Afford Anything - Upgrade Your Thinking, with Super Thinking authors Gabriel Weinberg and Lauren McCann

Episode Date: July 15, 2019

#204: You make decisions on a daily basis about your career, family, friendships, health and investments; these choices shape your life. But how much have you thought about how to think? There are common threads and collective wisdom across disciplines. These common threads create mental models, which are frameworks for understanding the world. Mental models allow us to apply insights from a variety of unrelated fields, using reasoning by analogy to make better choices about our lives. For example: Critical mass is a concept from physics that can be applied to our understanding of microeconomics or entrepreneurship. The availability heuristic and filter bubble are concepts that we can use to check in with ourselves whenever we’re assessing risk in our businesses, careers or personal safety. Loss aversion and information aversion are notions that, when articulated, allow us to understand why we hesitate to learn more about investing during recessions. Mental models can make us better thinkers. Warren Buffett’s business partner, Charlie Munger, says he relies on mental models to evaluate businesses and make investing choices. What we know is that we’ll never be right. But mental models can help us become less wrong. On today’s episode, Gabriel Weinberg and Lauren McCann join us to discuss Super Thinking, their book about how to use mental models to improve the skill of thinking. Enjoy! For more information, visit the show notes at https://affordanything.com/episode204  Learn more about your ad choices. Visit podcastchoices.com/adchoices

You can afford anything, but not everything. Every choice you make is a trade-off against something else, and that doesn't just apply to your money. It applies to your time, your focus, your energy, your attention, anything in your life that's a scarce or limited resource. And that leads to two questions. Number one, what is most important to you? Not what does society say ought to be, but what actually matters in your own life? Number two, how do you align your day-to-day decisions accordingly? Answering these two questions is a lifetime practice, and that is what this podcast is here,

to explore. My name is Paula Pant. I'm the host of the Afford Anything podcast. And as I have frequently said, thinking about how to think and learning how to be better at the decision-making process is one of the most important, if not the most important life skill that you can master. I would say that learning how to be a better thinker coupled with emotional mastery, if you can get those two things nailed, wow, that's the foundation for living a good life. And so today, Gabriel Wynie, and Lauren McCann join us on the show to discuss how to become a better thinker and how to be more skilled at the practice of making decisions. They are a husband and wife team who recently co-authored a book called Super Thinking, which is a book that describes how to apply models from a variety of disciplines onto questions, problems, issues that exist in other fields. Essentially, it's a book about how to borrow concepts across a variety of industries and disciplines

so that you can apply different conceptual frameworks to problem solving in any area of your life. Warren Buffett's business partner, Charlie Munger, uses mental models in order to make better investing decisions. And the study of mental models, which is essentially the study of frameworks or concepts, is often used by people who want to improve the same. skill set of thinking. So here are Gabriel and Lauren discussing super thinking. Hi, Gabriel and Lauren. Hi. Thanks for having us. Thank you for joining me. So you wrote a book about mental models. Now, can you talk about what is a mental model and why does it matter? Sure. Mental model is kind of a fancy word for concept and there's concepts everywhere. Whatever area of study that

you kind of did in school, you learned probably tons of concepts. So I was a physics, major and learn all sorts of physics concepts that aren't relevant to much of anyone or even myself nowadays. But there are a couple that really are because they're just useful as metaphors to help you make general decisions, investing decisions or personal decisions. An example is critical mass from physics. So that's a nuclear energy concept about making chain reactions. But as a metaphor, it's really useful to understand businesses because businesses can have critical mass or political movements can have critical mass if they have enough people behind them. And so once you understand that a situation maybe applies, that concept applies to that situation, you can automatically kind of think more

strategically about it and say things like, well, how could I maybe reach critical mass faster? Now, Charlie Munger, the famous investor, he really opened up my eyes to mental models about 20 years ago when he's talking about his own success in investing and talked about how mental models are behind it and 80 to 90 models, if he knew them and he applies them regularly, makes him a worldly wide person. But he never really systematically listed out those models. And so I've been spending that time and then ultimately wrote this book to try to really comprehensively list out these special concepts. So would it be accurate to say that mental models are a practice of taking principles

across a range of disciplines, taking interdisciplinary principles and applying them to new modalities or new ways of thinking? Yeah, I think so. Maslow's Hammer is a good example. You want to talk about that? So Maslow's Hammer is the concept that if all you have a hammer, everything looks like a nail. And the idea there is that if you only have one way of solving problems, you're going to try to solve every problem with that method. But that may not be the best way to approach the problem. And so the idea is that you need to have more tools in your toolbox than just a hammer. And the tools may come from economics. They may come from science. They may come from business. But you want to have all those tools in your toolbox. What do you do in the event that

you could apply multiple mental models or concepts to a problem and they would lead you in different directions? This is a good point. I mean, these are shortcuts for thinking, but they're not always the answer. By way of example, there is a model called Occam's Razor, which is one of maybe more people are familiar with about the simplest answer being usually the true one and one that you should investigate first. But sometimes it's not. I mean, sometimes it's wrong. And so it's actually kind of nice when you have multiple things that might conflict because it forces you to think critically a bit more about which is correct and which is not. And the meta whole point of this entire thing is to not trust just your intuition and slow down and be more methodical in your

thinking and then apply these concepts. And if you're doing that slow thinking, then you can really think through whether something applies or not. Yeah, I mean, it's, it's almost better to be able to think through a number of different models and figure out which one works the best and which one's the most appropriate rather than always only having one way of viewing things. How can you obtain feedback that allows you to improve at the practice of thinking? I definitely think that this requires practice. We like to think of it. It's called super thinking because we think it gives you superpowers,

but just knowing the concepts are like that first spider bite or radiation dose. It doesn't help you really hone your powers or use them. And to do that, you really have to practice. And because of the same traps of intuition, I don't think you can do it alone. I think you actually need support. Now, we talk every day. And so we kind of are each other's foil for a lot of these things.

