methodologies. Ability to lead and work with a team. Work under tight deadlines. Possess knowledge base of industry-specific tools available. Applicable area of expertise. Able to interface and deal with a wide variety of people. Goal driven. Graduate degree or equivalent experience: linguistics, computer science, AI, knowledge representation, lexical semantics.

5.8.11. Knowledge Management Specialist Position description Manage organizational employee development and/or KM programs Primary duties Provide leadership to develop agency-wide coalitions; serve as a subject matter expert in the formulation and implementation of career development, competency models, and/or knowledge management systems; analyze performance gaps, research state-of-art interventions, create measurement evaluation criteria to build a dynamic, fast-paced, learning organization. 5.8.12. Intranet Developer/Knowledge Management Content Developer Position description Capability to collect, store, retrieve, disseminate, and archive critical business information. Primary duties The above mentioned capability must be implemented on intranet/extranet to provide secured global access on a 24- hour basis. The responsibility would include the definition, implementation, and support of several intranet/extranet based applications and related procedures. This position will also be responsible for documenting and maintaining all of formal business procedures of the organization including those related with project management, business development, and business planning. Required skills •

Two to five years of experience in internet site content management.

•

One to two years experience in defining and implementing business operation procedures. 204



•

End user and/or IS staff experience with internet based applications.

•

Experience with defining, implementing, and maintaining operational procedures.

•

Engineering degree preferred.

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5.8.13. Knowledge Management Director Position description Independently responsible for capturing, consolidating, organizing, and architecting all of the knowledge required for the organizational functioning. Primary duties Responsibilities include the definition, shaping and of the organizational knowledge management solutions. The candidate would oversee current and future team efforts around building and enhancing web-based KM solutions. This includes managing complete development life cycle of the KMS from design to deployment, and managing the project team consisting of program managers, developers, and testing staff. Required skills •

Demonstrate understanding of current and emerging technologies from an architectural standpoint with the ability to rapidly learn new technologies and experience with server-based products.

•

Strong understanding of all facets of the intranet/internet infrastructures, information management concepts, network services, multimedia over the internet, and security is necessary.

•

Experience in designing and implementing intranet applications and websites preferably on enterprise-scale internet/intranet sites is highly desirable

•

Experience using software development methodologies, processes, and metrics.

•

Strong knowledge of web authoring, HTML, W3C standards and definitions, and internet development.

•

Opportunities for specialists in knowledge representation and categorization schema continue to expand as e-commerce applications grow. Short position descriptions are listed below.

5.8.14 Z. Director of Ontologies Responsibilities/qualities • Develop and implement schema for classifying and describing items across multiple domains. • Develop automatic classification methods. • Work with SME’s in multiple industries. • Work with domain experts inside the company. 205


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• • • • • •

Managing a team of ontologies. Leverage ontology “maintenance” procedures. Create a team environment in ontology group with a “get it dome” attitude. Progressive thinking. Possess knowledge base of industry-specific tools available. Goal driven.

Desired • • • •

A proven track record developing timely and usable solutions to complex problems. Two years experience building ontologies for commercial use. Ability to lead a team and a company to implement and improve schema. Experience in building ontologies and knowledge representation systems.

Required • • • •

Ph.D or Masters in linguistics or equivalent experience. Two years experience as an ontologist. Knowledge of computational classification methodologies. Ability to lead and work with a team.

5.8.15. Ontologist (biological domain) Responsibilities Build ontologies in a team of knowledge representation experts. Gather, analyze, and categorize biological knowledge from diverse sources. Work with SME’s to accurately present knowledge. Required competencies •

Experience in building ontologies, or in electronic publishing mark-up languages, or related categorizing specialties.

•

Experience in a similar role in a business enterprise.

Desired competencies • • •

Knowledge of biological issues and vocabulary. Experience in genetic and protein-related research. Data modeling experience in biotechnology.

Required educational background • Degree in a field related to biology or medicine. Desired educational background • Ph.D in biology with research in computational data modeling. 206



5.8.16. Natural Language Processing Specialist (medical/biomedical)

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Responsibilities •

Knowledge extraction from medical/biomedical text corpus in support of knowledge representation product.

Required educational background • MS in computer science or computational linguistics. 5.8.17. Knowledge Development Manager Position description The primary responsibility is to assist in managing the organizational knowledge reuse strategies. Primary duties •

Implementing processes to locate existing knowledge/content from selected areas within the organization and extending it into educational opportunities for customers. This content may be in the form of survey data, white papers, research publications, conference proceedings, etc.The resulting educational programming would be created in partnership with the original content developers and maybe delivered via seminars, publications, CD ROMS, web-based, satellite networks, streaming media or two-way interactive video.

•

In addition, this position will be responsible for the process related to the organizational identification and communication, the topics of current interest to customers as well as stimulating the creation of new knowledge directed towards these topics

Personal competencies •

Excellent networking skills in order to develop and maintain highly effective internal and external relationship.

•

Ability to quickly grasp new concepts.

•

High level of initiative and creativity.

•

Crisp, precise written communication and well-developed presentation skills.

•

Adept with all types of educational technologies

•

Strong project management skills.

Managerial • • •

Develop methods, techniques, policy and evaluation criteria for obtaining results. Drive change and gain acceptance of others in sensitive situations. Work on complex, undefined problems. 207


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Knowledge and experience •

5-7 years instructional design with proven abilities in needs assessment, creating educational programming and documentation.

5.9. CASE STUDIES Case I - TATA Steel Tata Steel has been recognized as the overall (1st place) 2006 Indian Most Admired Knowledge Enterprises (MAKE) Winner compared to its 6th position far the last year (2005). Tata Steel’s 2006 Indian MAKE rankings in the 8 knowledge performance dimensions which are the basis of the MAKE framework are: • • • • • • • •

creating an enterprise knowledge-driven culture (1st place) developing knowledge workers through senior management leadership (2nd place) delivering knowledge-based products/solutions (3rd place) maximizing enterprise intellectual capital (3rd place) creating an environment for collaborative knowledge sharing (1st place) creating a learning organization (1st place) delivering value based on customer knowledge (1st place) transforming organizational knowledge into shareholder value (2nd place)

According to Rory Chase, managing director of Teleos, “India is emerging as a dynamic center of innovative knowledge management. The annual Indian MAKE study serves as a benchmark to recognize those Indian companies which are leaders in effectively transforming enterprise knowledge into wealth-creating ideas, products and solutions. These companies are building portfolios of intellectual capital and intangible assets which will enable them to out-perform their competitors - both in India and abroad - in years to come.” This is the first time that the Tata Group has been named a Global MAKE Winner. As per the summary report available Tata Group was rated high in two of the following knowledge dimensions •

Developing knowledge workers through senior management leadership (8th place)

•

Creating an environment for collaborative knowledge sharing (13th place)

•

According to Mr. Rory Chase, MD, Teleos, Tata Steel and Tata Consultancy Services received a similar number of nominations from the 2006 Global MAKE expert panel. Most of Tata Steel’s nominations (approx. 90%) were from 2006 Global MAKE expert panel members located in Asia.

