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Applying simulation to a decision problem 189
Profit ($)
No. of
simulations Probability
−200 000 to under −100 000 26 26/500 = 0.052
−100 000 to under 0 120 120/500 = 0.240
0 to under 100 000 213 213/500 = 0.426
100 000 to under 200 000 104 104/500 = 0.208
200 000 to under 300 000 34 34/500 = 0.068
300 000 to under 400 000 3 3/500 = 0.006
Mean profit = $51 800
500 1.000
This distribution is illustrated in Figure 7.4. It can be seen that it is
likely that profit will fall between $0 and $100 000. There is, however, a
probability of 0.292 that the product will make a loss and it is unlikely
that profits will exceed $200 000.
Stage 6: Sensitivity analysis on the results of the simulation
Hertz and Thomas 1 argue that Monte Carlo simulation is itself a comprehensive
form of sensitivity analysis so that, in general, further sensitivity
tests are not required. However, if the decision maker has some doubts
Probability
0.5
0.4
0.3
0.2
0.1
−200 −100 0 100 200 300 400
Profit ($000)
Figure 7.4 – Probability distribution for profit earned by the commemorative plate