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Organizational decision-making and the returns to experimentation

Author

Listed:
  • Todd A. Hall

    (University of Kansas)

  • Sharique Hasan

    (Duke University)

Abstract

Many organizations have embraced formal experimentation, i.e., A/B testing, to improve the performance of their products and services. Experimentation, some have argued, should democratize innovation inside organizations by creating a platform to test new ideas, regardless of origin. In this article, we argue that experimentation’s promise hinges on having the proper organizational decision-making process that encourages innovation while mitigating the risk of unanticipated failures. We study this question by developing a model of experimentation inside organizations, where decisions to implement are either centralized or decentralized—a tension identified by practitioners and scholars alike. Organizations with centralized mechanisms that rely too much on the input of other teams benefit least from experimentation, as do ones with completely decentralized ones. In contrast, organizations with mostly decentralized decisions, with a single authority that sets consistent thresholds for implementation, achieve growth but with less downside risk. Thus, without considering the organizational decision-making structure, the benefits of experimentation may be limited.

Suggested Citation

  • Todd A. Hall & Sharique Hasan, 2022. "Organizational decision-making and the returns to experimentation," Journal of Organization Design, Springer;Organizational Design Community, vol. 11(4), pages 129-144, December.
    • Handle: RePEc:spr:jorgde:v:11:y:2022:i:4:d:10.1007_s41469-023-00135-z
    DOI: 10.1007/s41469-023-00135-z
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    as
    1. Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2021. "The Productivity J-Curve: How Intangibles Complement General Purpose Technologies," American Economic Journal: Macroeconomics, American Economic Association, vol. 13(1), pages 333-372, January.
    2. Nicholas Bloom & Luis Garicano & Raffaella Sadun & John Van Reenen, 2014. "The Distinct Effects of Information Technology and Communication Technology on Firm Organization," Management Science, INFORMS, vol. 60(12), pages 2859-2885, December.
    3. Jan W. Rivkin & Nicolaj Siggelkow, 2003. "Balancing Search and Stability: Interdependencies Among Elements of Organizational Design," Management Science, INFORMS, vol. 49(3), pages 290-311, March.
    4. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    5. Sah, Raaj Kumar & Stiglitz, Joseph E, 1986. "The Architecture of Economic Systems: Hierarchies and Polyarchies," American Economic Review, American Economic Association, vol. 76(4), pages 716-727, September.
    6. Felipe A. Csaszar, 2013. "An Efficient Frontier in Organization Design: Organizational Structure as a Determinant of Exploration and Exploitation," Organization Science, INFORMS, vol. 24(4), pages 1083-1101, August.
    7. Sendil K. Ethiraj & Daniel Levinthal, 2004. "Modularity and Innovation in Complex Systems," Management Science, INFORMS, vol. 50(2), pages 159-173, February.
    8. Daniel A. Levinthal, 2017. "Mendel in the C-Suite: Design and the Evolution of Strategies," Strategy Science, INFORMS, vol. 2(4), pages 282-287, December.
    9. Arnaldo Camuffo & Alessandro Cordova & Alfonso Gambardella & Chiara Spina, 2020. "A Scientific Approach to Entrepreneurial Decision Making: Evidence from a Randomized Control Trial," Management Science, INFORMS, vol. 66(2), pages 564-586, February.
    10. Eric von Hippel, 2006. "Democratizing Innovation," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262720477, April.
    11. O'Reilly, Charles A., III & Tushman, Michael L., 2013. "Organizational Ambidexterity: Past, Present and Future," Research Papers 2130, Stanford University, Graduate School of Business.
    12. Carliss Y. Baldwin & Kim B. Clark, 2000. "Design Rules, Volume 1: The Power of Modularity," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262024667, April.
    13. Diane E. Bailey & Paul M. Leonardi & Jan Chong, 2010. "Minding the Gaps: Understanding Technology Interdependence and Coordination in Knowledge Work," Organization Science, INFORMS, vol. 21(3), pages 713-730, June.
    14. Erik Brynjolfsson & Kristina McElheran, 2016. "The Rapid Adoption of Data-Driven Decision-Making," American Economic Review, American Economic Association, vol. 106(5), pages 133-139, May.
    15. Blakeley B. McShane & David Gal, 2016. "Blinding Us to the Obvious? The Effect of Statistical Training on the Evaluation of Evidence," Management Science, INFORMS, vol. 62(6), pages 1707-1718, June.
    16. Joshua S. Gans & Scott Stern & Jane Wu, 2019. "Foundations of entrepreneurial strategy," Strategic Management Journal, Wiley Blackwell, vol. 40(5), pages 736-756, May.
    17. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    18. Michael Christensen & Thorbjørn Knudsen, 2010. "Design of Decision-Making Organizations," Management Science, INFORMS, vol. 56(1), pages 71-89, January.
    19. Pankaj Ghemawat & Daniel Levinthal, 2008. "Choice Interactions and Business Strategy," Management Science, INFORMS, vol. 54(9), pages 1638-1651, September.
    20. Christina Fang & Jeho Lee & Melissa A. Schilling, 2010. "Balancing Exploration and Exploitation Through Structural Design: The Isolation of Subgroups and Organizational Learning," Organization Science, INFORMS, vol. 21(3), pages 625-642, June.
    21. Felipe A. Csaszar, 2012. "Organizational structure as a determinant of performance: Evidence from mutual funds," Strategic Management Journal, Wiley Blackwell, vol. 33(6), pages 611-632, June.
    22. Oliver Baumann & Nicolaj Siggelkow, 2013. "Dealing with Complexity: Integrated vs. Chunky Search Processes," Organization Science, INFORMS, vol. 24(1), pages 116-132, February.
    23. Daniel A. Levinthal, 1997. "Adaptation on Rugged Landscapes," Management Science, INFORMS, vol. 43(7), pages 934-950, July.
    24. Levinthal, Daniel & March, James G., 1981. "A model of adaptive organizational search," Journal of Economic Behavior & Organization, Elsevier, vol. 2(4), pages 307-333, December.
    25. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation," NBER Working Papers 24449, National Bureau of Economic Research, Inc.
    26. Ron Adner & Phanish Puranam & Feng Zhu, 2019. "What Is Different About Digital Strategy? From Quantitative to Qualitative Change," Strategy Science, INFORMS, vol. 4(4), pages 253-261, December.
    27. Eduardo M. Azevedo & Alex Deng & José Luis Montiel Olea & Justin Rao & E. Glen Weyl, 2020. "A/B Testing with Fat Tails," Journal of Political Economy, University of Chicago Press, vol. 128(12), pages 4614-4000.
    28. Iain M. Cockburn & Rebecca Henderson & Scott Stern, 2018. "The Impact of Artificial Intelligence on Innovation: An Exploratory Analysis," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 115-146, National Bureau of Economic Research, Inc.
    29. Nicolaj Siggelkow & Daniel A. Levinthal, 2003. "Temporarily Divide to Conquer: Centralized, Decentralized, and Reintegrated Organizational Approaches to Exploration and Adaptation," Organization Science, INFORMS, vol. 14(6), pages 650-669, December.
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