Using the Crowd as an Innovation Partner

Kevin J. Boudreau; Karim R. Lakhani

Article | Harvard Business Review | April 2013

Using the Crowd as an Innovation Partner

by Kevin J. Boudreau and Karim R. Lakhani

Abstract

More and more organizations are turning to crowds for help in solving their most vexing innovation and research questions, but managers remain understandably cautious. It seems risky and even unnatural to push problems out to vast groups of strangers distributed around the world, particularly for companies built on a history of internal innovation. How can intellectual property be protected? How can a crowdsourced solution be integrated into corporate operations? What about the costs? These concerns are all reasonable, but excluding crowdsourcing from the corporate innovation tool kit means losing an opportunity. After a decade of study, we have identified when crowds tend to outperform internal organizations (or not). We outline four ways to tap into crowd-powered problem solving—contests, collaborative communities, complementors, and labor markets—and offer a system for picking the best one in a given situation. We emphasize that crowds are complementary to internal innovation efforts and present a new capability for firms that want to accelerate their innovation outcomes.

Keywords: Innovation and Management; Research and Development;

Format: Print

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Citation:

Boudreau, Kevin J., and Karim R. Lakhani. "Using the Crowd as an Innovation Partner." Harvard Business Review 91, no. 4 (April 2013): 61–69.

Working Paper | HBS Working Paper Series | 2019

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant performance gains over established algorithms. These include studying algorithms for antibody clustering, imputing gene expression data, and querying the Connectivity Map (CMap). Performance gains are evaluated quantitatively using realistic, albeit sanitized, data sets. The solutions produced through these competitions are then examined with respect to their utility and the prospects for implementation in the field. We present the decision process and competition design considerations that lead to these successful outcomes as a model for researchers who want to use competitions and non-domain crowds as collaborators to further their research.

Keywords: computational biology; bioinformatics; innovation competitions; Research; Mathematical Methods; Strategy;

Citation:

Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani. "Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions." Harvard Business School Working Paper, No. 19-097, March 2019. View Details

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In 2015, German football club Bayern Munich is considering how to enter the Chinese market. Should it build its own infrastructure or rely on third-party partnerships to reach this massive football fan base?

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Using the Crowd as an Innovation Partner

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