Manzana Case Study

1. How is the Fruitvale branch doing, and what are the causes of these problems?
Obviously, Fruitvale did a terrible work in 1991. On one hand, compared with itself in the last year, Fruitvale in 1991 got a horribly increase on renewal loss rate, from 33% to 47%; in the meanwhile, the turnaround time was prolonged from 5 days to 6 days. On the other hand, compared to the main competitor, Golden Gate (GG), in 1991, Fruitvale, obviously, lost competitiveness - renewal loss rate was 32% higher, turnaround time was 4 days longer, and the amount of policies was significantly less than GG’s. In addition, according to the company data, the utilization rate of the whole working process was relative high (chart 1). All of these weak performance caused the decline of Fruitvale’s business. The following part will dig in the reasons of these problems.

(1) Increasing renewal loss rate
1) Distinguishing incentive regulations
According to Fruitvale’s regulations, “salary/plus” was only applicable to those employees who can write the new policy above on their established quota. However, for renewal policies, there were no additional incentive rules or bonus. As a result, instead of maintaining and renewing the existing policies, employee were much more willing to build new policy in order to earn more money. Thus, it was hard for Fruitvale to convert existing policies into renewal ones, thereby resulting in losing a lot of agents and customers to GG, as well as a dramatically reduce on revenue. The worst thing was that the employees abandoned the FIFO rules due to the distinguishing incentive regulations. Theoretically, every policy should be processed in the arrive order, but actually, the employees gave higher priority to RUN and RAP than RERUN and RAINS. Thus, they mainly focus on new policies and quotes, ignoring the renewals. As a result, Fruitvale needed to suffer from an extremely huge number of backlogs and a high loss rate of renewals policies.
2) Different priorities in FIFO approach
In 1991, because highly prioritizing RUNs and RAPs, Fruitvale always released the RERUNs to the DCs on the last day before the due date. However, the RERUNs actually took as much work as the other policies. Consequently, the whole process cannot finish the RERUNs on time, thereby causing a huge backlog of RERUNs and the long turnaround time, as well as the high loss rate.
(2) High utilization rate of the process
Based on the existing data, it is feasible to calculate the capacity of the process, and then figure out the utilization rate for every pool in the process. In the whole process, the utilization rate of distribution was already very high. Thus, when the distribution clerks receive the paperwork of RERUNs on the last day before the due date, it was hard for them to handle on all those jobs, thereby losing a lot of renewal policies.
Moreover, a deeper calculation on the underwriting pool shows that underwriting team 1 suffered from a high utilization rate, which was 82.51%, whereas UT3 had a relative lower rate that was 63.33% (Table 2). This kind of non-uniform workload isolated the company from reducing the high utilization rate and aggravated the loss of renewal policies.
2. Consider how Manzana is calculating turnaround time in Exhibit 3. What are they doing wrong? Use the information in the case and process flow principles to *properly* estimate flow time. How do you results compare to what is being reported?
In order to calculate the turnaround time, exhibit 3 directly added WIP in the upstream steps to the downstream steps, which means that it assumed every step was dependent on the others. In another word, it supposed that only when the previous steps were completed can the next step start to work. For instance, the rating team must wait 3.4 days for underwriting teams to finish their job. However, that was contrary to the realistic working flow in which every team could work simultaneously. For example,