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Manzana insurance

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Manzana insurance

Operations Analysis
Operations Analysis

Executive Summary
Manzana Insurance specialises in commercial insurance, with the Fruitvale branch typically processing 40 requests per day and the product mix being 60% new policies and 40% renewal requests.
The operating performance of Fruitvale is deteriorating across five of the company’s six key performance measures. Additionally, competitor Golden Gate has promised efficiency in service and offered a guarantee for time request turnarounds.
Our analysis of Fruitvale’s operations, priorities and cost structure shows that: * The “first-in, first-out” processing system is implemented differently across the teams, causing RERUNs to be submitted late and leading to lost renewals. * The increase in ordinary insured losses and declining revenues from renewals is causing a decline in Fruitvale’s profitability. * The current procedure to calculate turnaround time results in a high value and is really a worst case scenario. * There is a large degree of variance in the time it takes to handle requests, which can cause both the distribution and underwriting teams have more work than capacity. This affects responsiveness, as the system has little spare capacity to deal with increased demand due to variation, seasonality or new business.
Based on our analysis, we make a number of recommendations for Manzana to implement: * Review employee and agent incentives and change the priorities of the current process, to ensure more focus on RERUNs. * Consider increasing the number of staff to improve capacity and reduce turnaround time to accommodate uncertainty and variability in demand. * Pool underwriting resources to better balance utilisation. * Match Golden Gate’s policy if capacity is increased to cope with uncertainty in processing times.
If above recommendations are adopted, we anticipate that the Fruitvale branch can still be profitable.

Glossary

Introduction
Manzana Insurance specialises in commercial insurance, with property insurance, in 1991, contributing to 65% of revenues, liability insurance 20%, and investment income and miscellaneous specialty lines constituting the remainder.
Manzana Insurance works with roughly 2,000 independent agents that function as a front-of-house salesforce, although these agents provide services for competing insurance companies.
The Fruitvale branch typically receives 40 requests per day, which is a rough estimate for the flow rate for an average day, with product mix being 60% new policies and 40% renewal requests.
Manzana employs three underwriting teams whose sole purpose is to service agents assigned to three particular locations. Manzana compensates its sales force and underwriters with commission incentives:
Insurance Industry Snapshot
The trend in the insurance market has been downward for some time and the market appears saturated. With numerous competitors fighting for market share, price wars are abundant. Insurance companies are forced to accept ever decreasing margins until the market as a whole becomes unprofitable
The needs and demands of Manzana’s customers have recently been determined by performance of Manzana’s competitors (Golden Gate). Customers expect timely renewals for their existing polices. Late renewals result in agents looking to other insurance organisations for their customers, because the agent will only receive commissions if they can service their customers efficiently. The only distinguishing trait among popular insurance providers is the service they can offer, as the price differences between competitors are very slim. As a result, customers are attracted and repelled by the service that is offered. Additionally, competitor Golden Gate has promised efficiency in service and offered a guarantee for a timely turnaround.

Operating performance
Golden Gate is outperforming the Fruitvale branch on all operating performance metrics. The operating performance of the Fruitvale branch is deteriorating across five of the company’s six key performance measures:
Financial performance
The table below outlines the financial performance of the Fruitvale branch between 1989 and 1991.
Table 1: Fruitvale Branch Financial Performance

Manzana has steadily declining revenues from renewals, down 6.24% since 1989. The increase in ordinary insured losses have been steadily increasing (refer Figure1), account for nearly 90% (refer Table 2) of the total quarterly cost increase and can be attributed to the increase in new policies. With an incentive to sign up as many new policies as they can, because of the introduction of Plus Program, potential new policy risks may have been overlooked or underestimated leading to a higher rate of claims. Branch managers are responsible for running reports with all incoming requests and calculating their due dates. The incentive program also could have changed the way managers arrange their teams’ daily work: they would select RUNs and RAPs, even if that means being late or even losing other policies.
Figure 1: Ordinary Insured Losses

