Diversity and inclusion; Strategy and general management
Chance models, adaptation, organizational learning, luck, situation, risk-taking
Chance models—mechanisms that explain empirical regularities through unsystematic variance—have a long tradition in the sciences but have been historically marginalized in management scholarship. An exception is the work of James G. March and his coauthors, who proposed a variety of chance models that explain important management phenomena, including the careers of top executives, managerial risk taking, and organizational anarchy, learning, and adaptation. This paper serves as a tribute to the beauty of these “little ideas” and demonstrates how they can be recombined to generate novel implications. In particular, we focus on the example of an inverted V-shaped performance association among the executives featured in one of the most prominent lists of executives, Barron’s annual list of Top 30 chief executive officers. A reanalysis of March and Shapira’s 1992 model provides a novel explanation for why many of the executives’ exceptional performances did not persist. In contrast to the usual explanations of complacency, hubris, and statistical regression, the results show that declines may result from these executives’ slow adaptation, incompetence, and self-reinforced risk taking. We conclude by elaborating on the normative implications of Jim’s chance models, which address many modern management and societal challenges. We further encourage the continued development of chance models to help explain performance differences, shifting from accounts that favor heroic stories of corporate leaders toward accounts that favor those leaders’ changing fortunes.
With permission of the Academy of Management