Case Study: Blake Electronics

CASE:

1. MAI’s proposal directly gives Steve the conditional probabilities he needs (e.g., probability of a successful venture given a favorable survey). Although the information from Iverstine and Kinard (I&K) is different, we can easily use Bayes’ theorem to on I&K information to compute the revised probabilities. As such, does not need any additional information from I&K.

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2. Steve’s problem involves three decisions. First, should he contract the services of an outside research agency? Second, if a survey is warranted, should he employ MAI or I&K? Third, in any case, should the new product line be introduced?

• If Steve decides not to conduct a survey, the decision is to introduce the product with an EMV of $700,000 [= (0.6)($1,500,000) + (0.4)(-$500,000)].
• If Steve decides to conduct the survey, he has to choose between MAI and I&K. If he chooses MAI for the survey, the best choice is to introduce the product irrespective of whether the survey results are favorable or unfavorable. The EMV is $800,000 if the survey results are favorable, while the EMV is only $200,000 if the survey results are unfavorable. The overall EMV of hiring MAI is $500,000 [= (0.5)($800,000) + (0.5)($200,000)].
• If Steve chooses I&K for the survey, the best choice is to introduce the product if survey results are favorable, for an EMV of $940,000. On the other hand, if the survey results are unfavorable, the best decision is to not introduce the product for an EMV of -$300,000 (the cost of the survey). The overall EMV of hiring MAI is $468,800 [= (0.62)($940,000) + (0.38)(-$300,000)].

Comparing these alternatives, Steve should not hire either firm to do the survey. He should simply choose to introduce the produce right away.

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