Table 2: Cost Structure Analysis –Quarterly cost changes, showing net movement

Rules and priorities
Manzana currently has a policy of using a straight “first-in, first-out” (FIFO) system. This system is interpreted and implemented differently across the teams:
The majority of the documents that are being submitted late are RERUNs, which are also considered to be the lowest priority. Currently 44% of all RERUNS are late and Manzana’s Fruitvale Branch loses repeat customers because they are not delivering the renewal policy until after the current policy has ended. One of the main causes is underwriting team’s attitude toward the processing of RERUNs. The underwriting teams complete the work on RUNs and RAPs as the priority. RERUNs are not released to the DCs until the day before the work is due. With this process in place, there is no time to wait in order to finish the RERUN, or they will be late.
When RERUNs are submitted late this leads to lost renewals and the decline in renewals is having a direct impact on Fruitvale’s financial performance, as described in Table 1. If RERUNs were considered as an equal priority, fewer of them will be submitted late.
TAT and impact
As Table 3 illustrates, change is necessary if Manzana desires to compete in a market where buyer’s decisions are increasingly being made based on responsiveness and quality of service.
Table 3: Current Performance Comparison
However, the current procedure used by Manzana to calculate of TAT is flawed: * Instead of using the average time for processing a policy, the 95th percentile standard completion time (SCT) is used. This is the reason why such a high TAT (8.2 days) was calculated for the Fruitvale branch, and is really a worst case scenario. * The current procedure to calculate TAT assumes that the activities wait for earlier activities to complete. The uderwriting team starts work 0.6 days after DC finishes their current work. It is assumed that policies move from one activity to another in batches equal to the total number of current policies (work) with that department.

The actual TAT at Manzana is currently 6 days based on the weighted average TAT (refer Figure 3). This means that the average policy takes 6 days to create.
Figure 3: Weighted Average TAT

Utilisation and Capacity
The analysis in Table 4 shows that distribution is the bottleneck, with high utilisation (98%). This affects responsiveness as the system has little spare capacity to deal with increased demand due to variation, seasonality or new business.
Table 4: Capacity and Utilisation of Resources

The next significant constraint is underwriting (UW) with large average waiting times caused by separation of resources. The uneven distribution of work and varied utilisations between workgroups is because each UW team services a separate sales territory (refer Table 5). This analysis used a general queuing template.
Table 5: Utilisation of Underwriting Teams

Recommendations for managerial action
We recommend the following actions for Manzana’s Fruitvale operations: Recommendation | Benefit | Changing priorities of current process, more focus on RERUNs | Manzana currently has a policy of using a straight FIFO system, though it is interpreted and implemented differently by all the different departments. One recommendation is to actually implement the FIFO system as directed. This way no single type of process will be held back. A majority of the documents that are being submitted late are RERUNs, which are also considered to be the lowest priority by some departments. If the RERUNs are considered as an equal priority, fewer of them will be submitted late.Also, we analysed the contribution margins for each type of request processed at Fruitvale and found that RERUNs have the highest overall contribution margin (refer Appendix A) per employee hour based on the mean processing time.If Manzana were able to process 100% of the renewal requests and eliminate the lost renewals that result from poor performance and slow TAT, during Q2 1991 the firm would have had an additional $3,084,000 of revenues (refer Table 1). This additional revenue net the 7% paid to the underwriters as commissions would create a quarterly branch profit of $2,747,000. In comparison Manzana experienced a $121,000 loss. | Reducing variability | There is a large degree of variance in the time it takes to handle requests.We ran analysis (refer Appendix B) using the mean plus one standard deviation and 95th percentile SCT figures, and found that with the additional variance both the distribution and underwriting teams have more work than capacity.Currently, RERUNs are only released to DCs the working day before due date, posing huge variation in DCs daily workload. Because the due date is known a month in advance, flexibility should be allowed to ensure RERUNs are processed on time without disrupting the flow of new policies. Thus Manzana should prepare documentation for the renewals approximately 30 days before the policy expires. And RERUNs should be distributed to DCs at least one week ahead of the expiration. | Review employee and agent incentives | Manzana should re-visit their employee compensation plan. The current plan promotes the modified FIFO structure, which focuses on new policies first at the expense of renewals. We propose to give agents more incentive for RERUNs, by increasing their commission from 7% to 15%. The table below shows the difference between current and proposed agents’ commission structure: |

