Enabling Constraints: When Constraining Organizational Search Improves Innovative Performance?

Abstract

I systematically examine how constraining the degrees of freedom during organizational search affects performance. I label such constraints as “enabling,” reflecting the fact that constraints may channel the collective search toward a better performance. In prior research, constraints in the search process that are imposed by strategy or organizational structure are typically associated with tradeoffs. For instance, constraints may improve average performance at the expense of discovering radical new solutions. Modeling enabling constraints as emerging from imperfect strategies that guide agents in the search process, I show a more refined view in which the tradeoffs apply only to a portion of the parameter space. When organizations focus on large problems relative to the expertise of individual agents and the problems are also complex, then constraining the search improves both average performance and the likelihood of discovering radical improvements. For simple and small problems, unconstrained collective search is uniformly superior. The study has implications for the design of effective strategies and organizations.