•

Tata Steel received particularly high scores in the following knowledge performance dimensions: Creating a learning organization Delivering value based on customer knowledge Areas where Tata Steel can improve are:

• • •

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• •

Maximizing enterprise intellectual capital Transforming enterprise knowledge into shareholder value

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The American Productivity and Quality Center (APQC) selected Tata Steel as one of the Best Practice Partners in the area of “Leveraging Knowledge across the Value Chain”. The other organizations selected as best-practice partners are Buckman Labs, Raytheon, Caterpillar, and the US Air Force Material Command. All the Best Practice Organizations has been recognized on January 24-25, 2006 at Houston at the Knowledge Transfer Session. The message received from APQC is as follows:“Congratulations on being selected as a best-practice partner in APQC’s Leveraging Knowledge across the Value Chain consortium benchmarking study! The study sponsors are impressed with the work Tata Steel is doing and are eager to learn from your organization as we continue through this study. The other organizations selected best-practice partners are Buckman Labs, Raytheon, Caterpillar, and the US Air Force Material Command.” APQC is involved in conducting consortium benchmarking study on various business processes. They have a structured methodology for identifying and selecting “Best Practice Partner” for a particular consortium benchmarking study. In the process they have identified Tata Steel as one of the potential best practice partners and after one and a half hour of teleconferencing APQC prepared a case study for Tata Steel which was then discussed with the sponsors of the benchmarking study. After going through the case study of each potential partner, sponsors select the best practice partner. All selected Best Practice Partners share their practices with sponsors and with each other through a virtual site visit and the cycle finishes with one and a half day Knowledge Transfer Session (KTS) in which Best Practice Partners present their case study to all the participating organizations and APQC recognizes them at the end of KTS. TATA STEEL Launches ‘Knowledge Manthan’ - The KM programme, which so far was primarily focused on officers and a few supervisors who were computer savvy, was brought within the reach of other employees working at the shop floor through a new initiative named Aspire Knowledge Manthan.(Churning of Knowledge). This new initiative was launched by Dy. Managing Director (Steel), Dr T Mukherjee on 2nd March, 2004. This is an initiative to capture and share the tacit knowledge directly from the grass-root level. Knowledge Manthan is conducted every month on certain selected topics (e.g. Motor, Leveling and alignment, Lubrication, Water Treatment, etc.) in which supervisors from all corners of the plant including the sister concerns of Tata Steel participate. They discuss and share their knowledge on a common topic through various methods like Story-telling’ method or through case studies to generate initial interest in the group. In order to facilitate the discussion, all these Manthan sessions are chaired by one ‘Champion’ and an ‘Expert 209


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Question: Write a detailed account of KM initiates at Tata? Case II - Cognizant Most Indian firms aren’t exactly global leaders in the use of technology. IT penetration is taking off in Indian firms today, and there are some trendsetters, but these are few and far between. Take the hot field of Knowledge Management. Even the most IT-enabled Indian firms—with comprehensive electronic-KM infrastructure and systems such as intranets, HR guidelines and performance-linked incentives for KM practitioners—are content to let their CIOs or CEOs double up as Chief Knowledge Officers (CKOs). However, Cognizant is a trendsetter here and is perhaps one of the very few software companies in the country that has a senior position titled as the CKO, exclusively for knowledge management. R Ramkumar, who’s the CKO at Cognizant, explains why an organisation needs a CKO in the first place. “Look at the sheer enormity of requirements of a KM system. You need to spearhead all knowledge efforts; make knowledge visible by ensuring smooth running of knowledge practices and leverage knowledge by ensuring that generated/ transferred knowledge delivers for the organisation in the form of inputs for innovation, decision-making, etc. So if KM is to be practiced in its truest sense, the organization certainly requires an individual focusing entirely on these efforts.” He adds however that just a CKO alone does not help—there has to be a committed team to support the initiative in order for KM to become a success. Ramkumar also explains the evolution of the CKO role in companies. “The CKO emerged in the early 1990s. In the initial days of KM practices CKOs routed bits of information through different pipes to the right people, then they built better networks: company-wide e-mail networks and corporate intranets, and, further down the line redesigned work and communications processes to promote collaboration.” The other C From the way KM is being shaped at Cognizant, it becomes clear that it is not just about creating a culture conducive for knowledge creation, but more importantly, it is also about generating business. “Yes, our KM department has a revenue target too,” says Ramkumar. Having acquired substantial knowledge about KM in practice in the last four years since we embarked on the KM initiatives, developing KM systems itself has now become a new line of business.” ChannelOne Channel One is the knowledge management portal developed by Cognizant. Postings on best practices, proposals, estimations and methodologies are created, managed and distributed online via this portal. 210



The company has around 60 knowledge harvesters, including eight knowledge auditors, whose role is to encourage everyone in the organisation to participate in digitizing corporate memory and knowledge management initiatives.

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“Earlier, people used to send bulk mail to all employees, whenever they wanted to know some crucial information but had no clue with whom it resided. But now, they can find everything at ChannelOne, which also has a feature called: ‘What I didn’t find,’ that enables users to inform the KM team about their knowledge requirements which are not available in the portal,” Ramkumar explains. Communities of Practice (CoP) Another important facet of KM at Cognizant is the communities of practice. Ramkumar has this anecdote to share whenever he is asked to explain the power of CoP. “In the punch-card days, Indian Railways sourced out some of the processing operations that its existing staff could not handle in their eight-hour work shifts. At one point, the management decided to provide extra monetary benefits for its staff, who could work extra time to finish those additional processing operations. The staffs were motivated by the monetary incentives but they were not happy about working long hours. So they started exploring all ways to share their experiences and knowledge together in creative and free-flowing ways that fostered new approaches for completing the additional work well within office hours. Finally, they were able to process all the additional processing work well within the eight hours. This is a classic example of ‘communities of practice (CoP)’ in practice.” He points out that CoPs have been instrumental in driving the World Bank’s KM strategy; At Chrysler, senior managers and engineers formed ‘tech-clubs’ comprising experts from different car platforms, which helped the company cut R&D costs by almost 50 percent. They now maintain an Engineering Book of Knowledge that captures variations in best practices. “The effects of community activities are often delayed. But CoPs do pay off. For instance communities at Shell saved $2- 5 million for the company and contributed to revenues by more than $13 million in a single year,” Ramkumar says. At Cognizant too, CoPs are making a difference to the company. The returns “KM is not about building a smarter intranet. Intranets are only part of the KM initiative in an organization. It is also not about a one-time investment. KM is, in fact expensive and has a long gestation period. For these reasons, it is crucial to build metrics of the results of KM systems and continually monitor the return on the investment (RoI) made with the infrastructure.” However, Ramkumar acknowledges that there is a lack of comprehensive standards for measuring the impact of KM. “In a sense the metric is the limitation,” he feels and adds, “It is akin to one trying to compute the RoI of a telephone.” 211


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“Metrics data should be collectable without undue burden since it’s not the measures themselves that matter but the decisions that will be based on them. Measures that are expensive and cumbersome to collect will detract from the measurement program’s perceived value. The best measures would therefore be the ones that would be the natural outcome of people’s work,” he explains. Ramkumar further adds that it would be wrong to focus on the metrics that just emphasise hard (financial) results while totally ignoring the soft ones. Hard results are often dependent on soft employee attitudes and behaviour, and it would be wrong to ignore these. The other limitation is that outcomes can often be based on other reasons. Hence, it may not be possible to attribute a higher project win-rate, for instance, to KM, because it might also be the by-product of other factors such as competition, a skilled sales person, etc. The thinking at Cognizant is that it may be better to carefully select a set of 15-20 metrics to act as a barometer in order to focus on and measure the past, present and future value of investments in KM simultaneously. Question: What are the knowledge sharing practices at Cognizant? Explain briefly the KM measurement system in Cognizant? Case III - Tata Consultancy Services (TCS) The informal, closely-knit communities of practices (CoPs) have existed at Tata Consultancy Services (TCS) since the eighties, when its team size was just around a thousand. However, with the phenomenal growth in size (now, 25,000 plus), expansion into new domains and markets, this geographically dispersed software firm uses online platforms to facilitate the formation of more CoPs on new technology domains and managerial practices. Considerable care had gone even into the architecture of TCS’ own development centers located across the country to encourage employee “conversations”—the lifeline of lively communities (of practices). “Welcome to our Sholinganallur development centre,” invites the chief financial officer S Mahalingam, to show how the building allows employees to talk to each other. “This centre consists of modules, each dedicated to one particular technology or a client or an industry practice. These structures lead to garden terraces, where employees gather during their break for animated, informal conversations. Those conversations could be personal, about their colleges or native places, but they provide the necessary bonding for the communities that are technology centric,” he says, adding, that when they converse with their colleagues, they often get solutions for problems they were vexed with.

