Author Abstract
I introduce algorithmic and meta-algorithmic models for the study of strategic problem solving, aimed at illuminating the processes and procedures by which strategic managers and firms deal with complex problems. These models allow us to explore the relationship between the complexity of an environment, the sophistication of the problem-solving processes and procedures used to optimally map problem statements into strategic actions, and the organizational structures that are best suited to implementing solutions. This approach allows us to distinguish among levels of sophistication in the strategic management of complex predicaments, specifically among rational, irrational, quasi-rational and super-rational problem-solving processes and responses of strategic managers and organizations. It highlights a set of dynamic search and adaptation capabilities that can be studied via the algorithmic and computational properties of the problems they are meant to solve and the efficiency and reliability by which they search a solution space. It points to several new components of competitive advantage that are linked to the complexity adaptation of a firm: “offline problem solving” and “simulation advantage” emerge as key strategic differentiators for firms facing complex problems.
Paper Information
- Full Working Paper Text
- Working Paper Publication Date: October 2016
- HBS Working Paper Number: HBS Working Paper #17-036
- Faculty Unit(s): General Management
