Manzana Insurance Case

Case Background About the firm Manzana Insurance was founded in Sebastapol, California in 1902. It originally specialized in orchard and farm insurance. In 1906, after the San Francisco Fire, it saw an opportunity and expanded into a number of areas.

The main lines of business initially were Commercial property insurance only. Then Manzana dabbled into commercial liability segment which contributed to almost 50% of revenues.

But after the liability crisis and its takeover the strategy adopted was a back to basic strategy whereby there was a conscious effort to reduce the revenue contribution from liabilities. This went down to 20% in 1991. During this time frame the competition from other insurance companies especially from Golden Gate, had become intense.

Insurance Industry Segmentation Personal Commercial Property Liability Property Manzana s area of specialization Liability The case deals with the performance of a branch, located at Fruitvale, which has been consistently losing business to its archrival Golden Gate in its territory.

By mid-1991, Golden Gate had performed much better than Manzana s Fruitvale branch on every count and this resulted in memo being issued by the senior vicepresident at Manzana. The Fruitvale branch performed badly on various measures like total number of requests for new policies, endorsements, and renewals processed, very high turnaround time resulting in late renewals and increased renewal loss rate. OPERATIONS MANAGEMENT CASE ANALYSIS Problem Overview Manzana Insurance – Fruitvale’s core management problem is its under-par performance owing to long turnaround times (TAT) and piling up backlogs of request in process (RIP).

Also, because of the late Renewals, many of Fruitvale? s customers are turning to its major competitor Golden Gate.

There are systemic issues with the process for handling requests that have led to this deterioration, including the incorrect prioritization of requests and the uneven distribution of workload amongst its three underwriting teams. Other problems in the Fruitvale branch include ineffective incentive systems, increase in shift to newer policies, bottlenecks in operation, possible idle capacity in the Rating and Policy Writing teams, etc. These problems have resulted in loss of almost half of renewal business for Manzana-Fruitvale.

Addressing these underlying issues is key to Manzana s ability to compete with Golden Gate. Insurance Sector Performance Metrics The key parameters that the customers use to differentiate the various offerings in the market are: Turnaround Time: Turnaround time of policy requests and approvals refers to the amount of time it takes on average for a request to be handled from the time of entry to the time of final approval.

A low Turnaround Time is preferred by the customers. The average turnaround time of Fruitvale s operations has increased to 6 days, while Golden Gate s is around 2 days.

The long lead times on the policies and quotes and the waiting time of the renewals has led to a loss of business, creating the opportunity for the competitor to take up more market share. Renewal rate of Policies: The ease of renewal is also a selling point. A hassle free and quick renewal policy could be leveraged upon to increase the market share. Fruitvale s overemphasis on new policies, based on the idea that new policies would generate higher margins, is causing loss of profitability resulting in loss of almost half of the renewal business every year.

For instance, the dispatch for renewals is sent only the day before the expiry. This has serious consequences on the sustainability of the business as the number of renewals directly affects the policies in force, which in turn impacts the revenue stream. Backlog: The backlogs as well as the Late RERUNs have been increasing steadily over the given period, which acts as a detriment to the relationship with the agents. The average wait time, for instance, has increased by 118. 5%.

The competitor, Golden Gate has offered a 20% discount if it doesn t finish the processing in 1 day, directly denting Fruitvale s market share.

Pricing: Superior risk analysis, which results in better pricing decisions, can be leveraged for higher profits and advantages. Types of policies RUNS (Request for Underwriting) When a new policy arrives it is processed by a distribution clerk. The policy is sent to the respective underwriting desk based on pre set rules. After review and classification the underwriting team sends it to the Rating Desk which calculates the premium. It is then passed to the policy writing team who actually types, distributes and completes the policy.

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OPERATIONS MANAGEMENT CASE ANALYSIS RERUNS (Policy renewal) It deals with annual revaluation and if necessary re-pricing of risk. The processing is similar to that for RUNS with the difference that renewals are generated by the system. RAIN (Policy endorsement) pricing exercise. RAP (Price Quotes) The processing is similar to that for RUN but after the policy rating it is sent to the It is required to amend the terms of the existing policy. This is more of a re- distribution clerk who sends the quote back to the agent.

If the same is accepted, the RAP became a RUN.

The policies are dealt with on a First in First out (FIFO) basis while the underwriting team prioritizes them in the order of RUNs, RAPs, RAINs and then RERUNs. Process Flow The time (in minutes) required for ; utilization different request types are different for each of the activities. Type RUN RAP RAIN Distribution 68. 5 50.