Improve capacity and utilisation | Under the mean plus one standard deviation scenario (refer Appendix B), both the DCs and the underwriting teams had more work than capacity. We recommend adding the following additional resources: Distribution | 2 resources | Underwriting | 2 teams | Rating | 2 resources | Policy writing | 1 resource | | Pool underwriting resources | There is little benefit derived from organising the underwriting staff along geographic lines. And there is evidence that it may be detrimental. Analysis of the three underwriting teams indicates that Team 1 processed more policies and had a much higher utilisation level than Team 2 and Team 3 (refer Table 4).From Exhibit 4, we know the weighted average processing time per request for each department. Table 4 highlights the high utilisation rates for UW1, which will eventually cause delays, backlogs and long waiting times. On the other hand, PW has low utilization so that they often have idle time. This indicates that DC and UW1 do not have enough employees and PW has too many employees. Utilising the G/G/C (general) queuing template a more realistic picture of the process is obtained (refer Appendix C). | Matching Golden Gate’s new policy | It is possible for Fruitvale to process RUNs within one day, as shown in Appendix D. However, Manzana would need to increase capacity in line with the additional resources above to accommodate uncertainty in demand and processing times. Our analysis shows that financially the Fruitvale branch would be profitable and able to hire these resources. Fruitvale is already over the typical 20-25 agents per underwriting team and only four agents away from reaching the 20 agent per team mark. Additionally, this puts Fruitvale in a position for future growth. |

If above recommendations are adopted, we anticipate that the Fruitvale branch can still be profitable:

Appendix A – Request Types and Contribution Margins | Revenue | Commission | Contribution Margin | RUN | $6,724.00 | $1,681.00 | $5,043.00 | RERUN | $6,205.00 | $434.35 | $5,770.65 | RAIN | $645.00 | $ | $645.00 | RAP | $0 | $0 | $0 |

| RUNs | RERUNs | RAINs | RAPs | Contribution Margin | $5,043.00 | $5,770.65 | $645.00 | $0 | Total Mean Time (min) | 259 | 172 | 186 | 153 | CM per minute | $19.50 | $33.49 | $3.48 | $0.00 |

Appendix B – Current Worst Case Scenario Analysis Total Time Needed (Mean) | | Budgeted Dailya | DC | UT | RT | PW | RUNS | 5.00 | 342.5 | 218 | 377.5 | 355 | RAP | 14.00 | 700 | 532 | 905.8 | NA | RAINS | 4.00 | 174 | 90.4 | 262 | 216 | RERUNS | 17.00 | 31.16667 | 317.9 | 1283.5 | 851.7 | Needed | | 1247.667 | 1158.3 | 2828.8 | 1422.7 | Available | 1800 | 1350 | 3600 | 2250 | Excess (Difference) | 552.3333 | 191.7 | 771.2 | 827.3 | | | | | | | Total Time Needed (Mean+1 Standard Deviation) | | Budgeted Dailya | DC | UT | RT | PW | RUNS | 5.00 | 496 | 378 | 480 | 406.5 | RAP | 14.00 | 1048.6 | 875 | 1096.2 | 0 | RAINS | 4.00 | 210.8 | 137.2 | 325.6 | 250.4 | RERUNS | 17.00 | 581.4 | 654.5 | 1448.4 | 1013.2 | Needed | | 2336.8 | 2044.7 | 3350.2 | 1670.1 | Available | 1800 | 1350 | 3600 | 2250 | Excess (Difference) | (536.80) | (694.70) | 249.80 | 579.90 | | | | | | | Total Time Needed (95% SCT) | | Budgeted Dailya | DC | UT | RT | PW | RUNS | 5.00 | 640.5 | 536.0 | 561.5 | 446.5 | RAP | 14.00 | 1,509.2 | 1,225.0 | 1,241.8 | | RAINS | 4.00 | 272.4 | 197.6 | 357.6 | 288.4 | RERUNS | 17.00 | 734.4 | 1,067.6 | 1,567.4 | 1,139.0 | Needed | | 3,156.5 | 3,026.2 | 3,728.3 | 1,873.9 | Available | 1800 | 1350 | 3600 | 2250 | Excess (Difference) | (1356.50) | (1676.20) | (128.30) | 376.10 | | | | | | | aThis mix was calculated based on the percentage mix of the 1991 branch totals from Exhibit 7. For RUNs, RAPs, RAINs, and RERUNs the percentages were roughly 12.60%, 36.29%, 9.10%, and 42.01% respectively. These were then applied to the average request |

Appendix C – Average Time in System
Supporting calculations are provided overleaf.

