Manzana Insurance

OM Manzana Case Study - Team 2 (Rishi, Geoff, Vimalan, Rose, and Jonathan)

Manzana Insurance Fruitvale Branch case study Executive Summary

Manzana’s Fruitvale branch is suffering from declining profitability. The main issues resulting in this phenomenon are its falling renewal rate and rising turnaround time. There are systemic issues with the process for handling requests that have led to this deterio deteriorati ration on,, includ including ing the incorr incorrect ect priori prioritiz tizatio ation n of request requestss and the uneven uneven distrib distributi ution on of workl workload oad amongs amongstt its three three underwr underwriti iting ng teams. teams. There There are also also problems of understaffing in the Distribution and Underwriting teams and possible idle capacity in the Rating and Policy Writing teams. To compound matters, the branch is using an incorrect methodology for computing turnaround time. Addressing these underlying issues is key to Manzana’s ability to compete with Golden Gate, whose whose quicker quicker guaranteed guaranteed turnaround turnaround time will generate generate loyalty loyalty among independent independent agents agents and result result in furthe furtherr loss loss of busine business ss for Manzan Manzana. a. To prevent prevent this, the following steps are recommended:(i)the FIFO system on all requests received should be strictly implemented; (ii)the reward system for employees should be reviewed and aligned to support the implementation of (i); (iii) RERUNs should be sent to Distribution Clerks at least three days prior to the expiry of the old policy; (iv) The workload among the three underwriting teams should be better balanced; (v)The SCT for the rating and policy writing teams need to be reviewed as they are possibly based on outdated figures. This can lead to redeployment of some staff in these departments to the understaffed departments of Distribution and Underwriting; and

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(vi) the methodology for computing TAT needs to be reviewed as current methodology employed is incorrect and provides an inflated TAT figure. Accurate SCT figures also need to be used in the computation of TAT.

Major issues at the Fruitvale Branch

The most alarming issue facing the Fruitvale branch is the sharp increase in renewal loss rate, from 33% to 47% in the last year. As renewals represent roughly three quarters of the company’s revenue, this is a crucial area to improve. The primary cause of this increase is the fact that renewals are often not processed internally before they expire, causing agents to recommend other insurers to their customers. This links to the second major issue that needs addressing. The turnaround time (TAT) for insurance requests is far longer than Manzana’s main competitor Golden Gate, and is still increasing. Improving this is key to attracting new business and retaining existing business as agents will go elsewhere if Manzana’s TAT is not reduced and Golden Gate is able to deliver on its guaranteed TAT of 1 working day. These two issues have contributed significantly in overall branch profitability declining.

Causes and discussion of possible solutions

Late processing of RERUNs due to prioritization

Renewals, or RERUNs, are not issued to the distribution clerks (DCs) until the day before they are due. This would be fine if the DC’s were idle or if RERUNs were a top priority from there, but employees systematically deprioritise RERUNs in favour of securing new business through RUNs and RAPs, as their salary bonuses are linked to these. As a result, the percentage of late RERUNs has more than doubled this year. A simple solution would be to enforce the company’s official FIFO policy and not

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have any prioritisation rules, and to support this the bonus salary structure should be reviewed and revised so that a more aligned target, such as turnaround time or profit is rewarded. In addition, the one day notice for DCs should be increased to three days to ensure sufficient time for a renewed contract offer to reach the agents on or before the expiration date of the old policy . Although this may not be based on the most up to date information, it will not be far off and is vastly preferable to losing the business Insufficient Capacity

Once the question of prioritisation is removed, it is possible to analyze whether the Fruitvale branch has enough employees to cover the workload, or as John Lombard insists, they need more staff. Of the three examples given, the Fruitvale branch has the highest agent to underwriter ratio of approximately 25, compared to 20 for the largest and smallest Manzana branches. However, Tom Jacobs’ “rough calculations” indicate that the team is still working within its capacity. The utilization rates based on Tom Jacob’s calculations and exact utilization rates (based on 39 requests per day_) are set out below.