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Organizational memory

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To continue to facilitate the conversations across a growing and diversified team spread across different time zones and locations has been something Mahalingam and his colleagues are trying to do—with the help of IT. His understanding is that vibrant communities—the repositories of organizational memory—enhance organizational capabilities. When capturing organizational memory becomes a necessity, the communities become inevitable. Mahalingam explains, “In traditional set-ups, organizational memory resided in human memory. It could even be about customers of one particular geographic location. The knowledge was passed from one person to another within the organization through some type of mentoring processes.” Now the mentoring process takes place online through mailing lists, Web postings, etc. TCS has built a Web-based electronic knowledge management (EKM) portal—Ultimatix. Supported by this Web portal and several Intranet sub- portals are 26-odd divisions of CoPs—one each for 10 major industry practices, 10 service practices and six corporate functions. Mahalingam explains the two important knowledge types in an organization that CoPs and IT tools can help capture and disseminate. “There is knowledge pertaining to operational—that is on how to deal with a particular type of project or how to do business with a particular customer. Or knowledge about a business domain, like healthcare, telecom, etc. Or it could even be about how to do business itself. And the knowledge that has to do with the people and their project expertise. For instance, our US team could have delivered a project to a client based in the same country. In the event of the same client moving to Singapore, there needs to be a way to transfer the knowledge of our development team in the US, which had already learned a good deal about this customer, to the Singapore team.” The beginnings “The phrase communities of practices might have been coined some five years back, but there have been CoPs in the past as well. We simply did not have the software tools then and that is the only difference,” says Mahalingam. The earliest “group” in TCS was based on the migration of technologies headed by Professor Kesav Nori. Then teams were formed for mainframe, UNIX and databases. K Ananth Krishnan, certified quality auditor (CQA), architecture and technology consultant, who was heading the mainframe group, recollects the group practices in the initial days: “Typically such groups were built around one or two experts in that particular field. Then there were only about a thousand employees in TCS and the physical separation also was manageable. We almost instantly came to know what were the opportunities and solutions for the problems in the small setup.”

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The groups kicked off formal documentation practices with the members writing down the best practices. Says Krishnan, “In the mid-eighties, we started documenting the problems and solutions. For mainframe, we had over 1,500-odd case studies. We had this knowledge base to fall back on. Similarly for quality area, we had around 40 reviewed case study documents way back in 1993. In the late nineties, the community practices had been formalised.” About EKM EKM was the next big thing to happen to the community infrastructure, where the activities can take place with a wider user base. The precursor to Ulitimatix was the intranet system built after 1997. The intranet is still accessible only to the employees in India. “We concentrated on process change management and technology change management areas. Also we started creating Process Asset Libraries (PALs), which have technology, and process-related information, case studies, etc, for project leaders,” informs Krishnan, adding, “We have over 5,000 project leaders in TCS who have experience in the range of five to ten years. Not all of them have equal expertise in all project aspects. So, we formed the Software Engineering Group and made available the PAL copies to all development centres through the intranet.” Then came Ultimax, which made the knowledge globally available. The PAL library and knowledge bases, which were hosted on the intranet, became a part of Ultimatix. It presently has sub-portals for quality management system, software productivity improvement, training materials, tools information, among others. The company has EKM administrators for each practice and subject group with defined responsibilities. They edit the documents and approve it for publishing. Krishnan explains how the “relationship-based” exchanges, so typical of small groups, could still be maintained in the networked era. “The groups are still there. With technology we made them communicate with rocket power. Still in each community—at sub-levels— we have members in the range of 10 or 20 and not more than that. They typically work on a single site. For instance, our telecom group is based at Hyderabad and most members of this community are located there.” Measuring the success Measuring the return on investment and the success of CoP is not entirely possible. However, the level of participation of the members could indicate the vibrancy and activeness of a particular CoP. Krishnan informs, “Between January 2003 and June 2003, CoP members had exchanged around 10,000 document transactions (uploads and downloads) pertaining to the industry practices and 21,000, service practices via Ultimatix. The telecom CoPs alone had 6,000 transactions. This excludes the intranet-based community activities.”

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Though active community participation is not included in an employees’ appraisal process, it does count indirectly. According to Krishnan, the more expensive part of building the EKM and CoPs is not the hardware or software, but the investment the company makes on the employee-experts themselves. “Again the experts are not here to participate in the community and share knowledge by writing documents or taking training classes alone. These are only a part of their routine tasks. They are the innovators of the company,” he points out.

NOTES

Diversified groups Mahalingam emphasis that the sole objective of knowledge creation is knowledge dissemination, especially to diversified functional groups. In his opinion though EKM and CoPs are evolved confining to the people who create solutions, the knowledge they create should be extended to the staff of other functional areas as well. “From the strategic point of view, you have to extrapolate all sorts of data to do business. The marketing team with access to seemingly technical, project related data can actually understand, for instance, whether China is an emerging market in a particular segment.” Though the CoPs exist for human resource, marketing and other functional areas, TCS, which is emerging as an IT consulting service firm, rather than just a software development company, can expect to have more CoPs on management practices in the future. The future The challenge before the company is to make collaboration more cost effective. “We want to bring the cost incurred on travel, telephone and physical meetings down. The company has already minimized the cost of the first point communication by establishing mailing lists for the members. Now the cost of the first touch is almost nothing thanks to the Web. However, cost is involved in the second level of in-depth, comprehensive collaboration among the members of the CoPs, involving phone, travel, etc,” says Krishnan. He points out, “We do video conferencing but a lot has to be simplified. It should not be like walking into a room to use a video conferencing facility. It should be simple at the desktop level and not in one designated area. People should be able to do this with relative ease.” To facilitate interaction among members working in other offices, TCS will be rolling out new systems that would make it far easier for more comprehensive collaborations among employees working in geographically dispersed areas. Question: What are the causes of success of CoP practices at TCS? Case IV - Unilever Unilever is one of the largest consumer goods companies, with corporate centres in London and Rotterdam, and annual sales of around $48bn. It produces and markets a wide range of foods, home and personal-care products, under well known brands like Lipton, Ragu, Flora, I Can’t Believe It’s Not Butter, Breyers, Omo, All, Calvin Klein 215


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Cosmetics, Elisabeth Arden and Dove. A truly global company, Unilever employs almost 250,000 people in 100 countries, with sales in over 50 more. About 2.5 per cent of annual turnover is invested in basic research and product innovation, leading to the filing of more than 400 patent applications each year. At the heart of Unilever’s corporate purpose are the ambition to be a truly ‘multi-local’, multinational company – understanding and anticipating the everyday needs of people everywhere and meeting these needs with branded products and services. Having recognized the importance of knowledge as a key differentiator and the source for sustainable competitive advantage, Unilever has made significant investments in IT over the past decades. But the company soon realized that this was only part of the solution and that it was becoming more important that the investments the firm was making in knowledge contributed to top-line growth and profitability. Most knowledge in the organization is not explicit, but tacit, residing in the heads of its employees. In light of continuous restructuring, it is this tacit knowledge that is most under threat. Trying to capture or transfer this tacit knowledge is not easy, as it stems from personal experience and individuals are not always aware of the value of the knowledge they hold. Moreover, knowledge is not static. In fact, it is the continuous creation of new knowledge and learning, rather than static knowledge assets, which will produce a sustainable advantage. From knowledge workshops to communities of practice Taking this learning-organization perspective as a starting point, Unilever has put numerous knowledge-management initiatives in place across the company. In order to capture what was known and identify what was not (knowledge gaps), knowledge workshops were organized. Key experts and practitioners from around the world discussed, in an interactive and structured way, a specific, strategically relevant knowledge domain. The aim of the workshops was to come to a common understanding about the knowledge strengths and weaknesses of the company as a whole. Existing good practices were captured and rolled out to the wider community. At the same time, innovation and R&D programmes were put in place to address the knowledge gaps that were identified. From these workshops, communities of practice emerged – groups of experts acting as the custodians of a specific knowledge domain. However, it soon emerged that the most strategically relevant communities were not necessarily the most active ones, primarily because the experts that worked in an area that was of high strategic value were also in high local demand. To their own frustration, they found it difficult to keep the community of practice alive, given their day-to-day pressures. Networks have been interwoven with Unilever’s organization for many decades, both on a personal, informal level and on a more structured, organizational level. However, as 216



the organization becomes leaner, and bottom-line improvements bear fruit, it has become apparent that communities of practice depend on careful management and the appropriate allocation of resources if they are to survive. For this reason, the Knowledge Management Group (KMG) has put in place a more formal framework to help ensure the effective and efficient operation of the firm’s communities of practice.

