Decision-Making in Complex Systems: Relationship Between Scale of Change and Performance

Empirical research as well as numerous cases studying managers across diverse disciplines, cultures, and industries reveal consistent patterns of counter-productive decision-making. In this regard, decision-makers appear to exhibit an unmistakable tendency to 'over-intervene' in the systems (companies, organizations, cities, communities, etc.) they are responsible for. This suggests an inadequate appreciation and understanding of the dynamics underlying decision-making, generating unwarranted and excessive fluctuations and instability in organizations. Numerous studies have observed such phenomena in simulated and experimental settings. Research results, as well as in-depth case studies highlight a number of assumptions and mental models commonly held by decision-makers and managers with adverse effect on organizational dynamics and performance. This paper reports on extensive empirical research and findings elicited from subjects interacting with realistic simulation models of organizations (microworlds) to investigate the relationship between scale of intervention and performance. The results show that while large-scale interventions appear to be effective in the start-up phase of systems (e. g. new products, markets, companies) they are generally counter-productive in mature systems operating at steady state. The results support findings from organizational case studies, notably, the extensive study of 'Good to Great' firms. Copyright (C) 2010 John Wiley & Sons, Ltd.