Data Driven Venture Capital (DDVC): The Impact of Data-Driven Investment Strategy on VC Firms’ Success

In the venture capital (VC) industry, a new breed of VC firms has emerged to embrace data-driven investment strategy instead of relying on human judgments. Although data-driven methods has already demonstrated advantages over humans in some domains, it is unclear whether this strategy can lead to superior performance in the venture capital industry. This research fills this gap by estimating the causal impact of a VC firm’s adoption of data-driven investment strategy on its success using matched portfolios of startups from data-driven and non-data-driven VC firms. We find that adoption of data-driven strategy tends to increase the success of a VC firm in terms of successful exits (e.g. IPO and acquisition) of startups it invests in. In addition, we also find that data-driven investment strategy can reduce racial bias but increase gender and local bias. The increase of gender bias is responsible for the superior performance of data-driven investment strategy while the reduction of racial bias and the increase of local bias is not.