But I really think you need somebody. It doesn't have to be the same person for every type, but you need somebody questioning your own assumptions all the time. So the two of you talk every day. How do you protect against group think? That's an interesting point. One of the things that we recommend in the book is also spending a lot of time alone. and not always thinking of things together.

So you have to spend some time, you know, thinking about an issue on your own and then coming back together and saying, oh, you know, these were my thoughts. The example is writing the book. We kind of wrote a lot of things in parallel and Gabriel might like a way things were flowing, but then I would take a look at it separately

and say, you know, I don't really think that works the way you think it works. And if we had tried to do the whole thing together simultaneously, we might get wedded to an idea that just wasn't really the best one. It's a good question, though, and kind of two jumping off thoughts of that is, you know, the more diversity of thought you have injecting into a process, the less you're going to get group think. And so, you know, we engaged some external editors that had never even been familiar with these concepts, as example for the book. But at work, there's a lot of research that shows,

like, people do brainstorming just wrong. And so this idea. of getting everyone in the room and just everyone brainstorming together is generally a lot worse than setting people up with the problem and then letting them go individually, think on their own, and then come back as a group and sort through those ideas. And so for that kind of process, we try to like, at least a duct that go, the company that I run, we try to institutionalize that as like, that's how we're going to do brainstorming here. One example that's also given is that you should try to have a devil's advocate out there. And that's, concept that actually comes from the Catholic Church in deciding whether someone should be given

sainthood or not, and they always want to have someone arguing against it. And so any idea that you maybe have, you want someone to try to argue against why that's the best idea. And it's actually most effective if they really believe it. And they're not just pretending that they're against it, but it really gets you to think how to support your ideas and whether you're actually right. On the topic of supporting ideas and making decisions. Let's talk about some of the mental models around decision making. One of the points that you make in your book is that the simple pro-con list has shortcomings. Why? Yeah. It's kind of like the Mezzles Hammer thing. Everyone kind of goes there first because it's

easy. But some of the problems with it are when you write down pros and cons, you know, you're not writing down the weight of how much they matter. So you could have people kind of look at the list and they're like one side's bigger. But a lot of those things on the bigger side may be small. and inconsequential. Another issue with it is they could be interrelated things. And then a third issue with it is oftentimes people have a predetermined idea of what decision they want to make, and they kind of bias themselves. Often they want to make the decision. And so they're not really writing down or aware of all the cons on the list. What's a better alternative? So there's a lot of different decision-making models that you can use for different situations. One really easy tweak

on the pro-con list that solves a lot of those problems, is to try to put some numbers to your list and put some, first of all, group the interrelated things, but also rate each item even as simple as a one to 10, how important it is to you. And then you can start to get, you know, some actual numbers. And why that's important is, A, you can tell whether the pros way against the cons.

But another concept, which is a major problem, the pro-con list is something called opportunity costs, where when you're faced with the decision, you may be thinking about that decision alone, but you're not thinking about all the other decisions you could make. So, for example, say, like, you got a job opportunity, and you're trying to weigh that job opportunity, the pros and cons. But maybe what you should do,

if you really think of switching jobs, is take a step back and think about all the other jobs I could get. And then they each have their own pro-con lists. And if you wait them all, then you can kind of compare all the options more mathematically and say, wow, this other opportunity that I hadn't thought of before, now that I've laid them all the options and scored them has a much better score. Now, there's still problems with scores and whatnot, but you can start to get much better

questions to yourself as to which is actually the better opportunity. So if you were to numerically score the importance of each data point on the list, you could then come up with a final tally, with a net at the end. That's right. And if you want to get even more sophisticated with it, the more, the bigger decision it is, say it is, you know, buying a house type of thing or doing an investment, you can upgrade it to full cost benefit analysis where you're really turning that into a spreadsheet and making the benefits and costs accrue over time. And the reason why you want to upgrade to that is because

I'm sure many people on this podcast know, you know, there are things like inflation, there are things like risk that the benefits and costs may not happen. And so when you start to put that into the spreadsheet, you can account for those things in a numeric. fashion. So how would you do that? I mean, in practice, let's say that you were trying to decide whether to accept a job or even something that's maybe a little less numerically oriented, like whether to continue to live in Las Vegas or to move to a different city. How would you input that into a spreadsheet? It's funny because we did that same process to basically choose where we live now. And what you're effectively doing, and I think people react to some

this and they're like, well, there's subjectivity in it. But there's more subjectivity in your original list by putting no numbers to it. I think the goal is also deciding what factors are important. And for us, you know, you might think about traffic. You might think about what the schools are going to be like. You might think about whether you can actually afford to live there. I mean, that was a big, that was a big factor for us, you know, how close you're going to be to your family. There's so many different factors. And you really need to try to comprehensively. list things out. And I think that's where the group thing coming back to that is talking to other people who've made similar decisions and they can help you come up with

things that you maybe haven't even even thought of. So how to operation I was at, though, what we effectively did was rainstorm all those factors, including by talking to people. And then you're effectively making kind of like, you know, everyone's familiar with like the US News and World's report college rankings. You know, you're effectively making a weighted average decision for yourself. And so you're coming up with all the factors for that decision that you're making, say it's whether to move, and then you're weighting each factor with how much it's important to you. And then you can apply all those factors, rate them, and then see what comes out. Now, there's one, there's kind of another model that immediately comes to play here, which is called

