# Manzana Insurance Case

Topics: Standard deviation, Insurance, Mean Pages: 7 (2311 words) Published: January 28, 2013
Manzana Insurance
Case write-up

Introduction
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. Findings

TAT
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 (σ), 95% of the requests should be finished within (µ+2σ) 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. RERUNs Problem
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...