Manzana Insurance Case
Manzana Insurance Case
This study is designed to determine why the Fruitvale branch of Manzana Insurance is performing so poorly for Property Insurance. Golden Gates, a competitor of Manzana, numbers are estimated to outperform Manzana Fruitvale branch as well. There are several problems that are leading to the poor performance at this branch. This past quarter turnaround time increased again reaching 6 days, where Golden Gate is sitting at 2 days. Also the system is running very close to efficiency, which can cause a problem down the road with changes we recommend.
A big problem with what is going on has to deal with the RUNs and RAINs being of higher priority than the RERUNs for the senior underwriters. The senior underwriters are simply accepting the RUNs and RAINs first because those are more profitable for them, but this is hurting the company as our renewal loss rate hit an all-time high at 47%. Something must be done about these problems if we are going to compete with Golden Gate in this territory and below are these problems in more detail along with recommendations on how we feel these problems can be resolved.
The calculation of TAT was made by multiplying the number of each type of request at each desk by a standard completion time (SCT). The 95% SCT is the time during which 95% of the requests should be taken care of. The company assumes that the variability of the processing time has the normal distribution, which has the characteristic that with a mean of processing time (µ), and a deviation (?), 95% of the requests should be finished within (µ+2?) approximately. In this way the variability has been considered in the calculation of 95% SCT, so as in the TAT. But this method of calculating variability is not a good metric to measure. The right way to measure is using the queuing system to calculate the total time each request will take during the process.
We assume that arrivals appear to be perfectly random, with no discernible pattern of peaking, and interarrival times follow the exponential distribution, so CVa=1. Taking the distribution department for example, we will have calculations of waiting time and total time below: 1-Distribution| mean| standard deviation| CVa| CVp2| waiting time| total time| 95% SCT| RUNs| 68.5| 30.7| 1| 0.200860994| 107.3457966| 175.8457966| 128.1| RAPs| 50| 24.9| 1| 0.248004| 81.43061499| 131.430615| 107.8| RAINs| 43.5| 9.2| 1| 0.044729819| 59.30550122| 102.8055012| 68.1| RERUNs| 28| 6.2| 1| 0.049030612| 38.33080377| 66.33080377| 43.2| See Appendix 5 for more detailed total time calculation.
We can see TAT calculated by the 95% SCT is not consistent with the actual total time. This is not an accurate way to determine what the real TAT time is.
Apparently, the RERUNs should be considered the most important form of business that Manzana conducts. These are customers who have been loyal for at least one year, and are looking to continue to do business with the company. In Essence RERUNs are new policy holders who are looking to extend their policy. The increasing number of late renewals leads to the loss of the renewal requests which represents a significant loss of business and an overall reduction in the number of policies in force. It is factually incorrect though the RUNs are an important factor for the company they are not the most profitable. The revenue generated per new policy is greater than the revenue generated from the RERUNs, $6,720 and $6,210 respectively, but there is not nearly as many new policies issued per year as there is renewals.
Through the first two quarters of 1991 there were 624 RUNs processed compared to 2,081 renewals processed, this makes up 44% of the total business done by the company. They are however more profitable to the senior underwriters who receive $150 for each new policy written and nothing for the renewals. This leads the underwriters to put a high priority on the RUNs even if they were received after the RERUNs. The company also does not pay as much commission to the agents for RERUNs as they do for RUNs. They pay 25% for new policies and 7% for renewals.
Because the RERUNs can change each year they are not released to the DC’s until the last day before the renewal date. This is a problem because the system is not acting as a true FIFO system, instead the RAINS and RUNS are processed first while the RERUNs are put on the back burner. This practice causing many of these policies to expire before they are renewed (44% late renewals in the current quarter). Agents who do not receive a new quote on or before the expiration date commonly recommend a different company to their clients resulting in renewal losses by Manzana, which eats away a major part of the company’s revenue.
There are several problems with the current system at Fruitvale, Firstly the system is running dangerously close to the efficiency this first and foremost needs to be addressed in the DC department as well as the underwriters department. There are several ways to remedy this issue; one way would be to add staff through hiring new people to these departments, this would add unwanted overhead to the company though it would remedy the capacity issue, shown in Appendix 1 that how much capacity improved and Appendix 4 represents how much time in queue reduced by hiring one unit of each process. Another solution would be to update the rating and policy writing department both can be done using automation this would free up some of the current staff to be retrained and reassigned to the two inefficient departments. This would create more efficiency in both covering any variability that arises as well as increasing capacity.
This would cost upfront money in system updates and training, but in the long run it would make the system run more smoothly. Another issue that must be addressed id the fact that the RUNs and RAINs are getting priority over the RERUNs which is much more profitable then both. This is due to the fact that it is more profitable for the senior underwriters to process the RUNs and RAINs first because there is a bonus associated with the new policies issued. This causes the RERUNs to get backed up leading to renewal losses which equal lost profits. This incentive program needs to be re-evaluated to determine if it is what’s best for the company. The FIFO system that is supposed to be company policy is not being followed especially in the Underwriting department.
This needs to change and be strictly followed this will allow the company to be able to process the RERUNs more effectively. This raises another issue which is when to release the RERUNs to the DC’s so they can get quotes to the agents on or before the expiration date. Appendix 3 shows the revenues and profits, comparing the company’s FIFO system and general FIFO system. The current system releases the RERUNs the day before the expiration date, this leads to renewal losses due to quotes given past the expiration date. Instead of releasing the RERUNs the day before the expiration date they should be released 3 days before this date.
Though this will result in a less accurate policy, it will help cope with any variability. If any changes happen with the quote between the release date and the expiration date a RAIN can be issued to amend the policy. Another issue that needs to be addressed is the utilization of the underwriting teams within the different territories. Currently the utilization in territories one and two is 90.6% and 80.4% respectively and 69.4% in territory three which leads to more idle time in territory three and very little room for variability in territories one and two. It is recommended that the underwriting teams work unilaterally through the territories, this would increase the turnaround times in the department and improve the efficiency in territories one and two.
The company will be sacrificing the personal relationships with the agents, but it will reduce the renewal losses and give the company a better chance at the new policies because the turnaround times will be reduced. The last issue that needs to be addressed is the current system of measuring TAT time, because the current system is outdated and inaccurate. It has already been shown that the flow rate needs to be determined by the bottleneck resource which is the DC’s.
University/College: University of Chicago
Type of paper: Thesis/Dissertation Chapter
Date: 17 November 2016
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