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1/ Thanks @AaronSuplizio, @jmj and @JohnZettler. Just to clarify- while people often talk about VC as being tech only, I want to clarify I think of it as a stage - not an industry. VC can include tech, health care, CPG/retail, etc.
2/ Also- there are a TON of VC firms, almost all focused on tech, that say they are investing into data resources to inform sourcing, execution or post close. Let’s differentiate between data driven discretionary process and automating investing
3/ I think the tech VC firms that say they are building data resources are largely just doing it for marketing reasons. Well at least that’s what many of them, their entrepreneurs and LPs tell me. If we only focus on the “Sourcing” problem, even that is a massive one for tech vc.
4/ First there isn’t a lot of Feature Data (to understand performance from afar). [Please don’t point to credit card or LinkedIn data as if that’s differentiated.] Then there isn’t a lot of Training Data (i.e. there was no example of Uber hitting before Uber hit).
5/ In CPG the dynamics are very different. Ton of feature data (distribution, product, brand, etc info) and lots of training data (so many successful and *very similar business models*). That’s the pt @AaronSuplizio is making.
6/ To be clear, today our current investment vehicles have human discretion. That includes a $125m discretionary VC fund that leverages Helio but still has human involvement....

7/ ....And a $200m credit fund that is also discretionary. Both are data informed but not systematic (or as @Jmj put it “automating” the investment decision).
8/ We do have a vision for a systematic VC fund. But that will still have humans making calls, closing deals. Just not using human discretion to find/evaluate companies.

9/ Also- VC isn’t the first industry to look like it was full of human discretionary that couldn’t be systematized….until it was.
10/ Here is how I think a systematic VC could work:

11/ I think doing it within an existing private investing firm is close to impossible. Culture, incentives, ego, balance sheet, etc.
12/ Culture: Private investors (PE & VC) think they are the smartest people in the world. As the head of one $20B fund recently said “yeah I think my work can be automated, but I’m going to be the last one to admit it.”
13/ Incentives: Think about the massive tech investments it takes that cant be expensed to LPs because they aren’t deal related initially. Its asking the partners to invest millions (tens of Ms?) of their own money years in advance of showing if it could lead to a systematic fund
14/ Btw- the funds that can afford to do this? likely managing billions. Which means initially the systematic efforst will be lower gross margin and gross profit.

Sounds like it could fit into Clay’s theory of disruption…..
15/ To be clear, I don’t think textbook definition of “automation” is possible. But Two Sigma also isn’t literally automated - still humans that are involved in the process. They’ve just systematically tried to eliminate human discretion. That is possible in privates as well.
16/ The prize? A scalable, repeatable investing process in the private markets that isn’t dependent upon Key Person risk.

Also- should help democratize the investing process which should spur innovation for all.
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