STATISTICS - PROBABILITY THEORY IN DECISION MAKING
a. States of Nature/Expected Payoffs
High Sales (3000x.2) = 600
Medium Sales (2000x.5) = 1,000
Low Sales (-6000x.3) = -1,800
Expected Payoff = - 200
Expected payoff for A2: 0
Recommended decision: Probability analysis indicates that the risks of uncertainty associated with the proposed venture outweigh the potential gains associate with the venture. In the expected payoff assessment for A2 presented above, the assumption is that no costs are associated with not proceeding with the proposed venture. The recommendation, therefore, is to shelve the proposed venture until (a) sales projections improve, (b) profitability projections improve, and (c) some combination of the two occur that will result in a positive expected payoff.
Assuming that a potential venture is being considered to sell a specific brand of coffee in Mumbai, the problem confronting the decision-maker is to determine how well this brand of coffee might be received by consumers in Mumbai. Assuming further, that no reliable information is available in relation to the profitability of selling this brand of coffee in Mumbai, the decision-maker must determine what types of information may be used to analyze the problem. Within this context, the types of information that would be useful are as follows:
Coffee brands that are sold in Mumbai
Identification of cities with demographics similar to those of Mumbai where (a) coffee brands that are sold in Mumbai also are sold, and (b) the brand proposed for sale in Mumbai also is sold
Data from qualifying cities (as defined above) indicating how well the coffee brand proposed for sales in Mumbai competes in similar cities against coffee brands now sold in Mumbai
Based on the data described above, the decision-maker can infer how well the coffee brand proposed for Mumbai will do agai
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