0 43. 5 Underwriting 43. 6 38. 0 22. 6 Rating 75.

5 64. 7 65. 5 Policy Writing 71. 0 NA 54. 0 OPERATIONS MANAGEMENT CASE ANALYSIS RERUN 28.

0 18. 7 75. 5 50. 1 Distribution Weighted Avg. 41 Min/request Underwriting 28. 4 Min/request Rating 70.

4 Min/request Policy Writing 54. 8 Min/request

Processing Time = t Total Capacity = 1/t * 60 * capacity available 1/41 * 60 * 4 clerks * 7. 5 = 43. 9 requests Total Requests per day Capacity Utilization = total capacity requests/total 39 89 % 1/28. 4 * 60 * 3 * 7. 5 = 47.

54 requests 39 82% 1/70. 4 * 60 * 8 * 7. 5 = 51. 14 requests 39 76% 1/54. 8 * 60 * 5 * 7. 5 = 41.

06 requests 29 71% The capacity of the system is equal to the minimum capacity of the individual servers i. e. 41 requests/day. All requests start with the distribution clerk distributing the request for insurance policy (RUN, RAIN or RAP) received from an agent or computer (RERUN) to the respective underwriting team.

Distribution also analyses and disseminated published data, researches competitor s rates and oversees rating.

The underwriting team evaluates, selects, classifies and prices the request and then it passes on to the rating department where the premiums are calculated. The policy writing departments does the actual typing, assembly and distribution of completed policies. In case of RAP, the quote was transferred to the originating agent from the rating department and once accepted, went straight to the policy writers. Only around 15% of all quotes translated into policies.

The revenue generated by each is given below Type Premium Revenues ($) annual(max from case) RUN RAIN RERUN 6724 645 6205 The Fruitvale branch followed the FIFO method, but in practice, there were 2 priority classes (within which again, FIFO was followed). The RUNs and the RAPs, being more revenue generating were tackled first and then the RAIN and RERUN.

In case of policy writers, they seemed to handle the easier tasks first and then the more complex ones. 5 OPERATIONS MANAGEMENT CASE ANALYSIS The Fruitvale branch of the company has not been doing well over the last few years as revealed by the financials of the company.

Its performance has dropped over almost every metric. Profitability has declined and the TAT has gone up from about 3 days to 6 days now. On the other hand, Golden Gate was offering a seemingly impossible 1 day turnaround period. This had the effect of the independent agents pushing through the policies of Golden Gate ahead of Manzana s.

The number of new policies has stagnated for the Fruitvale branch over the years in spite of moderate industry growth. The renewal losses were also very high with about 47% renewals being lost every year. Capacity and Process Analysis

Scheduling at Manzana is currently done on a priority basis with RUNs ; RAPs being given higher priority over RAINs ; RERUNs. The problem associated with this treatment is that, we see the system in parts where in different teams become bottle necks as one particular type of request flows through the system. The efficiency that arises out of combining different requests which have different process times is lost in this method.

Though the system can operate at a higher capacity this scheduling chokes with the RERUNs being affected to the maximum amount. The total average weekly demand is about 195 requests i. . around 39 requests per day. The calculation of the average weekly demand has been provided in EXHIBIT 1 and the percentage composition of jobs has been given in EXHIBIT 2. RERUNs form over 51% of these requests.

The next highest proportion of requests is formed by RAPs which account for about 27% of the requests. The departments with 100% capacity utilization are the ones which are the bottlenecks for a particular request. On examining the figures, we see that at 95% SCT, the underwriting department is the bottleneck for RUNs, RAPs and RERUNs, while the distribution team is the bottleneck for RAINs.

Looking at the average utilization we see that the distribution department is the bottleneck for RUNs and RAINs. The aggregate figures show that the Policy Writing department is the bottleneck.

The distribution department is also running at a high utilization of 93. 52%. The average lead time of the process is given by Little s Law; the Requests In Process (RIP)/Throughput = 82 Policies/39 Policies/Day = approximately 2. 1 days. The turnaround time for various requests under current scheduling is highest for RERUNs at about 14.

5 hours. The total turnaround time is 38. 7 hours which is more than the workweek of 37. 5 hours.

As a result the backlog of requests is increasing. The major problem that Manzana is facing is loss of renewals due to high TAT and late renewals.

