An extreme-value model of concept testing

We model concept testing in new product development as a search for the mos t profitable solution to a design problem. When allocating resources, devel opers must balance the cost of testing multiple designs against the potenti al profits that may result. We propose extreme-value theory as a mathematic al abstraction of the concept-testing process. We investigate the trade-off between the benefits and costs of parallel concept testing and derive clos ed-form solutions for the case of profits that follow extreme-value distrib utions. We analyze the roles of the scale and tail-shape parameters of the profit distribution as well as the cost of testing in determining the optim al number of tests and total budget for the concept phase of NPD. Using an example, we illustrate how to estimate and interpret the scale and tail-sha pe parameters. We find that the impact of declining concept-testing costs o n expected profits, the number of concepts tested, and total spending depen d on the scale/cost ratio and tail-shape parameter of the profit distributi on.