Learning from Imitators to Increase Your Technological Advantage

Corey Phelps, Professor of Strategy and Business Policy - December 15th, 2009
Phelps - Innovation imiteur

Key Ideas

• The knowledge of innovators inevitably spreads. Imitators thus benefit from innovators’ research efforts.

• Nevertheless, imitators do not reproduce innovations exactly, and they can add to the innovator’s knowledge in return.

• The more widely innovation is spread, the more it contributes to innovators’ own knowledge and to their overall innovation capacity.

Corey Phelps ©HEC Paris

Corey Phelps is Professor of Strategy and Business Policy at HEC. His current research focuses on understanding how companies use strategy alliances, mergers and acquisitions, and (...)

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An innovation benefits not only its originator, but also its imitators. The spread of innovators’ knowledge to imitators (“knowledge spillover”) is inevitable, because knowledge is partly a public good. According to the two authors, the creation of new knowledge comes about either following a new combination of existing pieces of knowledge, or as a result of their reconfiguration. The process of innovation is experimental when innovators use their knowledge and try to alter each piece of it successively in order to observe the results and to draw conclusions from it. This can lead to a certain short-sightedness, related to ignorance of the efforts and advances made by other companies. This means running the risk, in the medium term, of being confined to incremental advances or sub-optimal solutions. The solution for optimizing the innovation process is to integrate external knowledge, which remains uncertain and costly. But reducing the costs and uncertainties associated with using external knowledge is possible if the process is heuristic: learning indirectly from others by observing their behavior and their results, and reproducing whatever works. This happens when researchers evaluate external knowledge and then integrate it into their own research—a filter before moving on to the experimental stage. Certain business models, such as those which integrate open source software, attempt to reconcile profit generation with rapid innovation.


Efforts at innovation, including those incorporated into routines, thus serve as models for other companies (imitators) and to society as a whole. Access to others’ knowledge depends on geographical proximity, the nature of their research efforts, and their sectorial proximity. The manner of appropriation of this knowledge thus creates a knowledge base specific to each company. Social networks, technical publications, conferences, patent applications and attempts at reverse engineering can help to understand the efforts of others (including those who have failed). Applying for patents allows innovators to protect their interests and to bargain, even if an innovation turns out not to be viable for commercialization. By doing this, innovators who need others’ innovation can negotiate mutual rights to use each other’s intellectual property. This fuels the spread of knowledge and increases the number of citations in patent applications, making it possible to trace the origins of innovations.


Imitators’ appropriation of innovations can potentially be compensated for through a feedback mechanism. Imitators contribute to the initial advance by appropriating the innovation and developing complementary knowledge. The initial innovator can learn from these induced innovations and thereby widen his knowledge base, prolonging his own innov­ation efforts, so long as he supplies himself with the tools to do so. This enriches his knowledge base and opens up pathways to new innovations. These opportunities are all the richer for the fact that the external knowledge produced by other companies is directly related to the innovator’s own knowledge. The greater the volume of feedback, and the closer the feedback is to a company’s

initial knowledge base, the more useful the feedback, and the greater the company's capacity to innovate. While the inevitable spread of knowledge can stimulate competition and reduce the profits that a company draws from its innovation, it can also come back in the form of further knowledge. This retroactive learning does not necessarily compensate for losses due to the advances made by competitors, however. The fact that knowledge spillover is inevitable, but also uncontrollable, means that feedback is a source of opportunities for innovators that it would be a mistake to ignore, but that is difficult to plan.

Based on an interview with Corey Phelps, and on his article “Learn­ing from what Others Have Learnt from You: The Effect of Knowledge Spillovers on Originating Firms” (Academy of Management Journal , July 2009) co-authored with Hongyan Yang, assistant professor in the Strategy and Marketing Department of Hong Kong Polytechnic University, and Kevin Steensma, professor of management at the Foster School of Business at the University of Washington.

Application for Managers of Innovating Companies
Application for Managers of Innovating Companies

The spread of knowledge and innovations is not necessarily negative. Its inevitability should spur managers to put in place mechanisms for observing how others use their innovations. This is important not only to prevent the illicit use of innovations, but also to learn from cases where innovations are used in a perfectly legal way. The spread of knowledge is thus a source of opportunity and learning. To benefit, it is necessary to invest in specific human and technical resources to exploit this feedback cycle and analyze its content.


For this study, researchers carried out interviews with scientists and managers of R&D teams in the public, private, and academic sectors. These interviews formed the basis of a theoretical analysis. They then tested their hypotheses on a sample of 87 telecommunications equipment manufacturers between 1987 and 1997. Citations of previous knowledge for patent applications in the United States—obligatory and verified by third-party examiners—served as a reference for analyzing the mechanisms by which knowledge spreads.