Parallel R&D Paths Revisited

Abstract

This paper revisits the logic of pursuing parallel R&D paths when there is uncertainty as to which approaches will succeed technically and/or economically. Previous findings by Richard Nelson and the present author are reviewed. A further analysis then seeks to determine how sensitive optimal strategies are to parameter variations and the extent to which parallel and series strategies are integrated. It pays to support more approaches, the deeper the stream of benefits is and the lower is the probability of success with a single approach. Higher profits are obtained with combinations of parallel and series strategies, but the differences are small when the number of series trial periods is extended from two to larger numbers. A "dartboard experiment" shows that when uncertainty pertains mainly to outcome values and the distribution of values is skew-distributed, the optimal number of trials is inversely related to the cost per trial.