Thread by @ryan_caldbeck

1/ Lots of ways to go with this question- which I love @dhaber. Here are my definitions:

Systematic- rules based decisions. Relies on data. Limits human discretion and bias.

Data driven- for sake of this TS, DD means using (lots of) data to drive a discretionary decision.

https://twitter.com/dhaber/status/1074416200313131008

2/ Then there is sourcing/evaluation/post close.

So framework is:
Systematic v. Data driven.

Applied to:
Sourcing/evaluation/post-close

3/ Systematic sourcing:
Maybe Correlation Ventures? But most of data comes when co’s give them the data.

DD sourcing:
PeakSpan and Signal Fire

4/ Systematic evaluation:
Correlation.

DD evaluation:
PeakSpan, Signal Fire. Social Capital’s CaaS product said they used data.

5/ Systematic post-close:
None.

DD post-close
Signal Fire? Maybe others I don’t know about.

6/ Caveats. A TON of VCs and growth PE now are getting in house data scientists. All I hear from them and their portfolio co’s is that the data scientists aren’t really sure what to do.

7/ Why? Bad data, no structured PM resources, no data engineers helping to ingest and pull together large amounts of data on private companies.

8/ Heard last week that the 4 data scientists currently working inhouse for a top 3 VC firm are basically just doing projects for their portfolio companies. Cant find a way to add value in sourcing/evaluation because there isn’t enough data.

9/ That’s all I can think of. I’m sure there are others I’m missing- and would love to hear about them.

10/ [Editor’s note: I’m excluding CircleUp from all of this to not be self-promotional.]