Chapter 11—Enterprise 11—Enterprise Resource Planning Systems
TRUE/FALSE
1. The primary primary goal of install installing ing an ERP system system is reducing reducing system system maintenan maintenance ce costs. costs. ANS: F 2. The recommended recommended data architecture for an ERP includes separate operational operational and and data arehouse data!ases. ANS: T ". A closed closed data!ase data!ase architectu architecture re shares shares data data easily easily.. ANS: F #. ERP systems systems support support a smooth smooth and seamless seamless flo of informat information ion across across organi$at organi$ations ions.. ANS: T %. &'AP stands stands for for on(line on(line applicatio application n processi processing. ng. ANS: F ). The primary goal of installing an ERP system is achie*ing !usiness !usiness process process reengineering reengineering to impro*e impro*e customer ser*ice+ reduce production time+ increase producti*ity+ producti*ity+ and impro*e decision(ma,ing. ANS: T -. ay(to(day ay(to(day transa transactio ctions ns are stored stored in the operat operationa ionall data!ase. data!ase. ANS: T /. ata mining mining typical typically ly focuses focuses on the the operatio operational nal data!as data!ases. es. ANS: F 0. ompanies ompanies are more more li,ely to modify modify an ERP to accommo accommodate date the company company than than to modify company company processes to accommodate accommodate the ERP. ANS: F 1. 3f a chosen ERP cannot cannot handle handle a specific specific company company process process !olt(on !olt(on softar softaree may !e a*aila!le. a*aila!le. ANS: T 11. 11. ore applicat applications ions are also also called called &'AP &'AP.. ANS: F
12. The client4ser*er client4ser*er model is a form form of netor, netor, technology in hich user computers+ computers+ called clients+ clients+ access ERP programs and data *ia a host co mputer called a ser*er. ANS: T 1". A data arehouse arehouse is a relational or multi(dimensional multi(dimensional data!ase that may re5uire hundreds hundreds of giga!ytes giga!ytes of storage. ANS: T 1#. rill(do rill(don n capa!ility capa!ility is an &'AP &'AP feature feature of data data mining mining tools. tools. ANS: T 1%. Supply(chain management management softare softare is a type of program that supports efforts relati*e relati*e to mo*ing mo*ing goods goods from the ra material stage to the customer. ANS: T 1). 3n to(tier to(tier architect architecture+ ure+ the data!as data!asee and applicatio application n functions functions are separate separated. d. ANS: F 1-. Slicing Slicing and dicing dicing permits permits the disaggreg disaggregation ation of data data to re*eal underly underlying ing details. details. ANS: F 1/. ata entere entered d into into the data data arehou arehouse se must must !e normal normali$ed i$ed.. ANS: F 10. &'AP includes decision support+ modeling+ information retrie*al+ and hat(if hat(if analysis. analysis. ANS: T 2. Efficient Efficient supply supply(chain (chain managemen managementt pro*ides pro*ides firms ith a compet competiti*e iti*e ad*antag ad*antage. e. ANS: T 21. The !ig(!ang approach in*ol*es in*ol*es con*erting con*erting from old old legacy systems systems to the the ne ERP in one implementation step. ANS: T 22. 3n a to(tier to(tier architecture architecture approach is used primarily for ide area netor, 67AN8 67AN8 applications. ANS: F 2". ata cleansing cleansing is a step performed !y e9ternal auditors to to identify and repairing in*alid data data prior to to the audit. ANS: F
MULTPLE C!"CE
1. oals oals of ERP ERP include include all all of the follo folloing ing e9cep e9ceptt a. impr impro* o*ed ed cus custo tome merr ser* ser*ic icee !. impro*ements of legacy systems systems c. redu reduce ced d pro produ duct ctio ion n tim timee d. incr increa ease sed d prod produc ucti tion on ANS: ; 2. ore ore app appli lica cati tion onss are are a. sale saless and and dist distri ri!u !uti tion on !. !usiness planning planning c. shop shop floo floorr cont control rol and logist logistics ics d. all all of of th the a!o a!o*e *e ANS: ". ata arehousi arehousing ng proces processes ses does not include include a. model odelin ing g dat data !. condensing data c. e9tr e9trac actting ing da data d. tran transf sfor orm ming ing data data ANS: ; #. 7hich of of the folloing folloing is is usually usually not part part of an ERP
