Using scale-free processes to explain punctuated-change in management-relevant phenomena

Abstract

The way organisations change shows evidence of ‘extreme dynamics’, but management research is based on Gaussian statistics that rule out these extremes. On occasion, deviation-amplifying mutual causal processes cause extreme events characterised by power laws. They seem ubiquitous; we list 103 kinds of them – social and/or organisational or managerial rank/frequency distributions. We draw a ‘line in the sand’ between scale-bound processes (characterised by Gaussian statistics and based on independent data points, finite variance and emphasising averages) and scale-free processes (characterised by Paretian statistics reflecting interdependence, positive feedback, infinite variance, and extreme outcomes). Quantitative journal publication depends almost entirely on the former type. We draw on complexity theory to propose redirecting management theory and research so as to make it more relevant to management practitioners. First, we propose a taxonomy of scale-free theories that explain the fractal properties of various kinds of organisational rank/frequency distributions and why they emerge. Second, we apply the scale-free theories to specific social/organisational examples.