Combining big data and lean startup methods for business model evolution

Abstract

The continued survival of firms depends on successful innovation. Yet, legacy firms are struggling to adapt their business models to successfully innovate in the face of greater competition from both local and global startups. The authors propose that firms should build on the lean startup methodology to help adapt their business models while at the same time leveraging the resource advantages that they have as legacy corporations. This paper provides an integrated process for corporate innovation learning through combining the lean startup methodology with big data. By themselves, the volume, variety and velocity of big data may trigger confirmation bias, communication problems and illusions of control. However, the lean startup methodology has the potential to alleviate these complications. Specifically, firms should evolve their business models through fast verification of managerial hypotheses, innovation accounting and the build-measure-learn-loop cycle. Such advice is especially valid for environments with high levels of technological and demand uncertainty.

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Fig. 1

Notes

  1. 1.

    We use product innovation in the broadest meaning of the term to also include service innovation.

  2. 2.

    We use the terms ‘legacy’, ‘incumbent’ and ‘established’ throughout the paper to denote the firm or company has been operating for over a decade (Henderson and Clark 1990), irrespective of its current size. As pointed out by an anonymous reviewer, our advice applies to both larger and smaller incumbents.

  3. 3.

    The one exception that we are aware of is an unpublished manuscript by Delvecchio et al. (2013) who compare the lean startup methodology with the stage-gate model.

  4. 4.

    Prior to the use of the lean startup methodology, startups traditionally developed a business plan for their product/service while making various assumptions about customers before they launched the product or service. However, more often than not these assumptions were found to be wrong when the startup had its first contact with customers, i.e. when it tried to sell its product/service. This then rendered the business plan redundant.

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Seggie, S.H., Soyer, E. & Pauwels, K.H. Combining big data and lean startup methods for business model evolution. AMS Rev 7, 154–169 (2017). https://doi.org/10.1007/s13162-017-0104-9

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Keywords

  • Business model
  • Innovation
  • Big data
  • Lean startup
  • Confirmation bias
  • Innovation accounting
  • Build-measure-learn-loop