This can be overcome by giving RERUNs a higher priority when processing requests. Appendix 10 shows the results under this scenario. If RERUNs are given first priority, the TAT for RERUNs decreases to 3. 4 hours and the total TAT comes down to about 27. 5 hours. 6 OPERATIONS MANAGEMENT CASE ANALYSIS Underwriting Teams Workload Unequally Divided There is a heavy imbalance between the average utilization rates of the different underwriting teams viz.

92. 3%, 82. 9% and 70. %. This has lead to underwriting becoming a bottle-neck operation in the whole process as during peak load times the underwriter team 1 is unable to cope with the overload and piling up of the jobs takes place.

Under-Writing Weighted Avg.

Territory 1 28. 4 Territory 2 28. 4 Territory 3 28. 4 Processing Time = t Total Capacity = 1/t * 60 * capacity available Total Requests per day 1/28. 4 * 60 * 7.

5 = 15. 84 requests 162+761+196+636/120 = 14. 625 Capacity Utilization 92. 3% 1/28. 4 * 60 * 7. 5 = 15.

84 requests 100+513+125+840/120 = 13. 15 82. 9% 1/28. 4 * 60 * 7. 5 = 15. 84 requests 88+524+130+605/120 = 11.

225 70. 6% Bottleneck Operation after Geographical Realignment TAT Calculations Distribution Weighted =t Total Capacity = 1/t * 60 * capacity available 1/41 * 60 * 4 clerks * 7. 5 = 43. 9 requests 1/28. 4 * 60 * 3 * 7.

5 = 47. 54 requests 1/70. 4 * 60 * 8 * 7. 5 = 51. 14 requests 1/54. 8 * 60 * 5 * 7.

5 = 41. 06 requests Avg. 41 Min/request Underwriting 28. 4 Min/request Rating 70. 4 Min/request Policy Writing 54.

8 Min/request Processing Time From the above calculations it can be seen that Policy writing comes out to be the bottle neck in our calculations when work is equally divided amongst the three underwriting teams.

Hence we have 82 requests in process, therefore from Little s law our TAT is 82/41. 06=2. 14 days, which is much lower compared to the TAT when Underwriting is the bottleneck due to unequal allocation of work. OPERATIONS MANAGEMENT CASE ANALYSIS Priority Rearrangement It is well known thumb rule in marketing that the effort in terms of time, money and energy required to acquire a new customer is 5 times more than that required to retain and existing customer yet Manzana keeps losing customers who don t renew. Tom Jacob states that Manzana cannot afford to keep increasing the customer loss rate by 50% every quarter.

This loss stems out of two false assumptions. One, that RUNs and RAPs are more important and generate more revenue. From the point of view of profitability of each type of request, it can be seen that RERUNS are actually more profitable than RUNs. Net Premium per minute = Premium / Avg. Time for processing RUN Net Premium per min ($/min) 6724/258. 6 = 26 RAIN 645/185.

6 = 3. 48 RAP 1008. 6/223. 7 = 4. 5 RERUN 6205/172. 3 = 36 The central policy is to use the FIFO processing system however this branch does not follow the policy to its entirety.

Each employee lets various incoming requests accumulate and then prioritize within the accumulated requests on the following lines RUNs, RAPs, RAINs and RERUNs. Within these segments they use FIFO. This alteration of the processing system leads to ignorance of RERUNs which leads to late renewals and customer and agent dissatisfaction. This dissatisfaction, results in either customers saying no to renewal requests or agents recommending competing firms to a suffering customer. Moreover, the incentive scheme for renewals is quite ineffective as the insurance commission for new policy is 25% whereas that for renewals is just 7%.

Hence agents give priority to RUNs over RERUNs.

Agents are the primary customers of Manzana. They influence the buying decision of the end customer (policyholders), and can influence the risk profile of policyholders and also Manzana s reputation. RERUN RAIN RUN through RAP RUN 0 5 10 15 20 25 30 35 40 Premium per minute OPERATIONS MANAGEMENT CASE ANALYSIS Miscalculation of TAT The calculation of TAT is based on the current system the manager calculates TAT assuming that various activities wait for earlier activities to complete before commencing.

In other words, the current system of TAT measurement assumes that the jobs are effectively being processed in batches i. e.

batch processing is being carried out. Also, the current measurement system for turnaround time is based on the SCTs calculated in 1986, before the development of computerized rating and policy writing, It is likely that the SCTs set out in the case exhibits and used to compute TAT are outdated and overstated. In addition, 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.