sensitivity analysis, which is the idea that your ratings are a bit subjective. Like we're basically trying to say location may be more important to you than Sauri in some cases, but is it twice as important or three times important? And you can actually test that in your model by changing the two to the three and seeing whether the decision would actually change and understanding how sensitive it is to the inputs. And by running a sensitivity analysis, that's in essence a way of testing your assumptions. If a particular input is highly sensitive, then your assumption about that must be correct in order for the data to be good. That's exactly right. Or else you get you succumb to another kind of model fallacy called garbage and garbage out, where if your

assumptions are too inaccurate for something that really moves the model, then the whole model is kind of garbage. And so it really helps you tell which are most important. And then you can go out, you may need to go out to get more data to understand how important that is or get better numbers for it. You also talk about a decision tree. Can you explain how a person might use that in order to make better decisions about various questions in their life, like taking a job or quitting their current job or moving to a new location? The idea here is that you may have a decision you're making, but there is some level of uncertainty involved in what the outcomes are going to be. You might say, I'm going to switch to this new company because there's going to be more

opportunities for advancement there. And I might be able to get to salary. X in fewer years, but you should really try to attribute, you know, some type of probability to what actually is the likelihood that that's going to be the outcome. And so you want to try to make a list systematically of here's the different options and here's the different possible outcomes and then trying to attribute some probabilities to the different outcomes to see like what the expected value or expected return is on each decision. Yeah, the reason to use the decision tree is helps you structure this kind of probability so you can actually at the end, similar to the pro-conless tally, get to a final result

and say the expected value of taking this job is more than that job. Whenever you're doing an expected value calculation, though, there's always risk of ruin. And so how do you, how should you guard against black swan events, those low probability but high magnitude events that could completely, completely wipe you out and render your decision terrible in hindsight. Yeah, it's exactly right. I mean, what we advocate is to actually move from dollar values to utility values. And those kind of chance of ruin things are so negative.

So negative in utility that you need to up the value of that part of the decision tree super high, not infinite, but more realistically high than the actual amount because it's going to ruin you or ruin that investment. And if you do that, the decision can tree can actually help you account for that, which is why it is a good model. You're multiplying a very low number of probability by a very high number this chance of ruin, and it can make you make sense of the outcome. Pulling back a bit, one question I've heard from several people in my audience is, what is a prudent level of thinking about a Black Swan event? I mean, there's a certain point at which it's good to guard against those.

And yet there's another point at which you tip the balance and now you're simply being overly cautious. How do you know where that tipping point is? I think it somewhat depends on what situation you're in, right? So if it's really ruined for your entire life, like it's going to cause you death or, you know, actually go absolutely bankrupt, that's kind of irreversible decision that, you know, at least me personally, would want to take a lot of time to account for. But if you're talking about somewhat diversified portfolio,

either of your life or your investments, where there still has a chance of ruin, but it's limited to one part or size of your portfolio that you've already decided you're willing to take risk on, I liken that we do angel investing. And, you know, there are so many black swans in angel investing. And a lot of investments go to zero. But that portion of the portfolio is designed.

that a lot of them are going to go to zero. It's quarantined in a way that there's only a minimal amount of loss. I think one of the hardest thing for people to do is to actually assess risk. It's really difficult, but, you know, people can get afraid possibly irrationally so of certain risks, but it's important to possibly quantify some known risks in your life that you're taking every day, like driving a car or, you know, getting on a plane and all. these decisions that you make and in trying to see how drastically different is this decision from something that I do every day, the types of risks that I take every day. I'm glad that you brought up known risks because one of my next questions was going to be, how do you, while you're going

through the process of making a decision, how do you account for the fact that there are unknown unknowns? Yeah, well, your first step is actually recognizing that they exist, to your point, and understand that they do and that there are things that are going to come up that you don't know. But one of the things Lauren said earlier, I think, is almost the best tactical thing to do, which is go talk to people who have been through or faced similar things already. Because a lot of things that are unknown unknowns to you are not unknown unknowns to everybody else in the world. And I can't tell you how many conversations I've had with other entrepreneurs who have been through

different things before I did. They really helped me understand where there were risks that. I didn't realize existed. Other than speaking to people who've been through the same situation, are there any other practices that a person can undertake in order to learn more about a decision that they're trying to make? Yeah, there's a whole other decision model called scenario analysis, which is really about that, effectively, uncovering unknown unknowns and really black swan events. And it really is trying to force you to think about alternative, effectively futures and how that might affect you.

And there are different approaches to that. It comes out to like the brainstorming kind of stuff we were talking earlier. But there's a whole body of research around how to do this well. It actually originated in the Shell Company. And they were thinking about, for example, climate change, you know, back in the 50s. And one of the things that you do is you think about. all sorts of world events maybe that have happened in the past. And if something similar happened again, you know, how would it affect you or the thing that you're thinking about? And you kind of go far into

the future and work backwards. But it really is a pretty good model for helping you uncover unknown unknowns. One of the things that we talk about in the book as well is called the Uda Loop. And that stands for observe, orient, decide, and act. And so the idea is that you're never going to be fully prepared for everything that's coming at you. But you have to be able to find a way to react to each situation. And people who are good at kind of reacting to spontaneous things that happen to them in a positive way, even if it's something very negative, are going to be the ones that are going to be, you know, have the most robust thinking and be able to handle the worst-case scenarios. So that points to preserving flexibility. Is that what I'm hearing? Like,

flexibility is security in that regard? In general, I think part of the idea here is that the world is complex and uncertain and you're just going to be faced with things that you... Yeah, no one can plan out their whole life exactly how it's going to go. And so you have to be ready for the unexpected. And being flexible, it's one of the examples that, you know, people often think of, survival of the fittest being that you were, you were born the fittest, but it's actually the animals that are the most adaptable are the ones that survive. How do you put yourself in a situation in which you preserve your own flexibility, particularly when you don't know what the future holds, as none of us do?

