#226： The Success Equation
Episode Stats
Summary
When it comes to the factors that lead to success, there's a tendency in folks to discount the role of luck. We like to think we're the complete masters of fortune, that we can control everything that happens to us and make our own luck. But by not giving luck its due, we actually prevent ourselves from effectively managing this force so we can experience success in the long run.
Transcript
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Brad McKay here and welcome to another edition of the Art of Manliness podcast. So when it comes
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to the factors that lead to success, there's a tendency in folks to discount the role of luck.
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We like to think we're the complete masters of fortune, that we can control everything that
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happens to us and make our own luck. But by not giving luck its due, we actually prevent ourselves
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from effectively managing this force so we can experience success in the long run. My guest today
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has written a book on the math of success, skill and luck. His name is Michael Mobison, and he's
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the author of the book, The Success Equation, Untangling Skill and Luck in Business, Sports
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and Investing. Today on the show, Michael and I discuss the philosophy and math of luck, which
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activities in life rely more on luck than skill to be successful, and what you can do to manage
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luck like a poker player in order to be more successful in life. Lots of great practical
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takeaways in this episode. You won't want to miss it. After you listen to the show, check
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out the show notes at aom.is slash luck for resources where you can explore more about this topic.
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All right. Well, Michael Mobison, welcome to the show.
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So your book is The Success Equation. And this is a fascinating book because it takes a look
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at the role of skill and luck in success or failure across a wide variety of domains from
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business, investing to sports. I think it's an interesting topic because I feel like us Americans
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particularly, we like to discount luck. We like to talk about how any success we have is because
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we worked hard, we developed our talent, and we made our own luck. Why is it that we discount
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luck so much? And why is it important for businesses and individuals to take an account luck?
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Yeah, Brad, it's a great question. And I have to say, in some realms, you know,
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hard work probably is the key to success. If you think about, for example, some elements of
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athletics, if you're a sprinter, or you know, or you're a rower, or even some kinds of businesses,
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like if you're a plumber, you know, most of your success is going to be by dint of your
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capabilities and your hard work. But as you point out, in other domains, there are huge doses of luck,
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especially things, for example, that have social processes attached to them, you know,
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the success of a book or a song or, or a film or something like that. And, or even businesses,
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like you said, you know, Bill Gates in an alternate universe, would Bill Gates be Bill Gates? And the
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answer is, in all likelihood, probably not. So in those instances, as you said, we have a very
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difficult time understanding the substantial contribution of luck. And I think the key to this
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is actually a psychological process. And there's some fascinating research done by neuroscientists who've
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been able to pinpoint part of your left module in your brain, where they have a module they call
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the interpreter, the job of the interpreter is to close cause and effect loops, right? So if I give
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you an effect, some sort of an outcome, your mind's going to come up with a story to explain it. And
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basically, the interpreter doesn't know anything about luck, right? Whenever you see a good outcome,
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you assume something good was behind it, typically skill. And you see a bad outcome, you assume that
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something bad was behind it, typically a lack of skill. So I think that I think we have a natural
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tendency just as humans to attach more skill than we probably should. And again, the significance of
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luck is different by different domains, but I think that's the fundamental problem. The last thing I'll
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say is, you know, if you really sit down with thoughtful people, especially thoughtful, successful
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people, almost always they acknowledge the role of luck in their process. They just understand that
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certain forks in the road, they had gone the other direction, they probably wouldn't be
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where they are today. So it is important for us to sit back from time to time, especially if you've
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enjoyed some success. And A, be grateful and B, to recognize that, you know, that luck has probably
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Right. Be humble about it. So let's start off with some definitions. I mean, how do you define
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luck in your work? Because I've read a whole, like, surprisingly, in philosophy, there's like a whole
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segment of philosophy dedicated to luck, and they have all these like really complicated definitions of
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luck. How do you define it in your book? Yeah, Brett, super important. And I got to say,
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as you said, you know, it spills over to philosophy very quickly. But the definition I settled on was
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one, and by the way, even things I'll mention, too, words like luck and chance and fortune are
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things we tend to use interchangeably day to day. But of course, they have different etymologies.
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The definition I settled on was by a philosopher. And he basically said luck exists when three
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conditions are in place. One, it operates for an individual organization. So it happens to you or your
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favorite sports team or your company. Second is it could be good or bad. So I don't mean to suggest
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that it's symmetrical because it's not, but there's a possible good luck and possible bad luck.
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And third, and I think this is sort of the pivotal one, it's reasonable to expect a different outcome
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could have occurred. So if we could somehow rewind the tape of time and play it again,
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it would be very reasonable to see a different outcome unfold. And so when those three conditions
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are in place, you can sort of check those off, I think you can suggest that luck is around.
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And another way to think about it, maybe even a more basic way to think about it, and especially
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when you're communicating to younger people, for instance, or giving people advice, is to think
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about what is in your control and what is not in your control. So if it's in your control, it's not
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going to be luck, right? Because that's, you know, it's your effort, it's your preparation,
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it's your hard work. If it's out of your control, we'll call that the realm of luck.
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And so as is, you know, always good advice for everybody, whether they're athletes or
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business people is to focus on what you can control and do everything you can to succeed
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and to recognize what's out of your control is beyond your capabilities. And you should
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take it with some sort of a, you know, reasonable philosophical attitude.
