Case 2- Manzana Insurance
MGMT 601 –Monday - Spring 2011
Group 6- Amit Deshpande, Alex Coates, Natalie Lopez
Overall Performance of Manzana-Fruitvale:
The Fruitvale branch of Manzana Insurance is struggling right now. “Branch profitability was declining.
The backlog policies had increases since 1989, and the number of new policies and endorsements
appeared to be stagnating.” To make matters even worse their main competitor, Golden Gate, had no
problem taking business away from Manzana while they were struggling. Exhibit 1 shows some of the
key metrics for Manzana the past two years and for Golden Gate this year. This shows just how bad of
shape Manzana-Fruitvale is in right now. Their renewals are decreasing and they have an extremely
high renewals late number (44%). This has led to a very high renewal loss rate (47%) while Golden
Gate’s is at just 15%. Even though renewals are the least profitable program for them, losing half of
your current business each year is a major problem. Something has to be done to fix this. The current
practice at Manzana was to do the new policies (RUNs and RAPs) first. These represented the highest
value to the company and employee but doing this has greatly hurt the renewals (RERUNS). When
employees get to work in the morning they sift through their work pile for RUNs and RAPs to do first.
This practice was not considered company policy but it seems the underwriters were encouraged to do
it. In the end, giving priority to new policies pushed renewals to the back of the line and is the main
reason that Manzana is seeing ever increasing late and lost renewals. If the company wants the
employees to focus on the more profitable new policies they must understand that renewals are going
to suffer. Although renewals do not present the same initial value of new policies, losing renewals still
represents a significant loss of business.
In addition to the poor renewal numbers, Manzana’s turnaround time is much longer than Golden Gate.
Golden gate currently has a turnaround time of 2 days (with a promise for 1 day turnaround in the
future). On the other hand, Manzana saw their turnaround increase over the past year to 6 days. This is
a huge competitive disadvantage for Manzana when agents typically steer their clients to the company
with the lowest turnaround time. Turnaround time (TAT) is a key metric in the insurance industry. It
can simply be defined as the number of days between the receipt of a new policy and the issuance of a
final policy. Agents work mostly on commission so they will naturally lean towards a company with a
low TAT. A lower turnaround time means they will get their commission sooner and will be able to sell
more policies. “It is not uncommon for an agent to call an insurer for an estimate of the company’s TAT
and then refer business elsewhere if issuing a new policy would take too long.” By having such a long
TAT (compared to Golden Gate) Manzana is just handing policies over to Golden Gate. This combined
with their huge renewal loss rate points to the fact that Manzana is in deep trouble. To make matters
worse, Golden Gate has announced that they will implement a guaranteed turnaround time of 1 day.
Meanwhile Manzana is currently sitting at a TAT of 6 days. Drastic changes need to be made at
Manzana if they want to stay in business
Theoretical TAT:
The actual TAT at Manzana is currently 6 days. This means that the average policy takes 6 days to
create. However, there is also a theoretical TAT. This is the TAT they should be able to achieve if
everything is normally done. Exhibit 2 shows the first way to find theoretical TAT. Typically Fruitvale
receives 40 requests per day. This can be a rough estimate for the flow rate for an average day.
R=40/day. We also know that for the week ending 6 September 1991 they had 82 requests in process.
This means that the inventory is 82. I=82. Using Little’s Law, which is T=I/R we find that the flow time
for an average policy is 2.05 days. This is the theoretical turnaround time for Manzana-Fruitvale and is
much lower than their actual TAT.
Another way to find their theoretical TAT is using a flow chart. This can be found in Exhibit 3. The
inventory numbers for this were found in the case (Exhibit 3). The flow times for each stage were also
found in the case (Exhibit 4) and named “weighted average processing time per request”. With this
information the flow rate (R) for each stage can be calculated using Little’s Law. After all the flow rates
are calculated the bottleneck can be found. This is the stage that has the lowest flow rate. This is the
weakest link and will establish what the maximum flow rate for the entire process is. In this case, Policy
Writing is the bottleneck. That stage has a flow rate of 3.3/hour or 24.75/day. This is lower than the
flow rate found from Manzana’s estimation of 40 requests per day (this is actually the demand rate).
24.75 days can be used as the flow rate for the process and 82 can be used as the inventory. This leads
to a total flow time of 3.31 days. This calculation is shown in Exhibit 4. 3.31 days is another estimate of
theoretical TAT (in addition to 2.05 days. While this is a longer time than the first calculation gave it is
still much shorter than their current 6 day actual TAT.
Causes Of The Problem:
The current procedure to calculate TAT assumes that the activities wait for earlier activities to complete.
From Exhibit 3, the Underwriting team starts work after 0.6 days after distribution clerk finish their
current work. It is assumed that policies move from one activity to another in batches equal to the total
number of current policies (work) with that department. Thus, TAT calculation as shown in Exhibit 3 (of
the case) seem to be incorrect.
The theoretical and actual TAT’s for Manzana are clearly very different. Theoretically it should be about
2-3 days but in reality the turnaround time is 6 days. They are not achieving anywhere close to the TAT
that they could be and there are a number of reasons for this. One main reason for this problem is that
the current practice at Manzana is to give priority to RUNs and RAPs over RERUNs. Renewals are less
profitable to the company and employees so they are often not allowed to interfere with the progress of
the more profitable new requests. This is the main reason for the increasingly late renewals and loss of
renewals. In addition to delaying renewals and leading to lost policies, this practice also took up some
of the employee’s time. They most likely spend a good deal of time searching through policies until they
find a RUN or RAP. This can take up some of their time that could otherwise be spent on processing
policies. Another cause of their problem is the attention they are paying to RAPs. These only amount to
a new policy 15% of the time yet they are being given priorities over renewals that almost certainly will
lead to a consistent sale for several years if handled right. In reality a new policy arriving from a RAP is
pretty rare and the priority being given to them seems out of whack. Also, the fact that only 15%
become RUNs is a source of variability in the system that can cause congestion and increase the average
flow time.
The due date for RERUNs is known 30 days in advance but they are being sent to the Distribution Clerks
only 1 day in advance. This is adding to the late and lost renewals that have become such a problem for
Manzana. Waiting for the last day makes the process less flexible and can also lead to a higher
variability. Both of these raise the flow time and thus the actual TAT. The salary/plus program may be
to blame for Manzana’s problems as well. These employees receive an incentive payment for each new
policy written, but receive nothing for a renewal. When there is an incentive for employees to ignore
RERUNs and focus on RUNs that is what will most likely happen. Manzana has seen the impact of the
commission based salary for new policies only. It has led to a disregarding of renewals and an extremely
high late/loss rate for these policies that employees have no incentive to complete.
Surprisingly, even the way Manzana calculates TAT may have led to some of their problems. In the case
(Exhibit 3) their calculations for Total TAT are shown. Instead of using the time for an average policy
they use the 95th percentile standard completion time. This is a much higher number than the average
(50th percentile). That is how they got such a high TAT (8.2 days). This is more of a worst case scenario
type of calculation and should not be used in an industry when having a lower TAT can lead to much
more business. Golden Gate looking much better in comparison (2 day TAT and future 1 day on RUNs)
cannot be ignored as a reason for Manzana’s recent struggles. While John Lombard may think that
Golden Gate will not be able to live up to their 1 day promise, the possibility has to be accepted. The
guarantee is only for RUNs and if Golden Gate gives these the highest priority they may just be able to
pull it off, which will lead to even bigger problems for Manzana.
Recommendations:
Manzana should modify their strategy in terms of the order in which they review policies.