Supporting calculations
To find the inter-arrival time, we used the data in Exhibit 6. First, we calculated out the arrival rate for Distribution Clerks. Since Distribution Clerks handle all requests, the total λ is also the arrival rate for DC. First step, we also found the total RUN, RAP (completed as RUN), RAP (rest), RAIN and RERUN for the first 6 month of 1991.
Since we know 6 months contain 120 days, we can find out the inter-arrival rate λ by little’s law. DC and Rating | Requests | Total days | Little's Law | RUN originating as RUN | 350 | 120 | 2.92 | RUN originating as RAP | 274 | 120 | 2.28 | RAP (excluding completed as RUN) | 1524 | 120 | 12.70 | RAIN | 451 | 120 | 3.76 | RERUN | 2081 | 120 | 17.34 | Total mean inter-arrival rate in days | 39.00 | Total mean inter-arrival rate in hours | 5.20 |

After the DC, the job will pass to next procedure. Since we know the system is in steady state, the utilization must less than 1. Therefore Underwriting and Rating have 39 jobs/ day or 5.2 jobs / hour.
However, even though UW, as a whole, has 39 jobs / day, each underwriting team has different λ (since each region has different number of requests). From Exhibit 7, we can find each team’s total requests.
Team 1 is 14.63 jobs / day or 1.95 jobs / hour. UW1 | Requests | Total days | Little's Law | RUN originating as RUN | 162 | 120 | 1.35 | RUN originating as RAP | 112 | 120 | 0.93 | RAP (excluding completed as RUN) | 649 | 120 | 5.41 | RAIN | 196 | 120 | 1.63 | RERUN | 636 | 120 | 5.30 | Total mean inter-arrival rate in days | 14.63 | Total mean inter-arrival rate in hours | 1.95 |

Team 2 is 13.15 jobs / day or 1.75 jobs / hour. UW2 | Requests | Total days | Little's Law | RUN originating as RUN | 100 | 120 | 0.83 | RUN originating as RAP | 79 | 120 | 0.66 | RAP (excluding completed as RUN) | 434 | 120 | 3.62 | RAIN | 125 | 120 | 1.04 | RERUN | 840 | 120 | 7.00 | Total mean inter-arrival rate in days | 13.15 | Total mean inter-arrival rate in hours | 1.75 |

Team 3 is 11.23 jobs / day or 1.5 jobs / hour. UW2 | Requests | Total days | Little's Law | RUN originating as RUN | 88 | 120 | 0.73 | RUN originating as RAP | 83 | 120 | 0.69 | RAP (excluding completed as RUN) | 441 | 120 | 3.68 | RAIN | 130 | 120 | 1.08 | RERUN | 605 | 120 | 5.04 | Total mean inter-arrival rate in days | 11.23 | Total mean inter-arrival rate in hours | 1.50 |

For PW, since not all RAP will eventually be completed as RUN, the total request is the sum of RUN, RAP (completed as RUN), RAIN and RERUN only. Then, by Little’s Law, the λ is 26.3 jobs / day or 3.51 jobs / hour. PW | Requests | Total days | Little's Law | RUN originating as RUN | 350 | 120 | 2.92 | RUN originating as RAP | 274 | 120 | 2.28 | RAP (excluding completed as RUN) | 0 | 120 | 0.00 | RAIN | 451 | 120 | 3.76 | RERUN | 2081 | 120 | 17.34 | Total mean inter-arrival rate in days | 26.30 | Total mean inter-arrival rate in hours | 3.51 |

The inter-arrival time α (in minutes) is 1/(λ/60): * DC is 11.54 minutes. * UW1 is 30.77 minutes. * UW2 is 34.22 minutes. * UW3 is 40.09 minutes. * Rating is 11.54 minutes. * PW is 17.11 minutes. | DC | UW1 | UW2 | UW3 | RT | PW | λ (in hours) | 5.20 | 1.95 | 1.75 | 1.50 | 5.20 | 3.51 | Weighted α (in avg. min) 1/(λ/60) | 11.54 | 30.77 | 34.29 | 40.00 | 11.54 | 17.09 | Service time p sever ( ma) | 41.00 | 28.40 | 28.40 | 28.40 | 70.40 | 54.80 | Servers (p) | 4.00 | 1.00 | 1.00 | 1.00 | 8.00 | 5.00 | Utilisation ρ=p/(ma) | 0.89 | 0.92 | 0.83 | 0.71 | 0.76 | 0.64 | Capacity (per hour)=λ/utilization | 5.85 | 2.11 | 2.11 | 2.11 | 6.82 | 5.47 |

Appendix D - TAT with Proposed Staff Plan