Finding the Next Unicorn: When Big Data Meets Venture Capital
- Johannes Weibl, University of Munich (LMU), Institute for Information Systems, Munich, Germany
- Thomas Hess, University of Munich (LMU), Institute for Information Systems, Munich, Germany
AbstractVenture capital (VC) has been growing rapidly in recent years. So far the screening and evaluation of potential startups as investment objects largely depends on the venture capitalist’s personal experience, network and qualitative evaluations. In the era of big data, the advent of new data sources and analytic techniques enables a data-driven investment process. Grounded in systems theory and the theory of complementarity, this study reports the findings from an exploratory study of 13 VC firms that synthesize and use novel data sources. Our analysis shows that the data-driven approach, in particular, impacts the deal origination and screening stages of investment. It leads to informational and transactional benefits, which lower operational costs in the short term and enlarge the potential return on investment of a VC firm in the long term. We contribute to the literature by shedding light on how various data sources complementarily lead to additional business value.
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