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Opportunity Selection in Self-Managing Organizations: The Limits of Crowds

This paper takes a critical perspective on self-managing organizations, i.e., crowds and online communities. I theorize that they are limited in their ability to select and integrate new opportunities (e.g., ideas, project proposals) and cumulatively develop technical systems (e.g., software systems). I compare self-managing organizations to traditional organizations under different complexity conditions. Therefore, I distinguish two opposing selection mechanisms: centralized opportunity selection, typifying traditional organizations, and decentralized opportunity selection, typifying self-managing organizations. Using a computational model, I let these mechanisms cumulatively develop a technical system architecture, which I formalize as a design structure matrix. The model shows that the selection mechanisms’ advantages relative to each other depend on the complexity conditions. Centralized opportunity selection is more effective in achieving rich functionality under high interdependence and many available opportunities, while decentralized opportunity selection is more effective in this regard when few opportunities are available. Surprisingly, when considering indicators of the architecture maintenance costs, decentralized opportunity selection can be outperformed by centralized opportunity selection. The paper contributes to the discussion on digitally enabled organizational forms by outlining the boundary conditions of self-managing organizations imposed by complexity. It also contributes to research on systems architectures by relating organizational characteristics to organizational outcomes.