Ever since I started playing poker seriously in 2004, I have found an odd comfort in the world of incomplete information. If everyone’s hands were turned face up, and everyone played according to proper mathematical odds, all players at a table would break even long-run (minus the rake). A small edge would be gained, even if everyone’s hands were face up, by taking advantage of those who made poor mathematical decisions. But the major edges come from refined analysis when the cards are face down – mathematical errors are amplified & huge profits can be generated if your assessment of potential holdings is even 10% more accurate than your opponents expectation.
The same holds true for early stage venture capital. We are playing a game of incomplete information. We make some money at the margin by investing at better valuations than non-institutional investors, but that’s not the game changer. The differentiator is our analysis of the intangibles – a founding team, market dynamics and evolution, macro-trends that will affect M&A, consumer adoption, the stability of distribution channels, etc etc etc. The list is never ending.
There are firms that have tried to quantify the entire process algorithmically – Right Side Capital Management is one, although I think they still require a level of human touch. My issue with a quant approach to VC is that much like poker, the game can’t be solved by bots. The only form of poker which has been roughly solved is Limit Hold’em which offers only fixed betting amounts and where risk/reward can be measured. The dynamic betting games, No Limit Hold’em & Pot Limit Omaha have never been cracked by bots at high stakes levels with expert players. The dynamic nature of the betting provides a nearly infinite variety of outcomes and choice architecture. Given the level of qualitative analysis in early stage venture capital, it’s my opinion that the process can’t be solved algorithmically.
That said, the process does need to evolve formulaically. When I started my marketing career, us brand experts/marketers sat around a table and spat out creative ideas, which, because we were smart people, were evidently likely to work. We threw darts at a wall and ROI was typically undefinable. That model has flipped. Few marketers who aren’t data/analytics focused are still in business, and at a minimum, firms are expected to provide detailed analyses of impressions, best distribution channel, demographic feedback, etc.
As a budding VC, my challenge is this: how do I have any clue if I’m good at my job? Literally. The feedback loop in VC is 5, 7, maybe 10 years (if not more). The sample sizes are so small that an entire lifetime might be insufficient. My poker background cultivated a strong sense of people and personality – their competency, trustworthiness, vision – and I base a lot of my decisions on those instincts. These instincts are actually better defined as pattern recognition. Stuart (one of our partners) has bolstered my confidence by investing similarly. But even if my instincts/pattern recognition are correct (which I wouldn’t know for 10-5,000 years), there’s an entire debate on whether human capital is even the dominant investment attribute.
My plan for the near term is as follows –
- I am going to keep an investment journal of all companies that make it to our investment committee (the ones with the most diligence) with a breakdown of whether I would invest or not & why – keeping tabs every 6-12 months on progress.
- To start mapping my instincts versus ultimate diligence. Specifically, rating new leads on a 1-10 scale for attributes such as founder/market fit, distribution channels, market size, market willingness to adopt, and competition – seeing how those scores change as diligence evolves.
- To start quantifying my gut reactions – and tracking what % of positive reactions make it to later stages.
- Rely on Jim Shrager and Herbert Simon’s analyses of new venture strategy to efficiently hone in on the underlying value prop & sustainability of all businesses we see.