Finding Decisive Data
The Rise of Thesis/ Research-Driven VC
Over the last few years, I’ve noticed a rise of targeted research and thesis-driven vc firms as a form of differentiation among the overflow in LP capital to the ecosystem. Some of these funds publicly post their market research and investment hypotheses, kind of similar to ARK, Morgan Stanley, or Bloomberg. I think it is tough to translate this investment format to early stage because there’s an incomprehensible amount of unknown variables from seed to IPO. Early stage market analysis can check out and lead a firm to profiling the type of startup they are looking to invest in, but even the most detailed analysis can only crack the surface of the variables along the startup journey. This is true even when limiting these variables to how the market will unfold over the next decade (not including intangible variables like team, vision, etc.).
This has led me to believe that research-driven early stage firms should focus on finding decisive data points. These would be key figures that are so suggestive that a combination of other future variables are unlikely to direct the outcome in another direction. The issue with this is that it seems extremely unlikely to find decisive data points that have been overlooked by other firms at large. Other conventional terminology for these might be leading indicators, signals, or insights.
Some past examples of decisive data points:
Late 2000’s: Smartphone adoption rates
2010’s: Cloud computing cost decline
Mid 2010’s: API usage growth
2013: BTC market cap surpassing $1B
2020-2021: Remote workforce tools usage growth
2010-2025: Growth in opensource developer activity (GitHub repos/star counts, Stack Overflow quarterly usage)
In-depth analysis could find more specific data points within each of these categories that could point to startup verticals.
All of this is to say, I’m not really sure what the answer is to find undiscovered signals; these are just some thoughts on the contradictory nature of some current approaches.