NOTES

The Unilever CoP framework The communities’ framework advocates certain principles within which Unilever CoPs operate in order to ensure added business value. These principles can be organized into four pillars: deliverables, people, operations and leverage. A clear distinction is made within the firm between communities of interest and communities of practice. Communities of practice are defined around a knowledge domain that is core to the company’s strategy. Therefore, clear, ongoing deliverables are identified that contribute to Unilever’s business results. These deliverables can be knowledge deliverables (such as improved insights, training programmes, good practices and so on) and business deliverables (such as increased speed of implementation of businessimprovement projects, roll-out of specific innovations, safety improvements and the like). The people pillar is about the roles and responsibilities of CoP members. Members themselves are key experts, recognized as such both inside and outside the community. They should represent the right mix of background, geographical representation and local versus corporate resource. Equally important is the role of the activist. The activist ensures continued strategic alignment in the activities of the community. Typically, the activist position is a rotating role that all members can eventually fill. The people pillar also addresses the stakeholders and sponsors external to the community, but necessary to validate its existence and free up resources for the members. The operations pillar is centered on the way the community functions. It forms the basis for creating an open and trusting culture in which members feel safe to share and create. As part of its launch, each community defines these ground rules itself, including the ICT support needed to ensure effective ongoing communication and knowledge sharing. In order to prevent a community becoming isolated within the organization, the outcomes generated by the community need to be communicated to the rest of the organization. Likewise, inputs from the wider network need to be able to flow without restrictions. These challenges are addressed by the leverage pillar. The CoP identifies the broader network of stakeholders and ensures effective two-way communication is maintained. Another aspect of this pillar is the effective branding of the community within the organization.

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Leveraging community capabilities The Unilever Knowledge Management Group has designed community guidelines and training for CoP activists. The training course is aimed at raising awareness of the general benefits offered by communities and building an understanding of CoP terminology. The course offers practical insights about communities of practice and hands-on experience in tools and techniques in establishing and sustaining a community. Acting as a profit centre within Unilever, the KMG also works outside of the company. For instance, and as testimony to the quality of the way CoPs are set up in Unilever, the KMG has also provided training to ABN Amro and other multi-nationals. In addition, the KMG works closely with activists and champions who are in the process of setting up a community of practice. A champion identifies the need for networking and knowledge development in their part of the business. The next step is then to clarify what the objectives are, and whether setting up a CoP is the most effective way of realising these objectives. When this has been clarified, the champion looks to appoint an activist for the CoP. An initial brief is then specified, outlining the broad objectives of the community and the relevant stakeholders. This brief is further refined by the champion and other stakeholders. Potential community participants are suggested and invited to join. A first proposal for operational procedures and leverage of results is drawn up, the community kick-off meeting is planned, and the agenda and process for the meeting are carefully designed, based on a standardised approach and guidelines. During the kick-off meeting, which lasts between two and five days, CoP participants discuss the deliverables and potential ways of working within the community. The constituent elements of the four pillars described above are specified and tailored to the needs, focus and spirit of each community. Sessions on defining the role of the CoP are interspersed with team-building activities aimed at building trust and relationships between the participants. The KMG works closely with the activist to prepare them for their role, such that during and after the kick-off meeting they are confident in their ability to energise their community and help it to deliver results. However, the KMG also maintains contact with the activists, and the training material used by the KMG is adapted continuously according to the learning’s and needs of the activists and their communities. Once a CoP has been up and running for some time, a health check allows the company to assess whether the community is still on track. It could be that, due to changes in the organizational environment, a CoP needs to shift focus or include new members. A healthcheck questionnaire and the recommendations that result can help to identify strengths and gaps in the sustainability of a community. For example, after a number of years, one of 218



Unilever’s communities is looking to broaden its focus from sharing knowledge and good practices to generating new knowledge. Knowledge visioning, one of the KMG’s other offerings, can help the community to identify which areas of knowledge have the most potential value. The company also recognises that, once a CoP is no longer adding value to the business, it should be allowed to disband. However, it is important in such instances to recognise and celebrate the community’s achievements. A debrief workshop can be a useful tool to ensure that lessons learnt will be captured and transferred.

NOTES

Communities require substantial levels of investment, and as such should be seen to add significant value to the business. Therefore, valuation of community activities is embedded in community processes from the beginning, and is a continuous process that lasts from conception of a CoP to its closure. Various valuation approaches – ranging from gathering success stories and quotes of satisfied CoP ‘customers’, to causal tracking and balanced scorecards – are used to help a community of practice to continuously manage (identify and exploit) the added value of the its activities. Each recommendation a CoP makes requires appropriate resources and is therefore treated as an investment decision. The valuation results provide the basis for the business case underpinning the resulting recommendations. Two examples of communities of practice that have resulted in quantifiable value to the business are the Agronomy community and the NPI Buying communities (see sidebars). Seven years and counting Walking the fine line between the empowered ‘anarchy’ of a purposeful network, and the structure of a focused and result-oriented business team, the flexibility and speed of CoPs have resulted in very impressive results for Unilever over the past seven years. Ranging from efficiency improvement, increased innovation and improved risk management, the payback is many times higher than the investments in starting up and operating the communities. Currently there are several dozen CoPs in Unilever that are highly active. Communities originated in areas such as supply chain, technology and innovation – sectors in which the value of knowledge is explicitly recognised, and resources tend to be scarce. More recently communities have also emerged in areas like marketing and consumer insights, where knowledge is of a more tacit nature. Due to a high turnover and the tacit nature of knowledge, the urgency of sharing and leveraging knowledge in these areas is higher than ever. As such, communities of practice are an essential element in Unilever’s organizational culture, and will continue to be as the company strives to satisfy its customers’ needs, now and in the future.

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Question: Analyze the case of Unilever with light of principles learnt in Communities of Practice. Solution: Lesson learnt •

As CoPs bring together the most highly talented people in their area, it is often difficult for them to balance community participation with the demands of their day job. As such, it is critical to be clear about the investment needed and the resource implications;

•

Successful CoPs do not just happen; they need to be carefully designed and supported, with clear and measurable objectives and roles, and a solid operational plan;

•

Training CoP activists provides them with an understanding of CoP terminology and a common framework that can be applied across your organization. Training helps to impart practical insights about communities, specifically about what makes them work and how to generate the most business value;

•

You get only one chance to launch a community, so a carefully designed kick-off meeting is essential;

•

It is crucial that you maintain a balance between the benefits for participants, their departments and the broader organization;

•

Balance longer-term projects with quick wins. A quick win can help in motivating your participants (and their stakeholders) in the short run, but longer-term, highvalue projects are required for the company to benefit from the step-change improvements a community can deliver;

•

Avoid single-leader dependency. Stakeholders and champions will change, and the CoP needs to be able to survive these changes;

•

Do not sell communities as a separate, knowledge-based initiative, but as a more effective way of achieving tangible business results.

The Agronomy community Unilever is one of world’s largest processors of tomatoes. With products such as Ragu Pasta Sauces, Chicken Tonight, Knorr soups and sauces, and many more, Unilever’s tomato-processing plants are spread across the world. Seven years ago the Culinary division organised a knowledge workshop, bringing together experts in the field of tomato production and processing. Participants came from all over the world. Management, and indeed the experts involved, felt it was so important to exchange and share knowledge in the area that they decided to establish a community. The CoP that was formed remains active today. The following section offers an example of the value that the community has generated.

