Demystifying Disruption: A New Model for Understanding and Predicting Disruptive Technologies
Ashish Sood and Gerard J. Tellis, 2010, 10-102
For its many benefits to consumers and markets, technological change may be most notable for the challenge it presents to incumbent firms. From microcomputers to MP3 players, there are numerous examples of established firms misinterpreting the impact of new technology, leading to their own demise.
Why do firms fail when faced with technological change? Of several prominent theories, the theory of “disruptive technologies” has been dominant. This theory posits that disruption occurs when a technology that is superior on a new dimension that appeals to a niche, but inferior on a dimension that appeals to the mass market, improves on the latter dimension to meet the needs of the mass market. The theory suggests that such a lower attack is potentially “disruptive,” because managers of incumbent firms may ignore or belittle a seemingly inferior technology. However, this theory lacks precise definitions, suffers from tautologies, lacks adequate empirical testing, and has no predictive model.
Authors Sood and Tellis attempt to remedy these problems with a new schema, new empirical data, and a new predictive model. The proposed schema has clear definitions for types of technologies, types of attacks, and domains of disruption, and explains the dynamics of competition between new and dominant technologies. They derive seven testable hypotheses, which they test using historical data on 36 platform technologies from seven markets. Further, they carry out an out-of-sample predictive analysis that shows good to high sensitivity and specificity in predicting disruption.
To begin, the authors distinguish between an upper attack—where an entering new technology performs better than the dominant technology—and a lower attack—where an entering new technology performs worse than the dominant technology on the primary dimension of performance. They also identify three domains of disruption, in each of which disruption could occur independently: technology, firm, and demand. Technology disruption occurs when the new technology crosses the performance of the dominant technology on the primary dimension of performance. Firm disruption occurs when the market share of a firm whose products use a new technology exceeds the market share of the largest firm whose products use the highest-share technology. Demand disruption occurs when the total share of products in the market based on a new technology exceeds the share of products based on the dominant technology.
The results of their analysis suggest that many aspects of the disruptive technologies theory are exaggerated. Though an entrant disrupting a well-funded, giant incumbent with a lower attack makes for a good story, such disruptions account for only a small fraction of all cases—for example, only 8% of all technology disruptions and 25% of all firm disruptions were caused by entrants using a lower attack. The hazard of disruption by incumbents is significantly higher than that by entrants. Further, technologies that adopt a lower attack are not cheaper than older technologies.
The analysis reveals other interesting patterns of technology competition. First, at many points in time, competing technologies co-exist. In some cases, disrupted technologies continue to survive and co-exist with the new technology by finding a niche market. Moreover, technology disruption is not permanent due to multiple crossings in technology performance.
Second, new secondary dimensions of performance frequently emerge among competing technologies. For example, while competition in monitors occurred in mainstream markets on the primary dimension of performance (resolution), at the same time, LCDs introduced the dimension of compactness, plasma the dimension of screen size, and OLED the dimension of convenience and low power consumption. A new technology almost always introduces a new dimension of importance to niche markets—even while they are competing with the old technologies on a primary dimension for the mainstream segment.
Third, some technologies experience disruption in one domain but not another. For example, incandescent lamps continue to dominate in the demand domain, even after being disrupted in the technology domain by better-performing technologies.
Fourth, most technologies do not improve smoothly over time as the theory of disruptive innovations predicts. Neither do most technologies improve in the shape of S-curves. Rather, improvement is sporadic with many periods of no improvement followed by spurts of big improvements. For example, gas discharge was stagnant for many years and lost technological superiority to a competing technology, arc discharge, which improved frequently every few years after its entry. However substantial improvement after almost 20 years propelled gas discharge into a position of superiority again.
Finally, firms that introduce a new technology may not be the ones to cause disruption. For example, while Optel Inc. introduced LCD technology, Samsung disrupted the incumbents and became the market leader. So first-mover advantage is not sufficient for disruption.
Ashish Sood is Assistant Professor of Marketing, Goizueta School of Business, Emory University. Gerard J. Tellis is Professor of Marketing, Director of the Center for Global Innovation, and Neely Chair in American Enterprise at the Marshall School of Business, University of Southern California.
Understanding Disruptive Technologies: Who Wins, Who Loses? (2010) [Article]
Innovation Diffusion and New Product Growth
Eitan Muller, Renana Peres, and Vijay Mahajan (2009) [Book]
Growth Acceleration across Technology Generations
Stefan Stremersch and Eitan Muller (2007) [Report]
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