Manzana Case Report

I. Background

While studying the Manzana Case, our team was introduced to the problem of Fruitvale Branch in process management. For the second quarter in a row, current office was outsider in policy sales among all other Manzana branches, and sales decreased in comparison with the same period last year. Branch Manager was notified regarding the unpleasant issue by head office note, which contained approximate calculations of processing capacity, where each step of the process seemed to be line with productivity performance. However in fact, applications backlog significantly increased due to increase of turnaround time (hereinafter -TAT) and percentage of late renewals doubled from the last year leading the increase of renewal loss rate. Responsible managers needed to react in a short time, given the fact that local competitor, acquiring the market share, introduced new campaign of one day TAT of policy issuance to all agents.

II. Analysis

After analyzing provided data and studying the details of the case, we came up that declining profits of affected branch were due to late policy renewal issuance that caused customers to be diverted to other carrier by insurance agents, therefore company suffered renewal fee losses. Additionally, average TAT of three days increased to more than five days, which also posed incremental customer loss because of inconvenient time frames. We tried to find the root of these issues, by addressing the four main steps of policy issuing process. According to the exhibit 1 of the memo (exhibit 4 of the case), we calculated maximum capacities of each employee at each step by dividing 7.5 working hours to weighted average processing time per request and multiplying it by 60 minutes. Actual load was calculated by summing up each type of processed requests obtained from exhibit 2 of the memo (exhibit 7 of the case) and dividing them by 120 as we wanted to find the amount of actual processed applications per day, which equaled to 39 requests for first three stages, and 26 for the policy writers. And finally we calculated the capacity utilization of each step, by dividing average daily work load to maximum capacity of all employees in that stage. All figures of calculations you may find at Exhibit 3 to this memo. From presented data, you may understand that neither of the steps is fully utilized, and with capability to process 39 requests per day, only underwriting stage is currently stacking a huge number of backlog, making it 52 requests out of 82 in total, according to exhibit 4 of memo (exhibit 3 of the case). That means, that process bottleneck is within this step. However it’s not because of its capacity, but due to prioritized sequence that underwriting managers used, while default FIFO was modified. Prioritizing the application types by its profitability, proved to be ineffective not only from process perspective, but also from profitability