They are correct that a FIFO strategy will keep them most efficient, but their modifications to
the FIFO strategy are causing problems. Not only are they wasting time in trying to sort the
policies, they are doing it wrong. They should focus on RUNS first; RERUNS second, and RAINS
and RAPs last (only 15% of RAPs become RUNS).
They should also modify procedure for handling RERUNs.

Their renewal loss rate is absolutely too high, mostly due to being late. There is no excuse for
being late, especially when they always know the date they need to provide the renewal well
ahead of time. Manzana should prepare documentation for the renewals approximately 30
days before the policy expires. They should then ensure that the agents receive the paperwork
at least 1 week ahead of the expiration. If the due date is known a month in advance then they
should be sent to Distribution much sooner. Even a week in advance would greatly increase
their ability to adjust their schedules to make sure RERUNs are processed on time without
disrupting the flow of new policies.
Invest in procedure standardization.

While the variation in the insurance business is high overall, be opportunities to standardize
types of clients to eliminate rework.
Re-visit Manzana employee compensation.

The salary plus employees currently receive a bonus for every new policy written. This
promotes their modified FIFO structure, which the case proves can be counter productive. The
Salary-Plus program has also added approximately 10% to the Salary expense, and no significant
increase in the number of new policies written.
Marketing Opportunities:
1. While hard to tell, due to the method of calculating TAT, Manzana should evaluate their capability to
turn around new requests for underwriting first, to result in a turnaround time of one day. They could
then market this as direct competition to the new Golden Gate strategy.
2. Manzana should market that they can turn around ANY policy in less than 3 days, and if not, they will
pay agents a penalty of 15%. This option requires them to go to a true FIFO strategy. Although GG will
win out on RUNs, Manzana can gain an advantage in the other 3.
The Fruitvale branch manager states that the branch is overstaffed. However, the manager fails to
understand that there is a significant variation in the input process (processing time for different types
of requests) that requires reserve capacity. There must be a compromise between productivity and
utilization so that there is enough flexibility within the system to respond to the inherent variability in
demand and request processing times.
Exhibit 1:
New Policies
Endorsements
Renewals
Turnaround time
(avg.)
Renewals late
Renewal loss rate
Manzana Fruitvale
This Year
Last Year
326
278
206
235
2063
1253
6 days
44%
47%
5 days
20%
33%
Golden
Gate
This Year
375
300
1400
2 days
NA
15%
Exhibit 2:
R=40/day
I=82
T=I/R
T=82/40
TAT=2.05 days
Exhibit 3:
DISTRIBUTION
I=16
R=23.4/hr
T=.683 hrs
Exhibit 4:
Policy Writing = Bottleneck
R=3.3/hr or 24.75/day
I=82
T=I/R
TAT=3.31 days
UNDERWRITING
I=52
R=109.86/hr
T=.473 hrs
RATING
I=11
R=9.36/hr
T=1.173 hrs
POLICY WRITING
I=3
R=3.3/hr
T=.913 hrs