and applications+ and the third is for 3nternet access. d. The data!ase data!ase and and applicatio application n functions functions are separa separate te in the three(ti three(tier er model. model. ANS: /. 7hich statement statementss a!out a!out data areho arehousin using g is not correct= correct= a. The data data arehous arehousee should should !e separa separate te from the operat operational ional system. system. !. ata cleansing is a process process of transforming data data into standard form. c. rill(do rill(don n is a data(m data(minin ining g tool tool a*aila!le a*aila!le to users users of &'AP &'AP.. d. Normali$a Normali$ation tion is an re5uir re5uirement ement of of data!ases data!ases included included in in a data arehous arehouse. e. ANS: 0. 7hich statement statement a!out a!out ERP ERP install installatio ation n is least least accurate= accurate= a. For the the ERP to !e succes successful sful++ process process reengine reengineering ering must occur occur.. !. ERP fails !ecause !ecause some important !usiness !usiness process is not not supported. c. 7hen a !usin !usiness ess is di*ers di*ersified ified++ little little is gained gained from ERP insta installat llation. ion. d. The phased( phased(in in approach approach is is more suited suited to to di*ersifi di*ersified ed !usiness !usinesses. es. ANS: 1. 1. 7hic 7hich h stat statem emen entt is true true== a. ERPs ERPs are are infin infinit itely ely sca scala la!l !le. e. !. Performance pro!lems usually usually stem from technical pro!lems+ pro!lems+ not !usiness process process reengineering. c. The !etter !etter ERP ERP can can handle handle any pro!lems pro!lems an organi$at organi$ation ion can can ha*e. ha*e. d. ERP systems systems can can !e modifi modified ed using using !olt( !olt(on on softar softare. e. ANS: 11. 11. Audito Auditors rs of ERP system systemss a. need need not orry orry a!ou a!outt segreg segregati ation on of dutie duties. s. !. may feel that the data arehouse arehouse is too clean and free from errors. errors. c. find find indep independ endent ent *eri *erific ficati ation on easy easy.. d. need not not orry orry a!out a!out system system access access since the ERP determines determines it. it. ANS: ; 12. 12. 'ega 'egacy cy syst system emss are are a. old manu manual al system systemss that that are stil stilll in place place.. !. flat file mainframe systems de*eloped de*eloped !efore client(ser*er client(ser*er computing !ecame standard. standard. c. sta!le sta!le data data!as !asee system systemss after after de!ugg de!ugging ing.. d. ad*anc ad*anced ed syste systems ms ithou ithoutt a data areho arehouse use.. ANS: ; 1". A data data mart art is is a. anothe anotherr name name for a data data areho arehouse use.. !. a data!ase that pro*ides pro*ides data to an organi$ationost ERPs are !ased !ased on hich hich netor, netor, model= model= a. peer to to pe peer
!. client(ser*er c. ring to topology d. !us to topology ANS: ; 1%. &n(line &n(line transactio transaction n processin processing g programs programs a. are !olt(o !olt(on n programs programs used ith commercial commercially ly a*aila! a*aila!le le ERSs. ERSs. !. are a*aila!le in to models?to(tier models?to(tier and three(tier. three(tier. c. handle handle large large num!er num!erss of relati*ely relati*ely simple simple transac transactions tions.. d. allo allo users users to analy$e analy$e comple9 comple9 data data relati relationsh onships. ips. ANS: 1). 1). Supply Supply chai chain n manage managemen mentt softa softare re a. is typical typically ly under under the the control control of e9ternal e9ternal partne partners rs in the the chain. chain. !. lin,s all of the partners partners in the chain+ including including *endors+ carriers+ third(party third(party firms+ and information systems pro*iders. c. cannot cannot !e !e integr integrate ated d into into an o*era o*erall ll ERP ERP. d. none none of the the a!o a!o*e *e ANS: ; 1-. 1-. The setu setup p of a data data areh arehous ousee includ includes es a. mode modeli ling ng the the data data !. e9tracting data from operational operational data!ases c. clea cleans nsin ing g the the data data d. all all of of th the a!o a!o*e *e ANS: 1/. 1/. E9trac E9tractin ting g data data for for a data data areho arehous usee a. cannot cannot !e done done from from flat flat file files. s. !. should only in*ol*e in*ol*e acti*e files. c. re5ui re5uires res tha thatt the the files files !e out of ser* ser*ice ice.. d. follo folloss the the cleans cleansing ing of data. data. ANS: 10. ata clean cleansing sing in*ol* in*ol*es es all of the the folloin folloing g e9cept e9cept a. filter filtering ing out out or repa repairi iring ng in*al in*alid id data data !. summari$ing data for ease of of e9traction c. transformi transforming ng data into standard standard !usiness !usiness terms d. format formattin ting g data data from from lega legacy cy syste systems ms ANS: ; 2. Separating the data arehouse arehouse from the operations data!ases occurs occurs for all of the folloing folloing reasons reasons e9cept a. to ma,e ma,e the the managem management ent of of the data!ases data!ases more economica economicall !. to increase the efficiency efficiency of data mining processes processes c. to integrat integratee legacy system system data into into a form that that permits permits entity( entity(ide ide analysis analysis d. to permit permit the integ integratio ration n of data from from di*ers di*ersee sources sources ANS: A
