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The power of prediction: predictive analytics, workplace complements, and business performance

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Listed:
  • Erik Brynjolfsson

    (Stanford University and NBER)

  • Wang Jin

    (MIT Sloan School of Management)

  • Kristina McElheran

    (University of Toronto)

Abstract

Anecdotes abound suggesting that the use of predictive analytics boosts firm performance. However, large-scale representative data on this phenomenon have been lacking. Working with the Census Bureau, we surveyed over 30,000 American manufacturing establishments on their use of predictive analytics and detailed workplace characteristics. We find that productivity is significantly higher among plants that use predictive analytics—up to $918,000 higher sales compared to similar competitors. Furthermore, both instrumental variables estimates and the timing of gains suggest a causal relationship. However, we find that the productivity pay-off only occurs when predictive analytics are combined with at least one of three workplace complements: significant accumulation of IT capital, educated workers, or workplaces designed for high flow-efficiency production. Our findings support claims that predictive analytics can substantially boost performance, while also explaining why some firms see no benefits at all.

Suggested Citation

  • Erik Brynjolfsson & Wang Jin & Kristina McElheran, 2021. "The power of prediction: predictive analytics, workplace complements, and business performance," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 56(4), pages 217-239, October.
  • Handle: RePEc:pal:buseco:v:56:y:2021:i:4:d:10.1057_s11369-021-00224-5
    DOI: 10.1057/s11369-021-00224-5
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    Cited by:

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    2. Barth, Erling & Davis, James C. & Freeman, Richard B. & McElheran, Kristina, 2023. "Twisting the demand curve: Digitalization and the older workforce," Journal of Econometrics, Elsevier, vol. 233(2), pages 443-467.
    3. Erik Brynjolfsson & Catherine Buffington & Nathan Goldschlag & J. Frank Li & Javier Miranda & Robert Seamans, 2023. "The Characteristics and Geographic Distribution of Robot Hubs in U.S. Manufacturing Establishments," Working Papers 23-14, Center for Economic Studies, U.S. Census Bureau.
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    6. Michael A. Levin & John T. Gironda, 2023. "New frontiers in forecasting, predicting, and explaining: an introduction to the special issue," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(4), pages 559-560, December.
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