Organizations do not lose the ability to innovate because they stop trying. They lose it because the behavioral system that produces innovating decays gradually and largely invisibly, while every conventional measure of innovation health continues to signal strength. Kodak, Nokia, and Blockbuster were not failing organizations by conventional innovation metrics in the years before their competitive collapse. They were in flow decay, producing an Innovation Mirage. This paper identifies the structural reason why. Innovation research measures innovation as a stock of outputs: patents, product launches, R&D expenditures. These measures are constitutively incapable of detecting whether the system producing them is healthy or already in decay. What decays is not the output but the flow: the ongoing organizational behavior of sensing, exploring, mobilizing, and executing. The Innovation Mirage names this condition precisely: not merely that output metrics lag behavioral decay, but that the measurement system and the failing system are one and the same. Stock measures are produced by the behavioral cycle that is decaying, so as the cycle slows they actively obscure the declining rate at which outputs are generated. Drawing on Herbert Simon’s architecture of complexity and complex adaptive systems theory, this paper develops a five-element behavioral model of organizational innovating (leadership activation, empathetic sensing, creative exploration, social network mobilization, and execution and stabilization) and specifies the cascade mechanism through which imbalance among these elements produces Organizational Flow Decay. Five theoretical contributions are advanced spanning measurement, mechanism, integration, prediction, and micro-foundational positioning, with seven theoretical propositions, including three counterintuitive predictions not derivable from any existing innovation framework, that define the theory’s empirical frontier. This paper develops a behavioral systems theory of innovating — a theory specifying the organizational conditions under which the capacity to innovate is sustained or silently lost. The practical consequence is direct: organizations can detect and interrupt flow decay before output metrics reflect it, but only if they stop measuring what they’ve produced and start measuring whether the system producing it is still cycling.
David S. Morgan (Thu,) studied this question.