That's partly why this meta-conceptive mental models is so powerful is that they're general problem-solving techniques. and you have this huge toolbox of things to draw on when you're hit with unexpected things. Another, though, like we said, is just to slow down. Even if you have to go fast, you're using this oot loop where you're, there are steps where you're actually orienting yourself and making a decision point rather than just, you know, instantly acting. Skipping from observing now.

Yeah, just observing and acting and not orienting or deciding. And I think people get caught up in that, especially when they're hit with uncertain situations because there's just an emotional inherent desire to get closure and to get stressful situations off your plate or just to be done with hard things. But you can really easily make suboptimal decisions that way. So the practice of thinking is an important practice. Yeah. I mean, I think it's a skill like any other.

I mean, maybe that's the way to look at it. you can practice apply mental models. You can practice thinking. You can practice analytical thinking. And you can go up the skill ladder on that by practice. And then when you're faced with something really consequential, you're going to be much better at it. We'll come back to this episode after this word from our sponsors. Are you tired of getting nickel and dime to buy your bank?

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These are the shoes you've been waiting for. Head to rothies. dot com slash paula today that's rothies.com slash paula. One thing that you caution against in your book is anchoring the practice of latching on to the first idea that comes into your mind. Can you describe why and how that happens and what we can do to protect ourselves against it? Yeah. It's one of these natural biases.

And so a canonical example is when you see like an infomercial online or something and they say the value of this is $1,000. And then they're like, but we're going to cross that price off and sell to you for $10. And you're like, wow, I'm going to use discount. But the $1,000 was, you know, probably some questionable assumptions went into that calculation. And so it's really hard to overcome this because you're emotionally really drawn to it. And so the way to really do it and kind of slow down is do this what you call first principles, thinking where you try to go from the opposite direction from the bottom up. So in that example,

you could say, well, how much is this really worth? How much should it cost to make? How much is worth to me? How much do I really want this thing? And thinking from first principles can help you break out of a lot of these biases like anchoring or other ones. Elon Musk is perhaps the most famous example of somebody who reasons from first principles rather than accepting at face value what the construction cost of a certain item should be. He goes all the way down to how much does it cost to produce these atoms and how much does it cost to bring them together? Exactly. And I think that is how you can cut through conventional wisdom that is wrong. And he's done that in different industries. And conventional wisdom may be right in a lot of cases, but it's interesting to question

it because there are some cases where it's wrong. And if it's wrong, you can discover what they call the middle of all the secret, which is really its colloquial use as applied to other things like business or investing. And you can really discover amazing investments or business opportunities this way where everybody is thinking one thing, but the world has changed a bit. And by thinking from reverse principles, you can uncover these opportunities that no one else is pursuing because everyone's following supposed conventional wisdom, which is now wrong. They're looking at the top layer and really something has changed at a lower layer that made the opportunity and new opportunity possible.

And so how do you discover those opportunities? Like prior to evaluating them, you first need to find them. Yeah. I mean, most big businesses and places where you've seen people make lots of amazing investments, there's one of these at the core of it. There are some strategies to kind of finding these secrets. One is just going around and doing bottom-up thinking. And just like, that's basically what Elon Musk has done.

Just starting from scratch on an industry or a type of investment. and running your own spreadsheet and numbers and trying to make it all add up. And you might discover a major flaw in what currently people are thinking. Another is to hang out with basically hang out with people who are doing that. So hang out with this innovator community in different areas. Like most of the things that ended up being used businesses, like even things like the internet or search engines or anything, actually started out in very small communities for long periods of time before they got mainstream.

And you can go looking at those things more. easy than ever on places like Reddit and stuff like that. And the idea is that, you know, say you know about the internet, it's like, well, how can I use this new cutting edge thing, you know, when it was cutting edge, to start a business. And obviously the internet is huge business right now. And so the idea is if you're with forward-thinking people, you can see what's kind of new out there and then see how that could be used in a new and interesting way to change how things are currently being done.

If you do spend your time with people who are in a given industry, I guess this goes back to the group think question from earlier. How do you avoid the bandwagon effect? Yeah, it's hard. You also have to avoid another problem, which is, you know, a lot of these things basically tinker around for decades before they take off. And so by asking one question, that's kind of another model that comes from venture capital firm Sequoia, why now is kind of a good one to break out of both these problems, you're asking yourself, okay, why is right now the time where this is going to take off and going all the way back to critical mass? It could be, that could be the answer. Like, it reaches some critical mass and then it's going to explode or it could be that there's

underlying cost reasons or there's an availability reason, like for an investment, a marketplace was immediately created and now this is a viable opportunity. But you're kind of asking yourself, okay, I think this may happen in the future, but why hasn't it been happening? in the last 10 years, and why do I think it's going to happen in the next three? And if you can really answer that question, then you can kind of avoid the bandwagon of all the innovators thinking that this thing is awesome and also avoid this problem of you may waste a decade of your life and it never takes off. You talked earlier about reasoning from first principles, but what about reasoning by analogy? Is there a place for that or is that a flawed heuristic?

