The Maximum Resource Allocation for Uncertainty Reduction in a Decision-analytic Concept Selection

This article addresses a procedure to identify the maximum resource allocated to uncertainty reduction activity in a decision-analytic product concept selection. Concept selection is one of the most important decisions in product development. Success of a new product depends on the goodness of a concept chosen in the concept selection stage. At the same time, it is one of the most challenging decisions, because engineers need to select a concept facing large degrees of uncertainties about future customer preferences, competitions, economic situations, feasibilities of new technologies, and product costs. Information on a particular uncertain event is sought in order to reduce uncertainty; however, information gathering is meaningful only if the benefit of additional information outweighs the cost of the effort. In decision analysis, the maximum resource allocated to an information gathering effort is defined by the expected value of perfect information (EVPI), which is calculated by assuming that the information is perfectly accurate. This article illustrates a procedure to calculate the EVPI and, thus, the maximum resource allocated to uncertainty reduction activity in a decision-analytic concept selection. The utility of the proposed approach is demonstrated in a decision-analytic concept selection for a public project.