Thread by @dunkhippo33

Some Sunday thoughts on reading Thinking in Bets, by @AnnieDuke:

(Kindle book is < $3 for this month too: amazon.com/Annie-Duke-ebo…)

1) Terrific framework for decision making. Highly recommend adopting this...

2) Most ppl do something called "resulting". I.e. look at a result and extrapolate from the event.

Such as: "We won! Yay, I'm the greatest basketball player."

This is the wrong way to make decisions.

3) Why? Because life has a lot of luck.

There are many examples where teams lost and fans blame the coach for making a bad decision when statistically it was actually the best decision.

E.g. Pete Carroll's Seahawks (boo - go 49ers) lost to the Pats in the superbowl.

4) Bad poker players chuck up losses to "bad luck" and wins to "great skill". Great players like Phil Ivey don't look at results -- he'll remember decision points and evaluate them. And you can use tons of data from all past poker games to thinking through decision pts.

5) But we don't do this in our real lives.

Partly, because it's hard to record decision points and probabilities of activities. But also partly because we don't really want to. Most ppl just want to think they're right no matter what.

6) But for professionals, there's a real opportunity to improve. Just like how the best poker players evaluate all their decisions. And the best athletes watch a lot of tape.

Other professionals can do that too.

7) In VC, I often hear ppl say it's hard to know if you're right, because actual outcomes don't happen for 7-10 years.

That's true but there are intermediary outcomes that do happen along the way and opportunity to measure everything.

8) For example, 1 way we measure our own decision making @HustleFundVC is by scoring our portfolio companies on a variety of axes before and after deciding to invest.

We do this on a lot of different axes including: execution, domain exp, fundraising capabilities, etc

9) E.g. On team execution, this is our rubric:

4 = Takes initiative; runs with ideas with little guidance; constantly hits goals / milestones; high velocity
3 = Consistent velocity but requires more guidance
2 = Slowly executing likely because far from PM fit
1 = No execution

10) And we have many more categories that we do this for, scoring from 1-4.

Then we find out how right or wrong our perception was from reality.

By measuring, you can practice your decision making on micro levels rather than waiting for 1 outcome.

11) This metadata allows you to find other patterns that improve your decision making.

E.g. Elizabeth is always blindsided thinking teams are a 4 in category X, but post investment, it turns out to always be very wrong.

12) Hard work is certainly important in all professions.

But, building learning into decision making and being able to quantify that is really critical in getting better.

How do you get lots of reps? In VC, I got a lot of feedback loops in was when I worked at an accelerator.

13) You are regularly bringing MANY teams.

You assess a LOT of companies. Pick a bunch. Then they come into your office and work. And then you can watch them work day in and day out understand if you were right or wrong about your various hypotheses.

14) Having talked w/ a lot of accelerator managers over the years (since I used to be one), I don't think most are methodical in recording those hypotheses & measuring them. But, they have a strong opportunity to do so. So if you want to learn how to invest, this is a big opp!

15) Most ppl who want to break into VC don't think about accelerators, because working on or running an accelerator is hard work.

BUT, you get a lot of learnings from seeing a LOT of data and over time, these learnings compound.

16) tl;dr Tying this back to Annie Duke's book (new one coming out in Sept):

-be careful of "resulting"
-write down your decision points and test them later
-learn from data and constantly, retroactively re-evaluate decisions to improve decision making