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The regions where tomatoes are grown and processed for Unilever are located in North America, South America, Australia and Europe. Some tomato-growing locations are situated in dry to very dry areas, and others in regions with more rainfall. In all areas, a sufficient water supply is essential for growth. Depending on the local situation, various types of irrigation systems are in use. In Brazil, plenty of water is available, unlike, for example, in Australia.

NOTES

In countries where water was scarce, Unilever worked with the local growers to develop highly sophisticated and efficient drip irrigation systems. Instead of spraying the fields overhead, the water was brought to the plants through a web of tubes, dripping water, pesticides and herbicides close to the plants. Besides water, pesticide and fungicide savings, the additional advantages turned out to be higher yields and less chance of disease. However, in areas where water was plentiful, over-irrigation led to moulds and the prevalence of bacteria. Information exchange between the experts in the Agronomy CoP, in addition to local technical support in Brazil, allowed Unilever to overcome these difficulties, and to the introduce drip irrigation systems across its tomato-growing network. The relatively high investment costs could be quickly paid back owing to the return on investment generated by significantly higher yields and the lower costs of fighting diseases. The fact that different experts from across the world had formed a CoP, developed professional trust and respect, and were fully empowered by the organization, resulted in a rapid and effective implementation, and the realization of considerable business benefits. The Agronomy CoP meets twice a year, each time in a different country. During each meeting, which lasts a couple of days, the CoP invites local growers to discuss cultivation problems and plans, often locally in the field or in the grower’s own business. Both the local growers and the Unilever agriculture managers appreciate this exchange of knowledge and experience. Both groups make grateful use of the tips and experiences they exchange in order improve the quality of the tomatoes and increase the yield. The NPI-Buying communities Within Unilever, Global Supply Management is divided into Production Items (e.g., raw materials, packaging materials) and Non-Production Items (NPI) (e.g., lease contracts, travel contracts, IT supplies, office supplies and market research). NPI is currently organized regionally, with regional targets. In the summer of 2002, a workshop was organized where representatives of all regions attended to discuss key issues and to identify must-win battles for global NPI. From this workshop, one of the global initiatives that emerged focused on communication, knowledge sharing and collaboration. One can easily imagine the enormous potential of savings that can be reached by aligning and standardizing the global buying programme of a company the size of Unilever.

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To encourage global collaboration and leverage cross-regional opportunities, the company decided to establish three global CoPs. Each community was to bring together a core team of NPI professionals to share expertise and good practice. As some activists had yet to be trained, the project consisted of two steps: first, training the global activists and potential regional activists-to be; second, launching all three global CoPs in parallel with each other. The CoP course was tailored to the specific NPI context and needs, with specific attention on the tools and techniques for a kick-off meeting that would follow straight after the course. After the course, the participants of all the CoPs arrived at the venue and the launch event began. The NPI CoPs were set up in three key areas: Engineering & Technical, Travel and Marketing. The CoPs are very active, both internally and in sharing with other communities. The NPI communities have since contributed to significant cost savings, not least in creating a common terminology. What’s more, new communities within NPI are emerging and being integrated with the global initiative. SUMMARY Knowledge management tools and techniques are used to enhance and enable knowledge generation, codification, transfer, generate knowledge to make knowledge available for others and also transfer knowledge to decrease problems with time and space when communicating in an organization. Content creation and management tools are used to structure and organize knowledge content for each retrieval and maintenance. Groupware and other collaboration tools are essential enablers of knowledge flow and knowledge-sharing activities among personnel. Data mining and knowledge discovery techniques can be used to identify emergent patterns that could not have otherwise been detected. Some of these techniques may provide valuable insights. Intelligent filtering agents are a KM technology that can help address the challenges of information overload by selecting relevant content and delivering this in a just-in-time and just-enough format. A knowledge repository will often be the most frequently used and most visible aspect of a KM technology. What is important is not so much the container but the content and how this content will be managed. Knowledge management technologies help support emergent phenomena involved in the creation, sharing, and application of valuable knowledge assets. 222



Knowledge management measurement is concerned with trying to select and/or formulate those concepts useful in measuring and influencing knowledge management performance. Measuring knowledge management (KM) is not simple. Determining KM’s pervasiveness and impact is analogous to measuring the contribution of marketing, employee development, or any other management or organizational competency. It is nonetheless a necessity if KM is to last and have significant impact in an organization. A number of fairly sophisticated KM measurement techniques are available now that can help assess how well an organization is progressing. These include benchmarking, IC rating and the balanced scorecard method.

NOTES

KM auditing is often the first step in any KM initiative because it serves to inventory what knowledge-intensive resources exist within a company. This provides snapshot of the “as is” or current state of the organization with respect to KM and helps in measuring progress toward organizational culture change and other KM goals. As KM field expands, organizations increasingly rely on “knowledge workers” to generate, classify, manage, and distribute tacit and explicit knowledge. The CKO represents the pinnacle position in a knowledge enabled organization. The unit presented the various opportunities that exist in various organizations employing KM professionals, classified based on the various organizational knowledge processes with clear picture of qualities and attributes required for the K-careers. Some selected case studies were given to know more about the KM practices and lesson to be learned from them. SHORT QUESTIONS 1. Why are intellectual assets difficult to measure? 2. Distinguish between content creation tools and content management tools. 3. Define data mining. 4. What is a chat room? 5. Define newsgroup and mailing lists. 6. What is the function of filtering tools? 7. Define KM measurement. 8. What is a tangible asset monitor? 9. Compare “efficiency” with “effectiveness”. 10. What is meant by balanced scorecard? 11. Define ‘knowledge audit’. 12. What are the objectives of K-audit? 13. What is process mapping? 14. What are the responsibilities of a CKO? 15. Who is a chief learning officer (CLO)?

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LONG QUESTIONS 1. Discuss the pros and cons of the major technologies used in the knowledge creation and capture phase. 2. Discuss the pros and cons of technologies used in the knowledge-sharing and dissemination phase. 3. Describe the pros and cons of major technologies used in the knowledge acquisition and application phase. 4. What are the major categories of data mining technologies and what sorts of patterns would this technology detect? 5. Describe an application of blog technology within an organization and its potential benefits? 6. Describe some of the ways in which unstructured content may be managed? 7. What are some best practices in the management of the useful lifecycle of knowledge content? 8. How would you categorise the different forms of groupware or collaboration technologies? How would you adopt a cost benefit approach to such a technology selection decision? 9. What role can a wiki play in promoting group collaboration? What advantages does a wiki offer when compared to a discussion forum? 10. Describe push and pull technologies that can be used in conjunction with knowledge repositories. What are some of the artificial intelligence technologies that can play a role in knowledge management? 11. What role do e-learning tools play in KM? 12. How can intelligent agents help knowledge workers find relevant knowledge content? 13. Describe the components of K-audit. 14. What are the different classifications of KM career? Explain each one of them briefly. 15. ‘Measuring knowledge management is not simple’ – Do you agree with this statement? If not, what are the approaches needed to measure KM? 16. Give your detailed analysis of balanced scorecard management system. 17. What are the duties and skills required for the positions of (i) K-architect, (ii) Kstrategist and (iii) K-engineer?

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APPENDIX Knowledge Management Glossary

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After Action Review (AAR). A systematic process to extract the learning from an event or activity. The process addresses the questions: What should have happened? What actually happened? What lessons are there for the future? Answernet. A service provided by a network of experts who answer questions posed online. Artificial Intelligence (AI). A set of computer techniques that make the computer appear to behave with a degree of human intelligence. Rather than the procedural way of programming, it draws on inferences and rules to guide its actions. Expert systems, intelligent agents and natural language search are examples of the use of AI techniques in knowledge management. BBS. See Balanced Business Scorecard. Now a less common abbreviation than BSC. Balanced Scorecard. A performance measurement system that incorporates a balanced set of measures, both financial and non-financial. It adds customer, internal processes and innovation and learning indicators to financial ones to provide a more balanced view. Contrast with the more specific intellectual capital measurement methods. Benchlearning. A structured approach whose focus is on learning from others to create distinctive improvements. Developed by Bengt Karlof and colleagues, it overcomes the often narrow focus of benchmarking on quantitative comparisons, which downplays the key role of knowledge transfer. Benchmarking. A systematic process for comparing the performance of an activity or process across a range of organizations or departments. Identifying gaps in performance leads to on to benchlearning and learning good practice from high performers. Benefits Tree. A diagrammatic depiction of cause-effect relationships from knowledge processes to business outcomes. Helpful in making the business case for knowledge management. See also the Benefits Tree tool. Best Practice. The distillation of accumulated wisdom about the most effective way to carry out a business activity or process. Since ‘best’ is highly subjective and context dependent, as well as implying that no further improvements are possible, many people now prefer the term good practice. BSC. See Balanced Business Scorecard.