S!"RT A#S$ER
1. efin efinee ERP ERP. ANS: Enterprise resource planning systems are multiple module systems designed to integrate the ,ey processes in an organi$ation?order organi$ation?order entry+ entry+ manufacturing+ manufacturing+ procurement+ human human resources+ etc. 2. efine efine the term term @core @core applicat applications ions and gi*e gi*e some some e9ample e9amples. s. ANS: ore applications are those applications that support the day(to(day acti*ities of the !usiness+ e.g.+ sales+ distri!ution+ shop floor control+ logistics. ". efine efine &'AP &'AP and gi* gi*ee some some e9ample e9amples. s. ANS: &n(line analytical processing 6&'AP8 includes decision support+ modeling+ information retrie*al+ ad hoc reporting and analysis+ and hat(if analysis+ e.g.+ determining sales ithin each region+ determining relationship of sales to certain promotions. #. 7hat 7hat is is @!ol @!olt(o t(on n softa softare= re= ANS: ;olt(on softare is softare produced !y third(party *endors hich can !e added onto an ERP to pro*ide function not not !uilt into the ERP. ERP. %. 7hat 7hat is S> S> sof soft tar are= e= ANS: Supply(chain management softare is designed to manage the acti*ities that get the product to the customer. This softare typically handles procurement+ production scheduling+ order processing+ in*entory management+ etc. ). 7hat 7hat is is a dat dataa are areho hous use= e= ANS: A data arehouse is a relational or multi(dimensional data!ase that ser*es as a central archi*e of inacti*e+ completed data from !oth ERP and legacy systems. 3t is created to permit e9tensi*e access capa!ility+ including data mining. -. 7hat 7hat is the @;ig(; @;ig(;ang ang appro approach ach== ANS: The !ig(!ang approach to con*ersion to an ERP is the approach hich con*erts from old legacy systems to the ne in one step that implements the ERP across the entire company. /. escri!e escri!e the to(tier to(tier client client ser*er ser*er model. model. ANS:
3n a to(tier architecture+ the ser*er handles !oth application and data!ase duties. Some ERP *endors use this approach for local area netor, 6'AN8 applications. lient computers are responsi!le for presenting data to the the user and passing user user input !ac, to the ser*er. ser*er. 0. 7hat 7hat is the client client(se (ser*e r*err model model== ANS: The client(ser*er model is a form of netor, topology in hich the users computer or terminal 6the client8 accesses the ERPs programs and data *ia a host computer called the ser*er. 7hile the ser*ers may !e centrali$ed+ the clients are usually located at multiple locations throughout throughout the enterprise. 1. 1. 7hat 7hat is is scal scala! a!il ilit ity= y= ANS: System scala!ility refers to the a!ility of a system to gro as the organi$ation itself gros. This can in*ol*e four factors: si$e+ speed+ or,load+ and transaction cost. 11. 11. 7hat 7hat is is data data min minin ing= g= ANS: ata mining is the process of selecting+ e9ploring+ and modeling large amounts of data to unco*er un,non relationships and patterns. 12. 7hy do ERP ERP systems systems need need !olt(on !olt(on soft softare= are= i*e i*e an e9ample e9ample.. ANS: epending on the uni5ue characteristics of a company+ an ERP may not !e designed to dri*e all processes needed+ e.g.+ supply supply chain management softare softare is a common !olt(on. 1". Bo can can a firm ac5uire ac5uire !olt( !olt(on on softare= softare= 7hat 7hat are the the options options== ANS: 7hen a firm needs additional function not pro*ided !y the ERP+ !olt(on applications may !e a*aila!le. These can often !e o!tained from third(party *endors ith hich the ERP pro*ider has a partnership arrangement. The more ris,y alternati*e is to see, an independent source. 1#. 1#. 7hy doe doess data data need need to !e @cle @cleans ansed ed== ANS: ata cleansing in*ol*es filtering out or repairing in*alid data prior to its !eing stored in the data arehouse. 3t also in*ol*es standardi$ing the format. 1%. 7hat are are the the !asic !asic stages stages of the the data arehousi arehousing ng process= process= ANS: modeling data for the data arehouse+ e9tracting data from the operational data!ases+ cleansing the e9tracted data+ transforming data into the arehouse model+ and loading the data into the data arehouse data!ase 1). escri!e escri!e the the three(t three(tier ier clien clientt ser*er ser*er model. model. ANS:
