Data-driven VC #22: Why data-driven approaches are like an e-bike
Where venture capital and data intersect. Every week.
👋 Hi, I’m Andre and welcome to my weekly newsletter, Data-driven VC. Every Thursday I cover hands-on insights into data-driven innovation in venture capital and connect the dots between the latest research, reviews of novel tools and datasets, deep dives into various VC tech stacks, interviews with experts and the implications for all stakeholders. Follow along to understand how data-driven approaches change the game, why it matters, and what it means for you.
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Disclaimer: This piece is strongly hypothesis-driven and I’d love to get challenged by you!
First and foremost, VC is a financial asset class with the primary goal of consistently superior returns. While some VC firms seem like they’ve always been this shiny and leading institution, it took decades of hard work for them to get the flywheel spinning. Let’s take a look at the individual steps to success and what the implications of data-driven approaches in this context may be.
The VC Flywheel, a simplified model of VC success
A new VC firm typically gets started by one or a few people with some kind of relevant experience, in most cases either entrepreneurial or investment track record. To start off, they put their own money into the fund and raise the majority of the remainder from external LPs. In parallel to their initial fundraise, they ramp up their “deal flow”, get in front of founders and try to get a first close done to finally start investing. This is where the “access” component comes into play.
Why should the best founders let you join their cap table? Typically it’s a mix of attractive terms (which are determined by a mix of your fund size, initial versus follow-on allocation, diversification strategy and target shareholding), firm brand and personal brand (which in the beginning are very much the same as mainly driven by the individual track records), expertise and personal fit. Many young firms struggle on the brand component as founders oftentimes opt for strong signaling of the VCs.
Once invested, “portfolio value creation” becomes key. Depending on the fund model (hands-on versus hands-off), this might include strategic advice, hiring support, customer introductions and support with follow-on funding rounds. Sooner or later, there will hopefully be an exit. As we all know, VC returns are distributed based on a Power-law and therefore, every VC desperately seeks one or more outliers in her portfolio. Big exits not only deliver great returns but also drive the external brand perception of the firm and the individual investor (see my previous post on personal branding here).
Unfortunately, VC feedback cycles are very long and after an initial investment phase of 3 to 4 years, the raise of the second fund is typically due before the first exits of the first fund return capital. Said differently, the wheel needs a second push before the first cycle has finished. This is common. While the second fund can oftentimes be raised based on the same ingredients as the first one, the third fund requires the VCs to present first exits and capital distributions (=DPI). This is where many rising fund managers struggle. The third fund is the most difficult one and separates the wheat from the chaff.