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Blog (originally Web log). A string of thoughts of an individual shown in chronological sequence on a Web page, often with hyperlinks to sources that have stimulated his or her thinking. A well established KM blog can be seen at David Gurteen’s website, while the AOK website lists a selection of KM blogs. Although often dismissed as a gimmick some people see blogging as grass-roots KM, alongside storytelling. Others suggest that it perpetuates knowledge silos and that a Wiki is more appropriate. Bulletin Board. See Message Board Case Based Reasoning (CBR). An application of AI techniques, where solutions to a given problem are sought through a reasoning process that draws analogies with similar problems whose solution is already known. Caves and Commons. Denotes two main types of physical working area: a cave is a private area for concentrated thinking; commons are open areas for socialization and meeting rooms for team discussions. Design of working space can significantly enhance the productivity of knowledge workers. Chat. See Instant Messaging. Chief Knowledge Officer (CKO). A senior executive, often at board level with responsibility for an organization’s knowledge agenda. Unlike other officers, they may not manage a knowledge ‘function’, although they may directly manage a small knowledge team, and hold budget responsibilities. Classification. A key process in the knowledge sharing cycle. Documents are classified and indexed according to their core terms and concepts. Increasingly computer systems provide a level of automation of this process, using natural language or statistical methods. CKO. See Chief Knowledge Officer. CMS. See Content Management System. Codification. See Knowledge Codification. CoI. See Community of Interest. Combination. One of four basic knowledge conversion processes described by Nonaka and Takeuchi. Combination is the bringing together of different sources of explicit knowledge, and reconfiguring it into new explicit knowledge. Contrast this with Externalization, Internalization and Socialization. Community. A community of interest or practice. The focus of a community is usually part of a website that typically provides message boards and other conversational facilities (such as discussion lists and instant messaging as well as a library of online 226



resources. Some people also refer to communities of purpose or communities of commitment.

NOTES

Community of Interest (CoI). A group of people who share knowledge and experience around a common interest. Driven more by learning and less on outcomes than a Community of Practice. Community of Practice (CoP). A group of people who share and develop their knowledge in pursuit of a common purpose or task, even though they do not necessarily work in the same department or organization.. Concept Mapping. A visual representation of core concepts showing the relationships between them. A typical concept map comprises a set of nodes or bubbles (the concepts) with arrowed links between them (the causal relationships). One of the several types of knowledge mapping. Content Analysis. Analysis of a body of content (text) into its key concepts. As well as a method of discerning trends, this technique is used to generate keywords and thesaurus terms to improve subsequent text search and retrieval. The latter result is increasingly achieved through the use of automated classification systems. CoP. See Community of Practice. Content Management System (CMS). A computer system that makes it easier to develop enterprise portals and websites, by separating the management of content from its presentation (display). Blocks of content are tagged with metadata and other attributes and held in a content database. Web pages are generated (often ‘on-the-fly’) by accessing content from the database and inserting it into the relevant ‘placeholders’ on Web page templates. Since a single block of content may appear on many Web pages, the task of maintenance and updating is simplified. Compared to document management systems the focus of a CMS is individual content blocks. CRM. See Customer Relationship Management. Customer Capital. A measure of the intangible value that accrues through customer relationships, including size of customer bases, knowledge of customers and their needs, and related intellectual property such as brands. A component of intellectual capital. Customer Relationship Management (CRM). An approach that gathers and uses knowledge of customers’ buying habits and preferences in order to strengthen the ongoing relationship for mutual benefit. Customer knowledge comes out as the most important knowledge to manage in many KM surveys. Data Mining. A computer technique for extracting meaningful knowledge from masses of data. Using artificial intelligence methods it identifies unanticipated patterns 227


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by considering the interaction of many more variables than is achievable by humans. Contrast with text mining. Decision Diary. A diary in which decisions are recorded, together with the assumptions and reasoning behind them. They are used to derive lessons and record knowledge that will help future decision-making. Digital Rights. The rights and conditions of use for a piece of digital content. These rights may be part of the product’s wrapper, or may be embedded in the product as part of a watermark to reduce illegal copying. Discussion List. A mechanism used by to share information and knowledge using a single email address to communicate to all members of a given list. Typically all messages generated during one day are grouped together and sent as a single email in a ‘digest’. Desktop Conferencing. Videoconferencing using a desktop PC. A small camera (webcam) is usually mounted on top of the user’s display screen. Evidence suggests that this often transfers expertise better than simply using email or documents. Document Management System. A computer-based system for storing and retrieving documents held in a variety of formats, including scanned images of paper documents. Many provide version control and audit trails of changes and usage. The distinctions between document management, content management and records management systems are increasingly blurring. EDRMS. Electronic (sometime Enterprise) Document and Records Management System. EIP. See Enterprise Information Portal. Enterprise Information Portal (EIP). Strictly, an entry point (home page) into an organization’s intranet, although the term now often refers to the intranet itself and its content. Users have a personalized starting page that gives them a single point of access to enterprise information, wherever it is held. Expert System. A common class of AI computer system that applies the logic and domain knowledge it has acquired from a human ‘expert’. A typical expert system has three main parts - a knowledge base (that contains the rules), an inference engine (that interprets the situation against the rules) and a human interface. Explicit Knowledge. Knowledge which is codified and articulated. It appears in the form of documents, procedures and in databases. Externalization. One of four basic knowledge conversion processes described by Nonaka and Takeuchi. It is the conversion of tacit to explicit knowledge, articulating thoughts through language or diagrams.

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Expertise Directory. A database of personnel and their skills that allow users to search for people with specific skills or relevant project experience. Often referred to as ‘Yellow Pages’.

NOTES

Expertise Profiling. The identification and classification of personal knowledge and skills. This may be done through manual completion of data forms or by computer systems that infer people expertise according to what they write in emails and documents. The output of the process may be an expertise directory or a database that is used in automated question and answer systems. Extensible Markup Language. See XML. Extranet. A portion of an organization’s intranet that is opened up for external Internet access on a selective basis e.g. for customers to access specific areas following input of a password. Frequently Asked Questions (FAQs). A list of questions that are most frequently asked or are anticipated by website or intranet users, together with their answers. Information providers use this technique to minimize the number of recurring queries and calls. Some organizations use the term AAQs - actually asked questions - since many writers of FAQs anticipate what might be asked or what questions their content answers. Fuzzy logic. A technique used in artificial intelligence that works on a balance of probabilities for rules, rather than precise matching of data or patterns. Examples of its use are found in text retrieval and case based reasoning applications. Groupware. Computer software tools that support collaborative working. Lotus Notes was the archetypal groupware software, but many groupware facilities are now provided on the Internet e.g. bulletin boards, discussion forums, instant messaging. The term is generally falling into disuse compared to ‘collaboration software’. Human Capital. The competencies, know-how, capabilities and experience possessed by individuals. One of the three main components of Intellectual Capital. The others are Structural Capital and Customer Capital. Information Resources Management (IRM). The techniques of managing information as organizational resources. They include the identification of information, its classification and ways of valuing and exploiting it. IAM. Intellectual asset management or Intangible Assets Monitor. IC. See Intellectual Capital. IC Measurement. The measurement of the Intellectual Capital of an organization. Over the last few years there have been significant developments in IC measurement methods to help managers focus on knowledge and other intangible sources of wealth creation.