The data!ase and application functions are separated in the three(tier model. This architecture is typical of large production ERP systems that use ide area netor,s 67ANs8 for connecti*ity. Satisfying a client re5uests re5uires to or more netor, connections. 3nitially+ 3nitially+ the client esta!lishes communications ith the application ser*er. The application ser*er then initiates a second connection to the data!ase ser*er. 1-. 7hy must must a data areho arehouse use includ includee !oth detail detail and and summary summary data= data= ANS: >any decision ma,ers need similar information and need it regularly. Prepared summary data and standard reports can ta,e the pressure off the data arehouse and speed up the pro*ision of regularly needed information. 1/. Bo does does a data arehous arehousee help the e9terna e9ternall auditor auditor perform perform the audit= audit= ANS: &ne of the ,ey procedures performed !y the audit team is analytical re*ie or procedures designed to gather e*idence relating to assertions made !y management in the financial statements. The functions a*aila!le in searching a data arehouse ma,e the e9amination of data to determine trends+ etc.+ fairly easy+ permitting the auditor to e9amine large 5uantities of data easily. 10. 7hat is the closed closed data!a data!ase se archit architectur ecture= e= ANS: The closed data!ase architecture is similar in concept to the !asic flat(file model. Cnder this approach a data!ase management system is used to pro*ide minimal technological ad*antage ad*antage o*er flat(file systems. The ;>S is little more than a pri*ate !ut poerful file system. Each function has a pri*ate data!ase. 2. 7hat is meant meant !y the &'AP &'AP term ( consolid consolidation ation ANS: onsolidation is the aggregation or roll(up of data. For e9ample+ sales offices data can !e rolled up to districts and districts rolled up to regions. 21. 7hat is meant meant !y the &'AP &'AP term ( rill(do rill(don= n= ANS: rill(don permits the disaggregation of data to re*eal the underlying details that e9plain certain phenomena. For e9ample+ the user user can drill don from total total sales returns for a period to to identify the actual products returned and the reasons for their return. 22. 7hat is is meant meant !y the the &'AP &'AP term term ( Slicing Slicing and and dicing dicing== ANS: Slicing and dicing ena!les the user to e9amine data from different *iepoints. &ne slice of data might sho sales ithin each region. r egion. Another Another slice might present sales !y product across regions. Slicing and dicing is often performed along a time a9is to depict trends and patterns. ESSA%
1. Bo are &'TP &'TP and &'AP &'AP differen different= t= i*e e9ample e9ampless of their use. use.
ANS: &n(line transaction processing 6&'TP8 6&'TP8 in*ol*es large num!ers of relati*ely simple day(to(day transactions. For e9ample+ this may in*ol*e order entry hich collects data on customers and detail of sales. &n(line analytical processing 6&'AP8 in*ol*es large amounts of data used to analy$e relationships+ in*ol*ing aggregate data+ that can !e analy$ed+ compared+ and dissected. 2. 7hy does does the data arehou arehouse se need to !e separat separatee from the operati operational onal data!as data!ases= es= ANS: The conclusion that a data arehouse must !e maintained separately from the operational data!ase reflects se*eral issues. The transaction processing system needs a data structure that supports performance. A normali$ed data!ase aids aids users !e adds comple9ity comple9ity that can yield performance performance inefficiency. inefficiency. ata mining systems need an organi$ation that permits !road 5ueries. The data arehouse permits the integration integration of data still maintained maintained in legacy systems. systems. And the the comple9ities of modern !usiness can !enefit !enefit from the a!ility to analy$e analy$e data e9tensi*ely in ays ays not permitted in traditional traditional data!ases. ". 3f an auditor suspected suspected an @unusual relationship !eteen a purchasing agent and certain suppliers+ suppliers+ ho could @drill(don !e used to collect data= ANS: rill(don capa!ility permits a user to repeatedly e9tract detailed data at increasing le*els of detail. An auditor ould !e a!le to e9amine purchasing transactions to determine any pattern of purchases ith the supplier in 5uestion that ere appro*ed !y the purchasing agent and tie such transactions to other characteristics li,e price *ariations relati*e to other *endors at the same time. #. 7hy must must an organi$atio organi$ation n e9pect the the implementat implementation ion of an ERP to disrupt disrupt operati operations= ons= ANS: Successful implementation of an ERP re5uires that many !usiness processes !e reengineered. &nce done+ e*erything is different. 3f the organi$ational culture is not responsi*e to the changes+ many pro!lems can arise. %. Scala!ility Scala!ility has has se*eral se*eral dimensions dimensions.. 