There's a few VC firms (Correlation Ventures leaps to mind, as noted in the article) that invest solely on the basis of a quantitative model that looks at the various features of the business (market, founders, etc.) and then doing some kind of neural network/similarity scoring analysis on it. Of course, a big feature that I presume their models have which this paper does not is the understanding that an IPO is worth tens of small wins, if not more.
The real optimal setup here would be to pair that kind of mathematical rigor with the dealflow of an a16z or KP. I would suspect that both of those two would say that a similar model exists in the heads of their partners so far as pattern recognition, but..
I just spoke to Correlation Ventures this week. Great model, and a refreshing change for fundraising. They came in cold after hearing about us from another VC, then we had one phone call which was mostly a friendly chat, and then 3 emails with pretty simple docs and clarifications. They got back to me with a decision in 2 days. After that, they just want a short conversation with a VC co-investor, and another short call with me. Super simple.
I agree that correlation has a great model that makes them easy to work with as a vc or entrepreneur. That said, they cannot exist without other traditional firms leading investments (just as in the public markets, an index fund cannot exist without active fund managers doing the work they have always done).
If this were true, 'most VCs' would be bankrupt, and many probably are.
However, nobody should care about 'most VCs'. You only need one. The good ones do not miss the big deals. There may be evidence that they take a long time on the big deals, but miss them? What evidence do you have?
They absolutely miss many big deals. Think of it this way, there are several dozen well-known Series A firms like Sequoia, Kleiner Perkins, Google Ventures, etc. But for any single company like Airbnb or Uber, only one or two or maybe three of those dozens of firms gets to invest. That means for any given unicorn, 90% of the good firms missed it, and probably 99% of all legitimate Series A firms. Sometimes that's because rounds are competitive and a company might have 5 term sheets but can only take one, but that is the exception and not the rule.
VC is an interesting business model because you don't have to get all of the good investments, you just need one or two per fund.
The real optimal setup here would be to pair that kind of mathematical rigor with the dealflow of an a16z or KP. I would suspect that both of those two would say that a similar model exists in the heads of their partners so far as pattern recognition, but..