Algorithmic Foundations for Business Strategy

Abstract

I introduce 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 the implementation of solutions. This approach allows us to distinguish among levels of sophistication in the strategic management of complexity, 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’ are key strategic differentiators for firms facing complex problems.

Keywords: strategy, algorithms, problem solving

JEL Classification: L23