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IC Multiplier. The ratio of Structural Capital / Human Capital. It indicates how well an organization leverages its human capital through it structural capital. A higher ratio indicates good leverage and minimizes the loss of knowledge when people leave. IC Reporting. The reporting of an organization’s intellectual capital in a similar way that financial results are reported. Typically this is done as an annual IC supplement to the formal accounts. Implicit knowledge. Knowledge that is not explicitly identified but can be inferred from its context or packaging. An example is the knowledge held in software that can be deduced by reverse engineering. Information Audit. See Knowledge Audit. Instant Messaging. An Internet or intranet facility in which users type messages into a window that is simultaneously viewed by other participants in that chat room or area. While commonly associated with informal social groups, the tool is a useful adjunct for synchronous knowledge exchange in a corporate context, for example as a way of interaction during a ‘webinar’. Intangible Assets. Assets that is not physical or tangible in nature. They are therefore more difficult to identify and count as discrete entities. Knowledge is one type of intangible asset. Intangible Assets Monitor (IAM). A method of IC Measurement developed by Karl Erik Sveiby for recording intangible assets. It divides intangible assets into three main categories - competencies, external structure and internal structure. Indicators are divided into four distinctive groups - growth, renewal, efficiency and stability. Intellectual Capital (IC). The intangible assets of a company not normally valued on the balance sheet. It is roughly - but not exactly - the difference between the market and book value of a company. It is often divided into the categories of human capital, customer capital and structural capital. Some schemes separate out intellectual property, while others use the broader term relationship capital instead of customer capital. Intellectual Property (IP). Intellectual capital that is identifiable and protect able in law. It includes copyrights, patents, designs, trademarks etc. Internalization. One of four basic knowledge conversion processes described by Nonaka and Takeuchi. Internalization is conversion of explicit to tacit, for example through applying explicit knowledge and learning from the experience. Contrast with Externalization, Combination and Socialization. Intranet. An internal internet. In other words an internal computer network that runs the Internet protocol (TCP/IP). Most intranets have a computer ‘gateway’ to the wider 230



(external) Internet and deploy a ‘firewall’ to prevent unauthorized access to a company’s information.

NOTES

IRM. See Information Resources Management. Just-in-time Knowledge. The concept of delivering knowledge to an individual just at the time that they need it to carry out a task. This overcomes the problem of information overload, where knowledge not immediately needed may be forgotten or ignored. Mechanisms that help are alerting systems linked to computerized procedures or what a knowledge worker is typing into their computer and natural language retrieval. K-Log (Knowledge Log). A blog (weblog) whose subject is knowledge. KM. See Knowledge Management. KM Assessment. An assessment of the quality and capabilities of knowledge management within an organization. A typical assessment tool will have a set of questions against which employees score the level of actual and desired capabilities. KM Maturity. The level of adoption of KM within an organization. This is gauged by reference to a KM maturity model that looks at stages of maturity from ad-hoc to fully embedded and integrated into the organization’s core activities. Know-bot (Knowledge robot). An intelligent agent that gathers or exchanges knowledge from other agents or computer systems. Knowledge Analyst. A person or business that interprets the needs of a knowledge seeker and finds the most suitable sources. May also act as a knowledge broker. Knowledge Archaeology. The process of rediscovering an organization’s historical knowledge that has become lost. Knowledge Asset. An identifiable piece of knowledge that has some intrinsic or extrinsic value. Knowledge Audit. The systematic analysis of an organization’s information and knowledge entities and their key attributes, such as ownership, usage and flows, mapped against user and organizational knowledge needs. The terms information audit, knowledge audit, knowledge inventory and knowledge mapping are often used synonymously. Knowledge Base. A computer held database that record knowledge in an appropriate format for later extraction. It may take various forms depending on whether it supports an expert system or contains documents and textual information for human retrieval. Knowledge Based System (KBS). A computer system that draws on AI techniques or knowledge bases for its operation. Examples include expert systems and neural networks.

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Knowledge-based product. A product in which knowledge is a major component. Contrast with a knowledge product, which is wholly knowledge. Knowledge Broker. An intermediary that connects knowledge seekers to knowledge providers. It may involve brokering a deal and retaining anonymity between buyer and seller until a suitable stage of negotiation. Some overlap with a knowledge analyst. Knowledge Business. A business whose primary outputs are knowledge products and services. Knowledge Café. Informal meeting area for the exchange of knowledge. Caf´s can be virtual meeting rooms as well as real ones. Knowledge Capital. The capital of an organization that is not physical or financial. Similar to intellectual capital, this is the term used by Paul Strassmann and Baruch Lev to describe the results of their methods that start with the capital reported in a company’s balance sheet. Knowledge Centre. A central function for managing knowledge resources. Often developed around a corporate library, a typical knowledge centre will manage both physical and virtual resources - documents, databases, intranet content, expertise directories etc. Knowledge Codification. The process of articulating knowledge in a more structured way. It typically involves eliciting tacit knowledge from an expert, making it explicit and putting it into a template and format that aids dissemination and understanding. High levels of codification are found in computer software and mathematical formulae. Knowledge Commercialization. The process of creating tradable goods and services from a body of knowledge. Knowledge Cycle. A sequence of core knowledge processes that result in new knowledge. There are two main cycles - the innovation cycle and the knowledge sharing cycle. Knowledge Economy. An economy in which knowledge is one of the main factors of production and constitutes the major component of economic output. This may occur directly through knowledge products and services or indirectly where knowledge is an added-value part of other products and services. Contrast with agricultural and industrial economies. Knowledge Elicitation. The process of eliciting knowledge from a human expert in order to codify it into some form of explicit knowledge base or rule based computer system (expert system). Knowledge Inventory. A list or database of knowledge entities - their sources, users and uses. It may be the output of a knowledge audit. 232



Knowledge Leakage. The loss of critical or damaging knowledge from an organization to the outside world (e.g. competitors, unauthorized personnel), either deliberately or unintentionally, when it should remain inside.

NOTES

Knowledge Management (KM). The explicit and systematic management of vital knowledge and its associated processes of creating, gathering, organizing, diffusion, use and exploitation in pursuit of organizational objectives. Knowledge Mapping. The process of identifying core knowledge and the relationship between knowledge elements. A map may be portrayed in many visual formats, such as a hierarchical tree or a node and link diagram. It is typically a task carried out as part of a knowledge audit. Knowledge Market. A marketplace for the buying and selling of knowledge. Online knowledge markets are sometimes referred to as knowledge e-marketplaces. They commonly allow the posting of knowledge needs and knowledge offers, and may conduct sales by auction. Knowledge Narrative. The articulation of value of and organization’s products and services to customers and how knowledge resources are used to achieve this value. It derives from the organization’s vision and strategy and describes its KM ambitions. It often forms part of an IC report. Knowledge Networking. The process of sharing and developing knowledge through human and computer networks. Knowledge Object. A piece of knowledge held in a well-defined and structured format, such that it is easy to replicate and disseminate. Although predominantly in the form of explicit knowledge, it may contain some element of human knowledge. Knowledge Practice. A specific method or technique used to manage or process knowledge. Several methods may be used within a knowledge process. See the list of common practices. Knowledge Process. A broad knowledge activity often performed at an aggregated level. Examples are knowledge gathering, sharing and dissemination. Knowledge moves from one process to another as part of a knowledge cycle. Knowledge Product. A product which consists almost entirely of information or knowledge. Knowledge Recipe. The transformation processes that uses existing knowledge assets as inputs and combines them in distinctive ways to create useful outputs and outcomes. Knowledge Refining. The process of filtering, aggregating and summarizing knowledge drawn from a wide range of resources. 233


