Algorithmic Foundations for Business Strategy

by Mihnea Moldoveanu
 
 

Overview — This paper uses tools and models from computational complexity theory and the algorithmics of hard problems that are new to the strategy field in order to address how strategic process and structure adapt to the complex strategic scenarios and predicaments. The paper’s model of strategic problem-solving allows researchers and strategists to distinguish between different levels and kinds of adaptations to complexity of the problem solving scenario. It also allows them to explore and optimize the fit between the canonical strategy problems a firm faces, its stock of problem solving procedures, and its architectural and procedural adaptations to complexity.

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