The TAT calculations at the rating desks, the requests outstanding at distribution clerk desks and underwriting team desks are also considered, even though they have already been accounted for. Also, SCT (Standard Completion Time) is used instead of the mean time to calculate the TAT (turnaround time).

When SCT is used, it is assumed that 95% of all requests will take that much time, whereas on an average, the time taken would be much less. Hence, the turnaround time calculations are inflated. Other Concerns Loss of renewals (drop in no. of RERUNS) resulting in stagnant revenues The number of renewals lost has increased from 317 to 784 and currently stands at 403 for six months in 1991.

Renewals generate a premium of $36 per minute of processing time. Thus losing renewals leads to a decline in revenues generated. New policies have been added but the loss due to renewals is greater than the gain.

Poor conversion of RAPs RAP has a mean processing time of 223. 7 min and it generates a premium of only $4. 5 per minute.

To add to this only15% of RAPs are converted into RUNs. Thus the effort (processing time) is lost and hence RAP should not be given a high priority. RERUN Processing Issues The RERUN is released only one day in advance of due date. Thus to ensure that there is no backlog the TAT must be less than 1day. In the current system with a higher TAT backlog occurs. Thus RERUN should be released much in advance of the due date.

This can be aided by the automated ickler system of the computer. Adverse Selection 9 OPERATIONS MANAGEMENT CASE ANALYSIS Since the Turnaround time for Manzana is quite high compared tot s competitors, only people with a high degree of risk would willingly opt for poor quality of service, since they know that good companies would reject their underwriting proposal straightaway. Thus, only people with high risk profiles would opt for Manzana Insurance. As can be seen in EXHIBIT 3 the net underwriting revenue has been increasing quite significantly over the past few quarters. Recommendations

Major operational issues directly impacting the company are: · · · Dropping renewal rate as the renewal loss rate increased from 33% this quarter last year to 47% this quarter this year Increased Turnaround Times (TAT) of high revenue generating streams viz.

RUNs and RERUNs Under-writing ; distribution operations have high average utilization rates leading to capacity constraints during peak times 1. If a simple round-robin scheduling of the under-writing processes is adopted instead of territorial scheduling of the incoming jobs, the workload of the incoming jobs can be shared equally leading to enhanced throughput.

The new utilization rate of the three underwriting teams with this round-robin scheduling is the average of the utilizations of the individual territories which is around 82%. Also, a drawback of this strategy would be that there would be limited levels of personalization and personal interactions between the underwriters and territorial agents. 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.

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To boost the renewal rate of policies, the first strategy is to enforce the FIFO policy on all requests, ensuring that RERUNs are not relegated and are promoted in the priority order. Also, as shown in the table above, the net premium per minute is higher for RERUN as compared to the other types of jobs. This will involve changing the salary plus bonus scheme so that not only new policies are rewarded. The commission structure of agents needs changes. Since the renewals are quite profitable for the company, the commission for renewals can be revised upwards.

Hence, the scheduling of the jobs is to be as follows: 1. RERUN 2. RUN 3.

RAP 4. RAIN 3.

The 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. The average utilization rates are still higher than the optimum value of 80%, suggesting that John Lombard s request for more underwriters is valid. 10 OPERATIONS MANAGEMENT CASE ANALYSIS EXHIBIT 1 6-month demand in 1991 Wkly Avg Demand in 1991 (6 month demand / 24) 26. 00 18. 79 63. 50 86.

71 Quarterly Peak Demand (Over the last 10 qtrs) 326 245 936 1308 Weekly Peak Demand (Qtrly demand / 12) 27. 7 20. 42 78. 00 109. 00 Policy RUNs RAPs RAINs RERUNs 624 451 1524 2081 EXHIBIT 2 Policy Policies processed (in last 10 qtrs) 2814 6524 2123 12234 23695 Average % composition 11.

88% 27. 53% 8. 96% 51. 63% RUNs RAPs RAINs RERUNs Total EXHIBIT 3 Ordinary Insured Losses 7000 6000 5000 4000 3000 2000 1000 0 1989 1989 1989 1989 1990 1990 1990 1990 1991 1991 q1 q2 q3 q4 q1 q2 q3 q4 q1 q2 Ordinary Insured Losses OPERATIONS MANAGEMENT CASE ANALYSIS EXHIBIT 4 Profit(Loss) 2000 1500 1000 500 0 Q1 1989 Q2 1989 Q3 1989 Q4 1989 Q1 1990 Q2 1990 Q3 1990 Q4 1990 Q1 1991 Q2 1991 -500 Profit ($)