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Knowledge Repository. A store of knowledge. While the term typically refers to explicit forms of knowledge, such as documents and databases, it can also refer to humanheld knowledge. Knowledge Value Chain. A sequence of knowledge processes including creation, organizing, dissemination and use that create value from knowledge stocks. Knowledge Worker. An individual whose primary contribution is through the knowledge that they possess or process. This contrasts with workers whose work is predominantly manual or following highly specified procedures with little scope for individual thought. Knowledge Wrapper. Information associated with a knowledge object that accurately describes the contents within. It holds metadata in a standard format and may hold encrypted digital rights information. Learning Network. A network of individuals who share knowledge for the primary purpose of personal development and learning. A specific example of a Community of Interest. Learning Organization. An organization which has in place systems, mechanisms and processes that are used to continually enhance its capabilities and those who work with it or for it, to achieve sustainable objectives - for themselves and the communities in which they participate. Mapping. See Knowledge Mapping or Social Network Mapping. Message Board. An area on a website where messages can be exchanged and viewed by a workgroup or community. Sometimes referred to as a bulletin board. The conversational interaction via the Web is sometimes called Web conferencing. Metadata. Data about data. A structured piece of data that describes the contents of a database record. One common metadata format is that of the Dublin core (page XXX) that defines metadata fields for bibliographic databases. Meta-knowledge. Knowledge about knowledge. Knowledge inventories, knowledge maps and expertise directories are examples of meta-knowledge. Mind Mapping. A visual method of organizing ideas. In most mind mapping systems the ideas branch out from a central point. In turn, each branch can have additional branches or links to other mind maps. A specific form of concept mapping. Natural Language Processing (NLP). The ability of a computer application, such as a search engine to accept ordinary language input rather than highly specified instructions. It processes text through analysis of syntax and semantics.

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Neural Networks. An artificial intelligence technique that mimics the operation of the human brain. It consists of a network of individual neurons that are triggered according to the intensity of various inputs and their relative ‘weights’. It adjusts these weights according to the quality of the outcome for a given set of inputs. In other words, a neural network learns from experience.

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Object-based Knowledge. Knowledge that is held in discrete entities (knowledge objects). Contrast with human-held knowledge (in people’s heads). Online Community. A community of interest or practice that uses computer-based collaboration facilities (such as message boards, discussion lists and chat, to share knowledge. Ontology. An extension to a taxonomy that adds specifications of relationships between entities plus a set of automatic inference rules and associated actions. Typical relationships include “instance of” and “made of”. Organizational Learning. The processes by which an organization ‘learns’, so as to share best practice and avoid repeating mistakes. The learning may be embedded in individuals or in organizational systems and organizational memory. Closely related to the learning organization (an organization which has good organizational learning processes). Organizational Memory. A place, such as a database or a document, where organizational knowledge is stored, and is readily accessible for reuse. Without a systematic storing of such knowledge, it is easily lost as people move around or leave the organization. Organizational Memory. The core knowledge of an organization’s past includes project histories, important decisions and their rationale, key documents and customer relationships. Recalling into organizational memory avoids ‘reinventing the wheel’ and repeating mistakes. Precision (of search engine). The proportion of documents retrieved in a search that is relevant to the searcher’s intention as opposed to results that are irrelevant (or ‘noise’). Project History. The main activities and decisions taken during a project, recorded in a way that aids knowledge sharing and derives lessons for similar projects in the future. Portal. The common term for Enterprise Information Portal. A portal is a single point of entry on the Web or an intranet to a wide range of information and knowledge resources and tools that enable a person to do their job more effectively. c.f. common definition of “gateway”.

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RDF. See Resource Description Framework. Reach. The extent to which knowledge is accessible in various locations. The Internet extends reach, as does the use of portable computers and mobile telephones. Contrast with Richness. Recall (of search engine). The proportion of documents from the total that are available that are retrieved as the result of a search. Contrast with Precision. Richness. The depth of knowledge, such as contextual knowledge, that enhances a piece of core knowledge. Multimedia also adds richness by giving the viewer more visual information and cues. Contrast with Reach. Richness. Resource Description Framework (RDF). A framework developed by W3C for developing metadata standards for WWW resources. It brings together in one place metadata activities for resources such as site maps, content ratings, search engine data collection and digital library collections. The resource descriptions use XML as the interchange language. Schema. A taxonomy (classification) of knowledge or information. Common terms are used to describe an organization’s knowledge domains which are categorized into hierarchies and related terms. Search Engine. A piece of software or a service that indexes pages from the Web and lists those that match or closely match a user’s search terms. Results are ranked by relevance or other factors and include items from sources all over the Web. One of the growing problems is the ‘hidden’ Web, content that is not indexed because it is generated on the fly or held in databases. It is estimated that over four fifths of Internet content is now hidden. Share Fair. An event especially constructed to encourage the interchange of knowledge. Typically organized as a conference and exhibition with booths. Semantic Network. A method of representing structured knowledge. It consists of nodes and links, where the nodes are concepts or entities and the links represent relationships and associations among the concepts. An ontology can be viewed as domain knowledge represented in the form of a semantic network. Semantic Web. The addition of semantic constructs (ontological elements) to World Wide Web resources to create semantic networks accessible via the Internet. The Semantic Web is seen by some as the next evolution of the World Wide Web (the ‘intelligent’ Web). Socialization. One of four basic knowledge conversion processes described by Nonaka and Takeuchi. Socialization is conversion of tacit knowledge to other tacit

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knowledge, typically by group processes where people learn together through a shared experience. Contrast with Externalization, Internalization and Combination.

NOTES

Stickiness. A property of knowledge that is difficult to transfer, i.e. it is heavily dependent on personal knowledge and/or context. The term is also applied to a website that encourages visitors to spend significant time there and return repeatedly. Portal sites and search engines are very ‘sticky’. Storytelling. The use of stories in the organizational context, as a way of sharing knowledge and helping the process of learning. Structural Capital. A measure of the intangible value of the firm embedded in its processes, systems and other non-human elements. A component of Intellectual Capital. Tacit knowledge. Knowledge that is not codified but held in people’s heads. Intuitive, experiential, judgmental and context sensitive, it may be difficult to articulate. Contrast with explicit knowledge. Tag. Instruction for an application or formatting tool, such as an Internet browser. Tags are used in markup languages (HTML and XML). Tagging content is a key activity in implementing Content Management Systems. Taxonomy. A system of classification. A typical taxonomy is a hierarchy of terms (nodes), where lower level terms are more specific instances of higher level ones. Taxonomies in which a term can appear in more than one branch are called ‘poly-hierarchical’. Contrast with Thesaurus and Ontology. Thesaurus. A controlled vocabulary of terms for a corpus of information. An extension of a taxonomy that includes rules on vocabulary usage for document classification e.g. “preferred terms”, “synonym of”, “belongs to”, “used for” etc. Topic Map. An ISO standard (ISO 13250) for describing relationships of nodes in an ontology independent of its underlying resources. Associations and Occurrences are key constructs in the XTM (XML Topic Map) standard. Text Mining. Extracting the essential concepts and meaning from large amounts of textual information. The result of text mining a single document and producing a summary which includes some of its key sentences. Typically, all the main concepts of a large document can be summarized in less than twenty per cent of its original size. Videoconferencing. Communications over an electronic network using video. Systems range from desktop units on PCs (desktop conferencing) to dedicated systems that use cameras and monitors in a conference room setting.

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Virtual Organization. An organization whose participants are geographically separated but who work together through online communications. Less commonly, the term refers to a temporary organization or network that is created for a specific purpose, but whose members remain independent. Weblog. The full term for Blog. Webinar (Web seminar). A presentation delivered over the Web using videoconferencing. Wiki. A collaboration tool that allows multiple authors to create and update Web pages. KMWiki is an example of a Wiki devoted to KM. Contrast with a blog which is authored by an individual. XML (eXtensible Markup Language). A Web-based markup language that allows a wide range of user-defined tags. If a community uses a common XML schema, then structured information can be shared between computer applications. ‘Yellow Pages. A colloquial term for an expertise directory, since entries are organized by category rather than by name.

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MBA Notes Knowledge Management

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