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occurred. This would allow us to quantify the number of minutes that we are under
demand capacity in each service area for 250 days.
Inez has completed her analysis and we are now prepared to discuss some of the
results. The major focus of the analysis is on the use of capacity and the level of
service that is provided to clients. So what are the questions that Inez might ask
about the simulation results? Here are a number that she might consider important:
1. How does the demand for the various services differ?
2. Will Autohaus be capable of meeting the anticipated demand for services?
3. Are there obvious surpluses or shortages of capacity? Given the revenue genera-
tion capability of each service, do the model results suggest a reconﬁguration of
4. Can we be sure that the simulation model has sufﬁcient sample size (250 days)
to provide conﬁdence in the results?
The ﬁrst question does not have an obvious answer from the raw data avail-
able in the Brain . Although the Engine/electrical Diagnosis represents the highest
percentage of service (40%), it has shorter service times for worst, best, and most
likely cases than Mechanical Diagnosis . The comparison to Oil Change also is
not clear. The summary statistics near the bottom of Exhibit 8.24, row 256, show
very clearly that Engine/electrical Diagnosis dominates demand by a substantial
margin. The averages for demand are 258, 209, and 197 minutes, respectively,
for Engine/electrical , Mechanical , and Oil . Thus, the average for Engine/electrical
is about 23% ([258–209]/209) greater than the average for Mechanical , and 31%
([258–197]/197) greater than Oil .
What about the variation of the service demand time? Exhibit 8.25 shows that
the distribution for Engine/electrical Diagnosis is wider than that of Mechanical
Diagnosis or Oil Change . This is veriﬁed by the summary statistics in Exhibit
8.24, row 257, where the annual (250 days) standard deviations range from 71.1 for
Engine/electrical , to 58.4 and 54.1 for Mechanical and Oil . Additionally, the range
of values, max–min, for Engine/electrical (440–50
390) is substantially greater
that Mechanical (395–65
270). All this evidence indicates
that Engine/electrical has much more volatile demand that the other services.
The answer to the second question has already been discussed. Again, we see in
Exhibit 8.24 that the only area where there appears to be any signiﬁcant demand that
is not being met for a service type is for Engine/electrical Diagnosis . The simulation
shows that there were 6 days of unsatisﬁed service. We need to be quite careful to
understand what this suggests for capacity planning at Autohaus. It does not mean
that demand was not met for all the demand that occurred for a service type in 6
330) or Oil (340–70