A theory of strategic problem formulation

We develop a theory of strategic problem formulation in the context of complex, illstructured problems. To do so, we identify a criterion of comprehensiveness, which is the extent to which alternative, relevant problem formulations are identified with respect to an initial symptom or web of symptoms. Assuming bounded rationality, the use of a group of individuals to formulate the problem, and group heterogeneity in terms of information, cognitive structures, and motivation, we theoretically identify a set of impediments that narrow and limit formulation comprehensiveness. These impediments provide a set of design goals, which, if satisfied by an appropriately designed mechanism, can expand problem formulation comprehensiveness. We design a structured process that indeed satisfies the goals and discuss its use in several real-world applications. The paper concludes by discussing future research directions. Designing new business strategies, producing innovations to sustain profitable growth, or developing alternative supply chain configurations to achieve a cost advantage are some the complex, ill-structured strategic challenges organizations must grapple with in order to remain successful in today’s business environment (e.g., Camillus, 2008). Tackling these challenges typically is the domain of groups or teams, particularly those that bring together actors from heterogeneous backgrounds and disciplines, such as top management or cross-functional/ interdisciplinary teams (e.g., Amason, 1996; Bantel & Jackson, 1989; Nickerson & Zenger 2004; Schweiger, Sandberg, & Ragan, 1986; Wanous & Youtz, 1986). To create valuable solutions to such wicked problems, however, these groups first must know what problem it is that they should be addressing. Indeed, as many scientists recognize, “the formulation of a problem is often more essential than its solution...” (Einstein & Infeld, 1938: 92). Research has shown that the initial formulation of a problem is not only one of the most significant determinants of its solution, both in terms of quantity and quality, but also profoundly determines what problem is solved (e.g., Ackoff & Emery, 1972; Boland & Greenberg, 1988; Churchman, 1971; Csikszentmihalyi & Getzels, 1971; Dewey, 1938; Ducker, 1945; Lipshitz & Bar-Ilan, 1996; Nutt, 1992; Simon & Hayes, 1976; Volkema, 1983). Indeed, according to Mitroff and Featheringham (1974), one of the most important challenges associated with problemsolving is the error of the third kind—solving the “wrong” problem by adopting a formulation that is either too narrow or inappropriate (see also Yadav & Korukonda, 1985). Consequently, problem formulation—often under the guise of different terminologies such as problem finding, defining, or diagnosing (e.g., Drucker, 1954; Getzels, 1975; Kilmann & Mitroff, 1979; Mason & 1 Challenges include both problems and opportunities. Throughout the remaining paper we use the more conventional term, problem, but do so with the intent of referring to problems and opportunities. 2 Type I and Type II errors refer to the classical statistical errors of rejecting a null hypothesis when it is actually true and failing to reject a null hypothesis when the alternative hypothesis is the true state of nature.