I definitely agree there's a place for it. I mean, essentially a lot of of the mental models are are reasoning from analogy because you're you're taking an analogy from a tried and true discipline like physics and doing something from nature and applying it elsewhere. And there's a lot of, you know, historical basis for using that, but it may not be correct all the time. So there's a place for both, but it's kind of like anything. It's like you want to check, you always want to check whether it really applies or not. But if you do that check, step. It's a really big shortcut. I think one of the concepts we talk about in the book also is design patterns. You don't always have to start from scratch. If something's happening a certain way

and it's working, sometimes it's best not to try to do it differently. And there's a reason why it works. And there's a reason why everyone does something a certain way. But the first principle's idea is just a way of say of just questioning occasionally, are we sure that that's the best way that we should be doing things? Yeah, most often it probably is. And you should use that way because it's tried and true and it's going to be faster for you. But, you know, sometimes it won't be. And just at least asking the question can make you think whether it is or is not. So reasoning from first principles allows you to not be contrarian for contrarian's sake. Exactly. Good way to put it. If you're contrarian for contrarian's sake, you're just going to waste a lot of your time and effort and probably have

suboptimal results. Let's talk about the, in terms of cognitive biases, the availability heuristic. Yeah, this is kind of similar to anchoring. It's similar in the way that you're presented with information and you're kind of going off that information. But what it is is when you're thinking of like making a decision, things that are more recent in your mind play much more heavily in your thinking. and there might be things that are not in your mind that you might have heard about.

You may never heard about it's like unknown unknowns that are important to making a good decision. And so what you need to do to avoid availability bias is to not just go on what's in your head and try to write down and think about the wider things that are applied to this. I think a lot of times, you know, especially in terms of risk, as we were talking about ricks before, is in the media there's a lot of doom and gloom. And here's all the bad things that can happen to you. And it's easy to get caught up in the fear of here's all the 8 million bad things that can happen to me today that's going to lead you away from taking some good chances.

Right. And that seems like the most obvious example of the availability heuristic is that if there's a big fire that happens two blocks away, you're going to be very fire conscious for the next month. And then after that, you'll forget about it and move on. Exactly. I mean, it's like there's a illustration that we have is very famous one from like a 1970 paper about asking people what are the risks of different types of things from shark attacks to heart disease and there's like 40 different things. And people, as you might expect, from availability bias, way overestimate the risk of

things like shark attacks and way underestimate the risk of things like heart disease, just because the proportion of which they're reported in the media based on their actual occurrence. And so it sounds like as we talk through a lot of these different decision-making practices, it sounds as though slowing down and writing things down and scanning for unknown unknowns is the way to overcome some of the biases or the fallacies in your own mind. Yeah, I think that's right. if you're in kind of like ascribing a meta process to what you do, I think you're absolutely right. You slow down, use first principles to try to avoid the biases, and then you use these additional

analogies to help you go faster than just starting from scratch all the time. I think the idea, you know, with the book as well is that we've tried to write down all the possible biases and all the possible, you know, influence models in different ways that you're thinking may be skewed away from the truth just to, you know, at times people may not even be aware of some of the concepts and not even know like, oh, you know, I never really thought that about that happening to me. And so just the idea of having them listed allows you the chance to kind of run through the ideas of like, wait, am I getting caught up here with this common trap? As you go through that practice, the deliberate practice of thinking, how do you

avoid analysis paralysis. There's kind of another model about a sliding scale between reversible and irreversible decisions. This actually came from Jeff Bezos in a shareholder letter. And the idea is that reversible decisions, think of it as like a doorway that you can just walk through and walk back through. And there's not as high a consequence of those decisions. And then irreversible decisions are once you're through, you can't walk back through the door. Think about like having a kid or selling your company or something.

something like that. And to the degree which things are more irreversible, then you want these more hefty decision-making. You want to use these more complex and heavy decision-making models. But for a reversible decision, you don't need to get tied up in as much analysis process. You shouldn't just react to the first-and-tops in your head, but you could do more of a quick pass because you can always change it later. And so that's kind of what we try to tell people to have to go, too, is, to the extent this decision is reversible, try to apply some analytical thinking to it, just go ahead and make the decision. Write down why you made it and proceed, and you don't need a big structure for it. And then if it turns out to be wrong, we could just change it.

Although anytime that you're changing decision, there's a cost associated with changing it. And also you lose out on the compounding effects of what could have been. You're absolutely right. And this gets to the case of kind of how consequential it is. it's like as you get more and more consequential, that cost becomes higher and higher. The other way to kind of mitigate against that, which we do is we try to make everything open to everyone. And we have a core value around questioning assumptions. And so what we tell people to do is a key part of that is write up your decision. And so people will say, like, I'm going to go in this direction.

If anyone doesn't have any objections. And so basically if no one raises their hand, they're going to go in that direction. But if other people are watching it and say, hey, I have some experience here, I know that that's probably a bad thing, or I think you should slow down a little bit more here. They can kind of raise their hand and do that. But it doesn't force the slow decision-making process. It only forces it if someone's going to raise their hand. So most of the time, people are moving fast, but it still gives the escape hatch for people to force people to slow down. The people who are listening to this podcast, the common thread is that we all have an interest in,

personal finance and personal development. But the people who are listening come from a wide variety of professional industries. How can each person figure out how to borrow principles or borrow analogies from their own industries and apply those to the management of their lives and their money? I think that is insightful because if you're really familiar with your discipline, so a lot of things we're talking about here are things are universally applicable. But if you have your own set of mental models from your discipline and you can use them as analogies, that's a great thing to do because you've acquired all this intuition and learning about them over time. And, you know, I do that a lot because I have all this, you know, entrepreneurship experience and learned as the same thing with statistics.

