Disruption theory as a predictor of innovation success/failure

Purpose – Executives and managers are in need of research that will elevate the pursuit of successful innovations from a gut‐level, intuition‐driven art to something more closely resembling a science based on repeatable processes with predictable results. this paper aims to address this issue. Design/methodology/approach – Using Intel Corporation's proprietary data the author conducted a number of experiments designed to test disruption theory's impact on predictive accuracy. Findings – After training in the rules of disruptive theory MBA students were up to 50 percent more accurate in correctly identifying the survivors and failures, constructing, collectively, a portfolio with a survival rate of up to 15 percent. Research limitations/implications – Intel's New Business Initiatives (NBI) division provided data on a portfolio of 48 new business ventures that were granted seed financing, a sum that ranged between $250,000 and $2 million, between approximately 1995 and 2005. Practical implications – Disruption theory can deliver statistically significant and practically material improvement in the ability to innovate successfully. Disruption theory can be used to shape existing innovation ideas in ways consistent with the theory's prescriptions. Originality/value – As of now the disruption theory of innovation is the only one with evidence to support the assertion that it can improve predictive accuracy.