Manzana Insurance Case

Manzana Insurance, the second largest property insurance company in the country, is currently facing stiff competition from its arch rival Golden Gate Insurance. Over the last few years Manzana Insurance has been facing several operational issues which have led to a substantial decrease in the number of policy renewals. In addition, Golden Gate has come up with aggressive strategies and Manzana faces the possibility of losing its existing policy holders to Golden Gate.
In this study we will look at the major issues Manzana is facing, analyse the causes behind the same and suggest feasible solutions and recommendations to improve its turnaround time. We have recalculated the turnaround time using the mean time required for processing a task (instead of using 95% SCT per request). Further details and calculations are provided in Exhibit 1 – Turnaround time calculation for existing system. Each of the processes RUN, RAP, RAIN and RERUN are processed using a First In, First Out method with priority given in the order RUN, RAP, RAIN and RERUN.
Therefore, the backlog queue is also treated as a priority queue with the priority as mentioned before. Whenever, there is no task or job to be processed, the Server (clerk or employee) waits or remains idle till the Job becomes available. According to our analysis, using the Gantt chart for the existing process, the turnaround time for the existing system turns out to be, 836. 2 minutes, i. e. 1. 86 days. Job Flow and Capacity Utilization From the analysis of the current system, we notice that the distribution and underwriting departments are being efficiently utilized (88% and 82% respectively).

However, the capacity utilization of rating and writing departments is only 76% and 64% respectively. The fact that in spite of under-utilization of resources, Manzana still has a high turnaround time suggests that the prioritizing strategy used is flawed and has to be reworked. The current job flow requires the underwriting teams to process requests only from their assigned territories. This leads to overloading of a team during a particular period while the other teams are heavily under-utilized. This inturn adds to the high turnaround time experienced by Manzana.
Our capacity utilization calculations (Exhibit 3) reveal that there is a lot of volatility in the capacity utilization of the underwriting teams. This leads to overloading of one of the teams while the other teams are underutilised. Manzana should alter its policy with regards to the same and distribute the work load across the three teams irrespective of their assigned territories. The turnaround time using the suggested method of prioritization is given in Exhibit 3. From the corresponding Gantt chart, we see that the new value of TAT is 569. 80 However, this includes the initial setup time of 122.2 minutes (during which the Policy Writer is considered idle and waiting for the job to arrive from the previous departments).
This waiting time would disappear in the steady state case. Therefore, the effective turnaround time is 569. 80 – 122. 2 which is approximately equal to 450 minutes (7. 5 hours or 1 working day). The effective time taken in the Rating department is 515. 8 – 46. 7 which is approximately equal to 470 hours which is slightly higher than 1 working day. Therefore, with our new suggested model, it may be required to account for 20-30 minutes of overtime work to handle the same (or extend the work hours to 8hrs per day)