And so I think that's a great thing. I mean, trying to connect things that you know to other things are really the key learning here. That's kind of the point of the idea of the secret is that sometimes when you have a lot of experience in a certain area and you try to do something different, you're actually bringing a secret to that area. You're actually bringing something new, a new way of looking at things

that might actually be helpful and might actually give you really great insights because the other people aren't thinking that way. So you're testing different. frames or testing different lenses as you look at a problem. Yeah, because you might be the first person to take some other discipline applied to another wine. You might come from a fresh perspective and uncover things that no one had uncovered before. How do you cope with the fact that thinking is hard? I mean, to truly do a good job

of thinking about a problem requires a massive amount of time and mental energy. And one thing you talk about in your book is the bike shed effect where people are eager to talk about how to solve a small problem but tend to avoid the big ones. How do you deal with that in your own life? I mean, I think that comes down to what we were talking about the Eisenhower decision matrix. You need to decide what the most important things are and you need to make time for them because it is exhausting. You know, making hard decisions is tiring, doing hard work is hiring, so you have to leave time for when you're fresh to do the hard things. Like, for instance, for Gabriel, he's a morning worker and he knows that he's best

to doing his hardest work earliest in the morning. So you need to make sure that you're not scheduling 20 different meetings in the morning that are going to make you burn out for the afternoon. And so it's about knowing yourself and when you work best and making sure that you're leaving time to do the hard things. What are some good models for evaluating decisions that you've made in the past? So there's one called, there's really a bias called hindsight bias. I think this is especially important with investing.

You know, I mentioned Angel investing earlier. There's a lot of decisions that are the right decision at the time, given you have the information you had available at that time, that turn out because of factors out of your control that are uncertain to be terrible decisions in the end. but you still made the right decision. And so what hindsight bias is really a bias that says if something goes wrong, a lot of people say, well, that was the wrong decision. Or if something goes right ends up, they say it was the right decision. When it turns out neither can be true. And so you really have to put yourself back in the frame of mind and understand if you're

going to buy your decisions in the past what was actually known at the time. And it's really hard to do. So one of the tactical things that is recommended is actually to write down all the information you have the time in your decision process so you can better evaluate it. Yeah, you need to be able to determine, was there really something foreseeable here that I missed? Or was this just bad luck? Because investing and things in life, you know, there's a lot of stuff up to chance. And if it wasn't foreseeable, you know, there really was no better choice for you to have made.

But if it was foreseeable, then there's a lesson to be learned. We'll come back to this episode in just a minute. But first, if you've been reading my blog, for a while, you see that I pretty much always wear yoga pants because they're comfortable. But the problem is that when you go to a conference or you make a speech or for those of you with jobs when you go to work, you have to wear workplace-appropriate pants. And they're just not as comfortable as yoga pants are. That's why this company called Beta Brand has dress pant yoga pants. They're workplace-appropriate pants. They have faux zippers, pockets, front buttons.

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Like maybe you have movie ticket stubs or concert ticket stubs from the first date that you went on with the person who is now your spouse. Or maybe you have photos of a favorite trip that's on your phone or on an SD card for a camera. Or maybe you have a clipping from a magazine or a newspaper article that you were once in. Or a diploma or a poster or something in your life that's really meaningful. Well, now it's easy and affordable to frame your favorite things. Just go to framebridge.com and upload your photo. Or if you have a physical item, they'll send you the packing to safely mail in that physical item. You can preview your item online in any frame style, and the team at Framebridge will custom frame your item and deliver it directly to your door, ready to hang.

And instead of paying the hundreds of dollars that you would pay at a Framing store, their prices start at $39 and all shipping is free. And plus, my listeners, get an extra 15% off. their first order at framebridge.com when they use my code, afford anything. I used them to frame the very first newspaper article that I ever wrote. On my first day working as an intern for a newspaper, I wrote this article about hauntavirus, which was an infectious disease, and it was the first article I ever published on my first day as an intern.

And so I mailed it to Framebridge, and they framed it, and now it's hanging up in my home. So get started today. Frame your photos, or send the perfect gift for weddings, birthdays and special events, go to framebridge.com and use promo code afford anything. You'll save an additional 15% off your first order. Just go to framebridge.com, promo code afford anything. Framebridge.com promo code afford anything. Oftentimes, when we look back on decisions that we've made in the past and we understand those lessons, a specific lesson that's applied to a specific situation,

How can we generalize that without overgeneralizing it? It's interesting. It's an art, not as healthy a science, but you're kind of building up that intuition. I think writing down a process here is good. Like I know a lot of venture capitalists do that. They kind of have a structured way to reevaluate their investing decisions. And if you have more of a structured process for doing it, I think you're going to be in a better place than if you're just kind of doing it happenstance.

And that structure process could be different for everything. I think one of the things about chance is that we need to remember that if you take similar chances over time, you're going to build up, you know, more information. And like, you know, maybe for an investor, it's like, boy, I just was missing that that this type of founder is really going to be unsuccessful. But you're only going to learn that after making 20 decisions like that. And so that some lessons, you know, you want to keep track of all the decisions you've made over time and see if there was a commonality between the failures or a commonality between the successes.

And where can you draw inferences from that and not necessarily take everything one at a time? You both talk about the importance of writing down your decision-making process as you're going through it so that then you can look at, back on that data later to evaluate and to learn. What specifically should you be writing down? I mean, should you be going through practices like a decision tree or like an Eisenhower decision matrix and then writing those things down so that you have a written record of it? I mean, I think it would be great for you to write down all the assumptions that you made because that's one of the things that we talk about a lot in the book about assumptions and testing your assumptions.

