The Acme Company is trying to decide whether to market a new product. As in many new-product…

The Acme Company is trying to decide whether to market a new
product. As in many new-product situations, there is considerable uncertainty
about whether the new product will eventually be popular. Acme believes that it
might be wise to introduce the product in a regional test market before
introducing it nationally. Therefore, the company’s first decision is whether
to conduct the test market.

Acme estimates that the net cost of the test market is
$100,000. We assume this is mostly fixed costs, so that the same cost is
incurred regardless of the test market results. If Acme decides to conduct the
test market, it must then wait for the results. Based on the results of the
test market, it can then decide whether to market the product nationally, in
which case it will incur a fixed cost of $7 million. On the other hand, if the
original decision is not to run a test market, then the final decision—whether
to market the product nationally—can be made without further delay. Acme’s unit
margin, the difference between its selling price and its unit variable cost, is
$18. We assume this is relevant only for the national market.

Acme classifies the results in either the test market or the
national market as great, fair, or awful. Each of these results in the national
market is accompanied by a forecast of total units sold. These sales volumes
(in 1000s of units) are 600 (great), 300 (fair), and 90 (awful). In the absence
of any test market information, Acme estimates that probabilities of the three
national market outcomes are 0.45, 0.35, and 0.20, respectively. In addition,
Acme has the following historical data from products that were introduced into
both test markets and national markets:


The company wants to use a decision tree approach to find
the best strategy. It also wants to find the expected value of the information
provided by the test market.

Objective To develop a decision tree to find the best
strategy for Acme, to perform a sensitivity analysis on the results, and to
find EVSI and EVPI.