Tom Jacobs’s calculation Exact calculation*

Distribution

Underwriting

Rating

Policy Writing

89%

89%

78%

73%

89%

82%

76%

64%

*Detailed calculations are set out at Appendix A. Tom Jacobs states that the Fruitvale branch is overstaffed. However, the current utilization rates suggest that there is insufficient reserve capacity in the system to handle variability in demand as the utilization rates are relatively close to 100%. A guideline of 80% utilization rate is suggested as a fair compromise between productivity and having the flexibility to respond to potential variability in demand. In

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the premises, the Fruitvale branch is understaffed in both the Distribution and Underwriting departments. The Distribution figure is particularly concerning as the calculations do not even take into account the other responsibilities performed by that department such as analysing and disseminating industry data every month, verifying insurance competitor’s quotes and overseeing the ratings operations. This could cause bottlenecks in these areas so will be examined further below. Unbalanced workload amongst the Underwriting teams

Another factor to consider is that the above calculation is for average utilization, using the average number of requests per day. This may be hiding the fact, highlighted by Tom Jacobs, that staff are overworked at times and idle at others. This is particularly likely to happen in the Underwriting team, who are only allocated jobs from specific agents. This can result in an uneven volume of work for each territorial team. If the same utilization analysis is used for each territory, it shows that this is in fact the case. Territory 1 Number of requests (H1 ’91)

1867

Requests per day (120 days total)

Territory 2 1657

Territory 3 1430 11.9

Time required (using 28.4min each)

15.6 443.04

13.8 391.92

337.96

Utilization (using 450mins available)

98.4%

87%

75%

It is clear that territory 1 is running close to its peak capacity, which is unsustainable, and no doubt results in substantial delays for some requests, especially RERUNs and RAINs which are down the priority order. Even territory 2 is being stretched at an unsustainable level. Only territory 3 is running at an effective capacity. As suspected, the underwriters are indeed the bottleneck in the process, with Exhibit 3 confirming that there are more requests at this stage than everywhere else put together, even more

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so for RAINs and RERUNs, and that this is the most t ime-consuming step at 3.4 days. To improve this situation Manzana needs to balance the territorial workloads. The company could do away with the territory system altogether, and simply allocate incoming requests to the first team available on a FIFO basis, smoothing the utilization across the teams with each of them at an average of 87%. However, this is still higher than the optimum value of 80%, suggesting that John Lombard’s request for more underwriters is valid. The drawback of this model is that it would reduce the effect of personal relationships held between agents and underwriters, which were deemed a “critical factor in building and sustaining market share and profitability” for Manzana. If this is still the case, and relationships are more important than simply reducing turnaround time, the company should not switch to FIFO with respect to allocation of requests to its underwriting teams. Instead it may consider redefining the territories so that territory 3 takes on some of territory 1’s agents (assuming the first half of 1991 is consistent with future expectations). It should also consider using the Review and Distribution (Distribution) function to identify which requests require personal relationships and prior knowledge, and which are more mechanical and can be done by any available underwriting team. This will add some time to an already overloaded Distribution team, but will help balance the underwriters workload and therefore ease the primary bottleneck. However, to seriously improve its TAT, Manzana should consider increasing its Distribution and Underwriting resources and hiring new staff in this area. Automation of Rating and Policy Writing Stages

A further area that could be improved to reduce the turnaround time is the rating and policy writing stages. These can both be largely automated thanks to the development

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of computers in the late 80’s, making the SCT inaccurate. The Fruitvale branch spends 2/3 of the processing time on these two stages, suggesting they have not capitalized on technological developments. Manzana cannot compete with Golden Gate until they do. There is a chance that staff freed-up in this area can develop the skills needed in the bottleneck stages outlined above, therefore maintaining the current headcount and reducing any need for expensive and time-consuming recruitment and training without affecting staff morale with retrenchments. Problems with the current measurement system for TAT

There are four main issues with the current system/methodology used by the branch to compute TAT. Firstly, based on the current system the manager calculates TAT assuming that various activities wait for earlier activities to complete before commencing. For example, from Exhibit 3, the Underwriting team starts work after 0.6 days within which Distribution clerks clears its backlog. Further, it assumes that policies move from one activity to another in batches equal to the total number of policies with the department. The TAT as computed for the week ending 6 th September 1991 as set out in Exhibit 3 is incorrect as the assumptions that the calculations are based on are fallacious. A more accurate calculation of the TAT for that week is set out at Appendix B. Secondly, the current measurement system for turnaround time is based on the SCTs calculated in 1986, before the development of computerized rating and policy writing, the liability crisis and subsequent takeover of Manzana by Banque du Soleil and the switch of focus to property insurance only for the Fruitvale branch. In the premises, it is likely that the SCTs set out in Exhibit 3 and used to compute TAT are outdated and overstated.