And so sometimes up front you can't test your assumptions, but retroactively you can say, well, that one turned out to be wrong. And you might be able to learn from that when you're making another assumption in the future. And so trying to understand also with the hindsight bias is how many of those assumptions that I made were actually foreseeably incorrect. And was there a way that I could have tested that and realized that that wasn't a mistake? But if you forget about, you know, oh, you know, I made all these assumptions and that was, that was the best information at the time, that leads you to realize that that maybe was still the best decision at the time. Yeah, I mean, I think a structured process where you standardize your template is desired, that's going to be different depending on what kind of decisions you're making.

So like at Doug.com, we have a standard project template, for example, where each project needs to list the background. the objective and success criteria. And that effectively lists out the assumptions of the project. And then we use that in the post-mortem to go back and check whether those assumptions were valid or why or why not. And why did we make them? But all those templates look the same. And I think if you're doing an investing, as we're kind of referring to the venture capitalist

earlier, they have their own sheet of paper that they've filled out over time that they're keeping a standardized. And so if you can make a kind of standardized process for yourself, if you're making repeated decisions that are similar, I think that will be beneficial because then you can more easily compare and contrast things. How do you handle this when you're making one-off life decisions? So, for example, if you're deciding whether or not to take an early retirement or whether or not to move to a different country. I think that gets back to this like cost-benefit analysis is a better model and trying to put some numbers and spreadsheet in your factors and thinking about all the options

you have in front of you. It's more that like we were talking early about where to move and kind of approaching it that way. And then it comes down to how important is this decision. If it's really important, then you probably want to put a lot of effort into it. Retiring early, I mean, you can always decide to go back to work. And, you know, moving, you can always move back. And like you were saying, there's switching costs of like, if you're moving to another country, you know, you're probably going to sell most of your belongings because you're not going to ship everything. And so moving back's not going to be as easy as deciding, maybe I'm going to retire. And then you change your mind and realize that you're bored and

you really want something intellectually stimulating to fill your days or something like that. And you can just decide to jump back into the workforce. So even big decisions like that are reversible. Yeah. I mean, I think most, it's a degree thing, but I think most are effectively reversible. great. Well, thank you so much. How can people find you if they would like to know more about you, your work, your book? We have a book website at superthinking.com, and that's probably the best way to find out everything. Excellent. Superthinking.com, and we will link to that in the show notes. Thanks for having us on. We really appreciate it.

Thank you, Gabriel and Lauren. What are some of the key takeaways that we got from this conversation? Here are five. Number one, when you're making decisions, throw out the simple pro-con list because it's rife with problems. Some of the problems with it are when you write down pros and cons, you know, you're not writing down the weight of how much they matter. You could have people kind of look at the list and they're like one side's bigger. But a lot of those things on the bigger side may be small and inconsequential. Another issue with it is they could be interrelated things.

And then a third issue with it is oftentimes people have a predetermined idea of what decision they want to make. And they kind of bias themselves. often they want to make the decision, and so they're not really writing down or aware of all the cons on the list. So what should you do instead? Try this. Create a weighted list in which you assign a numeric value to everything, including things that are non-quantifiable.

So assign on a scale of 1 to 10 or 1 to 100 how important each aspect of this decision is to you. This is essentially a way of evaluating how important various features or qualities are to you. It's a way of assessing your relative priorities in the context of one decision, because one decision is going to have multiple factors, and each of those factors are going to have various levels of priorities. And so assigning a weighted value to them lets you make sense of the chaos. And I understand that this might sound overly procedural, but it's also a useful way to clear your head. I think people react to some of this and they're like, well, there's subjectivity in it. But there's more subjectivity in your original list by putting no numbers to it. So that is the first key takeaway.

Replace the simple pro and con list with a weighted list. Key takeaway number two. This is also an action item and this is to make decisions in the context of expected value. Let's say that you're thinking about switching to another job or you're trying to decide between two different side hustles. What you could do is create a list of various outcomes. and then assign a probability to each outcome. You might say, I'm going to switch to this new company because there's going to be more opportunities for advancement there.

And I might be able to get to salary X in fewer years. But you should really try to attribute, you know, some type of probability to what actually is the likelihood that that's going to be the outcome. And so you want to try to make a list systematically, of here's the different options and here's the different possible outcomes and then trying to attribute some probabilities to the different outcomes to see like what the expected value or expected return is on each decision. So for example, if you start this particular side hustle and you devote

10 hours a week to it and you are going to have upfront starting costs of $5,000, right? This is you're trying to decide whether or not you want to do this. Based on your research, based on people whom you've talked to, reading that you've done about it, perhaps a beta test that you've done within it, a small, low-risk beta test that you've done within it. Let's say that based on all of that, you've determined that there's perhaps a 75% probability that you'll earn an extra $1,000 a month within the next six months. But of course, there's a 50% chance that you'll earn even more than that. But then there's also a chance.

There's a slim chance, but there is a non-zero chance that you'll earn nothing and you'll lose all of your money and you'll lose all of your time. So there are all of these different outcomes that could happen and there's different probabilities of each of them. And based on all of that, you can gauge whether or not this is a plus EV decision, which means that the expected value overall is better than it is worse. In other words, given the range of possible outcomes and the likelihood of each of those outcomes, you have on balance a higher likelihood of this being a good choice than not. And then if you come up with some type of conclusion based on that, then you go back and you test your assumptions. You ask yourself, are these assumptions, these probabilities that I've

given to various outcomes, are these correct? Or is this just a whole bunch of garbage in, garbage out? And maybe that's the case. But going through that process, going through that thinking process, can help you systematically think through the various outcomes, the likelihood of those outcomes, the degree to which you know anything or can predict anything, which you may or may not be able to do, you get to make decisions in the context of probability. And so that's really the second key takeaway, is to make decisions in the context of probability and have some sort of a method for being able to at least go through a thought exercise that allows you to do it a little bit more systematically. Key takeaway number three. Talk to the people who have done the thing that you

want to do, whether what you want to do is start a business, buy an investment property, retire early, find the people who have done that, search out their stories because this brings both opportunities and risks into light. Go talk to people who have been through or faced similar things already, because a lot of things that are unknown unknowns to you are not unknown unknowns to everybody else in the world. So I'm going to add two more points to this. First, as you talk, remember that their context is different from yours.