7hat are they= they= 7hat do they mean mean for ERP installa installation tion== ANS: >ost organi$ations ant to gro. gro. 7hen a ne system of any an y type is installed+ it should !e e9pected to !e a!le to handle a reasona!le reasona!le amount of groth. groth. ERP systems are no different. different. Se*eral dimensions dimensions of scala!ility can !e considered. 3f size of size of the data!ase dou!les+ access time may dou!le. 3f system speed is increased+ response time should decrease proportionately. proportionately. 3f workload is is increased+ response time can !e maintained ! y increasing hardare capacity accordingly. Transaction costs should costs should not increase as capacity is increased. ). istinguish !eteen the the to(tier to(tier and three(tier client client ser*er model. escri!e escri!e hen each ould !e used= ANS:
3n a to(tier architecture+ the ser*er handles !oth application and data!ase duties. Some ERP *endors use this approach for local area netor, 6'AN8 applications. lient computers are responsi!le for presenting data to the the user and passing user user input !ac, to the ser*er. ser*er. 3n the three(tier three(tier model the data!ase and application functions are separated. This architecture is typical of large production ERP systems that use ide area netor,s 67ANs8 67ANs8 for connecti*ity. Satisfying a client re5uests re5uires to or more netor, connections. 3nitially+ 3nitially+ the client esta!lishes communications ith the application ser*er. The application application ser*er then initiates a second connection to the data!ase ser*er. -. ata in a data arehouse arehouse are in a sta!le state. E9plain ho this can hamper data data mining analysis= 7hat can an organi$ation do to alle*iate this pro!lem= ANS: Typically Typically transaction data are loaded into the arehouse only hen the acti*ity on them has !een completed?they are sta!le. Potentially important relationships !eteen entities may+ hoe*er+ !e a!sent from data that are captured in there sta!le state. For e9ample+ information a!out cancelled sales orders ill pro!a!ly not !e reflected among the sales orders that ha*e !een shipped and paid for !efore they are placed in the arehouse. &ne ay to reflect these dynamics is to e9tract the operations data in @slices of time. These slices pro*ide snapshots of !usiness acti*ity. /. This chapter chapter stressed stressed the importance of of data normali$ation hen constructing constructing a relational relational data!ase. 7hy then is it important to de(normali$e data in a data arehouse= ANS: 7here*er possi!le+ normali$ed ta!les pertaining to selected e*ents should !e consolidated into de( normali$ed ta!les. ;ecause of the *ast si$e of a data arehouse+ inefficiency caused !y Doining normali$ed data can !e *ery detrimental to the performance of the system. A three(ay three(ay Doin !eteen ta!les in a large data arehouse may ta,e an unaccepta!ly long time to complete and may !e unnecessary. unnecessary. Since historical data are static in nature+ nothing is gained !y ! y constructing normali$ed ta!les ith dynamic lin,s. 0. ERP implem implementati entations ons are at ris, to e9tensi e9tensi*e *e cost o*eruns o*eruns.. iscuss three three of the more commonly commonly e9perienced pro!lems area. ANS: Training& Training costs are in*aria!ly higher than estimated !ecause management focuses primarily on the cost of teaching employees the ne softare. This is only part of the needed training. Employees also need to learn ne procedures+ hich is often o*erloo,ed during the !udgeting process. System Testing an' ntegration& 3n theory+ ERP is a holistic model in hich one system dri*es the entire organi$ation. The reality+ reality+ hoe*er+ is that many organi$ations organi$ations use their ERP as a !ac,!one system that is attached to legacy systems and other !olt(on systems+ hich support uni5ue needs of the firm. 3ntegrating these disparate systems ith the ERP may in*ol*e riting special con*ersion programs or e*en modifying modifying the internal code of the the ERP. 3ntegration and testing testing are done on a case( !y(case !asis thus+ thus+ the cost is e9tremely difficult difficult to estimate estimate in ad*ance.
(ata)ase Con*ersion& A ne ERP system usually means a ne data!ase. ata con*ersion is the process of transferring data data from the legacy systemore often+ the data in the legacy system are not relia!le 6sometimes called dirty8. Empty fields and corrupted data *alues cause con*ersion pro!lems that demand human inter*ention and data re,eying. Also+ and more importantly+ importantly+ the structure of the legacy data is li,ely to !e incompati!le ith the reengineered processes of the ne system. system. epending on the e9tent e9tent of the process reengineering reengineering in*ol*ed+ the the entire data!ase may need to !e con*erted through manual data entry procedures.
