AMBIGUITY REDUCTION IN NEW PRODUCT DEVELOPMENT PROJECTS

Abstract

In this paper, we argue that ambiguity is an essential component of "fuzziness" in the Fuzzy Front End of New Product Development (NPD), and that a better understanding of how ambiguity emerges and is reduced, is called for. We explore the process by which ambiguity was reduced in four NPD projects, and propose a model that enhances our understanding of this process. Ambiguity arises as multiple interpretations, and interpretations can be understood as hypotheses, hence these can be tested by using the hypothetical-deductive method (HDM). We present a model showing that ambiguity in NPD projects is efficiently reduced by applying the HDM to test the multiple interpretations that give rise to ambiguity and the assumptions underlying these interpretations. We discuss theoretical implications and the usefulness of the model for practitioners of NPD.