They made their decisions in the context of a specific time, a specific place, and the then-current circumstances that they had, which are different from yours. So the question of, what did you do is different from the question, what should I do? And when you talk to people who have been in these situations before, when you talk to people who have done the thing that you want to do, the question, what do you think I should do is more. relevant to you and more valuable to you, then what did you do? You don't necessarily want their biography. Their biography might be a side effect. But what you really want to know is, based on their knowledge, based on their experience, what do they think that you should do, given your current time, place, and circumstances? So frame your questions in that way, because oftentimes that subtle shift in the way that you phrase a question, switching from what did you do

to what should I do makes all the difference. So that's the first thing that I would add to this. And the second additional point that I would like to add to this is that it can be very helpful to seek out the stories of people who have tried the thing that you want to do and yet whose outcomes are not what you desire. In other words, find people who started a business, but then that business didn't make it. Find the people who bought an investment property and had a business. bad experience with it. Find the people who retired early and then ran out of money. Listen to their

stories too because that way you're not survivorship biasing your conversations. You learn from a larger spectrum of experiences. And so that's key takeaway number three. Talk to the people who have done the thing that you want to do regardless of their outcome and ask them not what they did, but rather what they think you should do. Key takeaway number four. If you think that something is going to happen in the future, ask yourself, why now? Don't ask, will it happen, but rather ask, if it does happen, why would it happen now? You're asking yourself, okay, why is right now the time where this is going to take off and going

all the way back to critical mass? It could be, that could be the answer. Like, it reaches some critical mass and then it's going to explode or it could be that there's underlying cost reasons or there's an availability reason, like for an investment, a marketplace was immediately created and now this is a viable opportunity. But you're kind of asking yourself, okay, I think this may happen in the future, but why hasn't it been happening in the last 10 years and why do I think it's going to happen in the next three? And if you can really answer that question, then you can kind of avoid the bandwagon of all the innovators thinking that this thing is awesome and also avoid this problem of you may waste a decade of your life and it never takes off. So Gabriel's point when he talked about the question of why now

reminds me a lot about cocktail party conversation about real estate appreciation. People love to speculate about what the housing market may or may not do, which drives me bonkers because as the students in my course always hear me say, appreciation of speculation. And And broad market forces are outside of our locus of control. So why are we keeping our energy there? Why are we focusing our energy on something that is not inside of our circle of influence? And yet, people love to speculate about the housing market anyway. And I often find myself in the middle of these conversations. And, well, I mean, actually, as I say that out loud, I guess that's a problem because the common denominator is me, isn't it? But nonetheless, it strikes me that when I

hear people say casually, like, oh, I really think Las Vegas is going to rise in the next three years, or I really think that XYZ place is going to rise in the next couple of years. It strikes me that they never address the question of why now? Why specifically the time frame of 2019 through 2021 or 22 as compared with any other three-year increment? Why will this particular three-year increment be abnormally better? And I think the reason that people don't address that question, I mean, partially it's because you have to learn to ask it, but partially it's because people often look at the situation in a vacuum. We see only what's immediately in front of us and don't zoom out to contextualize it in the broader landscape of decades.

And so do we see optimistic indicators in front of us? Sure. But zoomed out, have those optimistic indicators on a long-term aggregate average more or less always been there? Yeah, they have. And as they've been there over the long term, the city has grown at a fairly steady X percent rate. So for anybody who thinks there's going to be breakout growth, I mean, again, it goes back to the question of why now? And I really, I really don't. really like that Gabriel suggested asking that because it does bring that recency bias, that availability heuristic. It brings that to the forefront of your mind when you realize that you can't answer that question. And so that is key takeaway number four. Ask why now.

Finally, key takeaway number five. In this conversation, we talked a lot about the systematic process of evaluating decisions. But having said all of this, I must temper it with the following. Don't take any of this stuff too seriously. And what I mean by that is don't take most decisions in life too seriously because life and work are what we do every day and all of it is a big experiment. If you make a mistake, move on. Most mistakes are recoverable. Most situations, to quote Marie Forleo, are figure outable. And most decisions are reversible.

So 80-20 this put an incredible. amount of time and effort into the few major irreversible decisions of your life, and don't worry too much about the rest, particularly the decisions that can be reversed. The idea is that reversible decisions, think of it as like a doorway that you can just walk through and walk back through, and there's not as high a consequence of those decisions. And then irreversible decisions are once you're through, you can't walk back through the door. Think about like having a kid or selling your company or something like that. And to the degree which things are more irreversible, then you want these more hefty decision-making. You want to use these more

complex and heavy decision-making models. But for a reversible decision, you don't need to get tied up in as much analysis process. You shouldn't just react to the first-and-tops in your head, but you could do more of a quick pass because you can always change it later. So those are five key takeaways from this conversation with Gabriel Weinberg and Lauren McCann, the authors of the book, Superthinking. If you enjoyed today's episode, please do three things. Number one, share this episode with a friend or a family member. That's a single most important thing that you can do to help spread the message of being a better thinker and improving your skill set of improving skill sets. So number one, share it with a friend or a family member.

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Thanks again for tuning in, and I will catch you next week.