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Thirdly, the use of the 95% SCT itself is misleading, as it ignores the 5% of requests that are most time consuming. Taking underwriting RERUNs as the worst case example, the maximum time used for one request exceeded the 95% SCT by eleven hours. To ignore these problem requests in the turnaround calculations leads to inaccurate expectations for team performance. This figure is only calculated once a week, and then used for that entire week to predict turnarounds times. The workload can change significantly in that time, so agents may be given inaccurate due dates. Lastly, the processing times used have the staff’s unofficial prioritization process inherent within them. They do not therefore accurately reflect the processing times required for the requests if the official FIFO method were employed.

Recommendations

To address the two major issues of dropping renewals and increasing turnaround times, it is recommended that the following steps be taken immediately. The first is to enforce the FIFO policy on all requests, ensuring that RERUNs are not deprioritised and protecting Manzana’s largest revenue stream. This will involve changing the salary plus bonus scheme so that not only new policies are rewarded. The RERUNs should be sent to the DCs three days before they are due to ensure they are processed in time.

Secondly, headcount for the Distribution and Underwriting departments needs to be increased as the departments are understaffed as indicated by their utilization rates which are not able to cope with variability in demand.

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Thirdly, the territorial system for underwriters needs to be reviewed. A strategic choice is required on whether to sacrifice the personal relationships between underwriters and agents in favour of improved turnaround times. If Manzana are to maintain these relationships – possibly giving them a point of difference over Golden Gate’s model – they should balance the expected workloads and investigate which requests have to go to territory teams and which can go to anyone available. However, the company may still need to recruit in this area to successfully compete with Golden Gate.

Fourthly, Manzana needs to further implement technological developments in the computerization of the Rating and Policy Writing stages. This may free up staff to be redeployed in Distribution and Underwriting.

Lastly, the system and the methodology for computing TAT needs to be reviewed based on an updated SCT and employing the methodology set out above.

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Appendix A: Capacity Utilization rates

a) Weighted average processing time (Exhibit 4) b)Total Capacity (1/ a * 60 * capacity available) c) Total requests per day (22 +17) Capacity Utilization (c/b)

Distributio n

Underwritin g

Rating

Policy writing

41mins/ request

28.4mins/ request

70.4mins/ request

54.8mins/requ est

43.9 (1/41 * 60 * 30hrs)

47.54 (1/28.4 * 60 * 22.5hrs)

51.14 (1/70.4 * 60 * 60hrs)

41.06 (1/54.8 * 60 * 37.5hrs)

39

39

39

29 (75%)

89%

82%

76%

70%

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Appendix B: Proper calculation of TAT for week ending 6 th September 1991 DC no of requests

1.0

3.0

1.0

11.0

request per person

0.3

0.8

0.3

2.8

4.0

team members

128.1 32.0

107.8 80.9

68.1 17.0

43.2 118.8

0.6

days

no of requests

3.0

7.0

6.0

36.0

request per team

1.0

2.3

2.0

12.0

3.0

team members

107.2 107.2

87.5 204.2

49.4 98.8

62.8 753.6

2.6

days

no of requests

1.0

3.0

1.0

11.0

request per team

0.3

1.0

0.3

3.7

3.0

team members

107.2 35.7

87.5 87.5

49.4 16.5

62.8 230.3

0.8

days

no of requests

1.0

2.0

1.0

7.0

request per person

0.1

0.3

0.1

0.9

8.0

team members

112.3 14.0

88.7 22.2

89.4 11.2

92.2 80.7

0.3

days

no of requests

4.0

10.0

7.0

47.0

request per person

0.5

1.3

0.9

5.9

8.0

team members

112.3 56.2

88.7 110.9

89.4 78.2

92.2 541.7

1.7

days

no of requests

0.0

0.0

1.0

2.0

request per person

0.0

0.0

0.2

0.4

5.0

team members

89.3 0.0

0.0 0.0

72.1 14.4

67.0 26.8

0.1

days

no of requests

5.0

0.0

8.0

54.0

request per person

1.0

0.0

1.6

10.8

5.0

team members

89.3 89.3

0.0 0.0

72.1 115.4

67.0 723.6

2.1

days

no of requests

1.0

1.0

1.0

1.0

request per person

0.2

0.2

0.2

0.2

5.0

team members

89.3

0.0

72.1

67.0

95% SCT Time required

UW backlog


UW new


Rating backlog


Rating new


PW backlog


PW new


PW last

95% SCT

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Time required

17.9

0.0

14.4

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13.4

0.1

days

4.4

days

Manzana Insurance

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