TIP623: The Art Of Decision Making w/ Annie Duke

Annie Duke: I said, What do you mean the feedback loops are long? And they said, What do you mean? We don't know if it excerpts for... And I said, I'm sorry, do you invest in the company and then you go to sleep like Rip Van Winkle and 10 years later you wake up and you find out what happened? When you invest in a company, a couple of things are true. Two different categories of things are true. Both of which allow you to close the feedback loop more quickly. Thing number one is that you actually know objective things about the company. You know whether ARR is growing. You know whether they're hiring top talent and retaining the top talent. You know whether they fund a series A. You know whether it's an up round, a flat round, a down round. You know what the quality of the syndicate is, same thing for B, same thing for C. If you're, depending on the speed of the market, if you invest at seed, for example, you're going to know something very significant about that company between six and 16 months later. That sounds like a lot faster than 10 years, the first thing that you know. The second thing, and this is true across all investing, is that you're investing in the company because you're making a particular bet, and the bet is your thesis. If it's in the market, you're saying, I think that I know something that the market doesn't know. Why do I know that that's what your thesis is? Because otherwise you would be indexing the market. You're not indexing the market. So you're saying, I believe that the market has this mispriced temporarily. I believe the market is efficient, but not every single moment. It's overall efficient. So I believe that at this moment, when it comes to this stock or whatever, this stock or this option, the market does not have this price efficiently. So you have a thesis about why that is true. It's true when you're investing in a company. I believe that this market is going to be a great market to be in. This product is going to have a competitive advantage. They're going to execute in this particular way, so on, so forth. And those kinds of things, you can find out very quickly, even when you're investing in a seed stage company. You can see like, are they executing in the way that I thought they were? Is their product gaining traction? Like, so on, so forth, right? So all of these things like, look, is it like poker or jujitsu where you're going to find out two seconds later? No, but you're going to find out way more than 10 years.

Annie Duke: But how do we deal with that in a situation where your portfolio might have seven positions at a time, for example, or in venture where maybe you have 20 companies or 25 companies in a fund, right? And you're generating more outcomes than the final outcome. So it goes back to what I'm saying. So let's imagine this. Let's imagine that you're an investor investing in Series A. That's your specialty. And for every single company, every company that comes into partner meeting, You have to make a forecast of the probability that company will fund at series B. Now, you can put restrictions around it, right? Like you can say the probability that it will fund at series B with an up round. So you can do whatever you want. So we can think about what are those things that are really necessary for this to survive? Because the thing is, I can guarantee you, won't ever have a fund returner if you invest at series A that doesn't invest at series B, likely not a down round, which is a bad sign. Let's take that one data point, right? But then you can actually think about what are all the data points that I now want to be making predictions about where I'm going to start to know those things more quickly. Now, what's nice about that is it does double duty. What is it massively increases the outcomes that you have so that you can get more into the thousand coin flip situation? Because let's imagine that you have 100 companies come into partner meeting in a year And you've made that, we're just talking about the one forecast right now, you've made that one forecast for all 100 companies in the space of 18 months, you're going to know for every single one of those companies, because it's public whether they do a B, how good of a predictor am I of this particular thing that really, really matters. So now you start to be able to close these feedback loops faster because you're generating so much more data that we start to remove the luck and it becomes about sort of your predictive power.