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Right. Um, so how is, uh, I mean, we often associate luck with like gambling, right? And
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gambling, we associate with sort of randomness and chance. How is, is luck the same as randomness
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Yeah, we talked about it a little bit of a different, you know, um, we talked about
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randomness more on a system level and luck on a more individual level. So for example,
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you just pointed out really good example. Let's say we have, you know, a bunch of people in
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a room, we flip coins and we ask them to call heads or tails. You know, if we have 30, let's
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say 50 or 60 people, we know statistically that it's very likely that one person will get four
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or five in a row. Correct. So that's the element of randomness we know ahead of time. If you happen
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to be the guy that calls them right, I'm going to call you lucky. Right. So, so randomness,
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I think of more as a higher level, it's more of a system level and luck would be more of an
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individual situation. So that's how I try to parse those two things. But these are, I mean,
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you're grazing really important issues. And I think thinking about these things carefully
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can provide some insights to allow you to, to understand the whole concept more effectively.
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Gotcha. Um, so you make this interesting case in the book. It's like when I listened to
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your talk, talking about what you define as luck and what you define as skill, you know,
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skill is what we have in our control. Luck is what's not our control. I intuitively think,
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well, if I increase my skill, it means I have more control over a particular domain because
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I have more knowledge and ability to, uh, you know, to act in that domain. And so luck decreases,
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but you make this counterintuitive argument that actually as skill increases, uh, luck plays
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more of a role. Why is that? Yeah, Brett, it's super interesting writing and somewhat
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counterintuitive. Um, I want to be super, super clear that it's not my idea. It was, um, I learned
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this from Steven J. Gould, a famous biologist, but we called it the paradox of skill. And the basic
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idea, as you said, um, is that it can be the case skill goes up, luck becomes more important. And the
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way to, to, um, sort of understand that is to think about skill across two dimensions. The first is
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absolute skill. And I think we can say, you know, pretty confidently as we look around the world,
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the level of absolute skills never been higher than it is today. You know, athletics is a great
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example. We know, for example, athletes, um, that perform against the clock, we're moving
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asymptotically toward physical limits, certainly in the world of business, certainly world of
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investing. So that's the first dimension. But the second one is the poor, probably the more
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important one for distinguishing yourself. And that is relative skill, right? Which is how good is the
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very best person versus the average person in that same, um, uh, business or activity. And there we
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see quite consistently that relative skill is actually going down. So one concrete example
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that Gould gave that we repeated was, um, baseball batting averages. So it turns out the average
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batting average in baseball has been pretty consistent over time around 260 to 270. And that's
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because both the hitters and the pitchers are improving roughly in lockstep. But it turns out
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the last player to hit over 400 offensive player was Ted Williams, which was 1941. And the reason that
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was so long ago is because there was a much higher standard deviation of batting average because
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there was a higher standard deviation of skill. So over time, the capabilities of the players have
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become more uniform, which means they offset. And so luck has become more important. So the paradox of
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skill basically says, think about skill, not only absolute levels of skill, but also relative skill.
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And if relative skill is narrowing, luck actually may be more important than dictating outcome.
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So it's a really, it's a counterintuitive thought where it shows up the most vividly is probably the
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world of investing. And you, I'm sure you've heard people say, you know, markets are random walks and
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things like that. And, you know, the market looks like a big casino or gambling. I don't think those
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metaphors are necessarily totally true, but this idea that basically the prices reflect most of the
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information out there means that in effect, it becomes really difficult to beat it. So it feels
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like a little bit like a random game. It's again, not because of a lack of skill of investors,
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it's actually because of a surfeit of skill of investors, they basically offset and luck becomes
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the determining factor. Right. So if people are at the same level of skill, high level skill, then
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yeah, luck is going to determine whether, so it's like in football, right? You have two equally,
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you know, uh, sized teams that are just equally talented, but maybe the ball fumbles, you know,
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for some, whatever reason, you don't know why that's going to determine the game and not
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particularly the skill of the player. Exactly. And that's a perfect, you know,
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it's a great example where it might just be, you know, uh, you know, a fumble, there's a fumble
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that gets recovered by team A versus team B. It could be a weird bounce of a punt. It could be
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some unusual thing that under normal circumstances would be, um, relatively in unimportant in the
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course of events, but for that particular game, because there's such an equal match and, you know,
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you see it in professional sports, by the way, the other way to think about this is almost all
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professional sports and probably more vivid example than the NFL. And it would be something like
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the NBA is that they become very international, right? So these are, you're getting the best
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athletes from around the world. There's big money. The training techniques have gotten quite
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uniform. The coaching techniques have gotten quite uniform. So best practices spill over very quickly
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with the very best athletes. And so by almost by definition, you get, uh, effectively this parity
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and skill. And then again, the bounce of the ball, uh, becomes the determining factor in success or
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failure. Gotcha. So in the book, you talk about how, um, uh, statisticians have been
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able to, uh, just categorize different domains on this sort of luck continuum skill. So, you know,
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some activities require more luck, some activities require more skill. How are they able to do that?
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Yeah. And so this is a little trick, um, from the world of statistics and, uh, you know,
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they sort of, the statisticians call it the Pythagorean theorem of statistics and I won't get too fancy
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into it, but the basically the, the, the theorem is the idea is that if you look at the variance,
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so basically the, the range of differences for an independent distribution a, and you add the
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variance for independent distribution b, that equal the variance of independent distribution c,
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right? So a plus b equals c, you're looking at the variance, right? That wages. And so variance of a
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will call it skill, right? We'll call that variance, uh, distribution is skill. Luck will call it b,
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and then c will be the outcome. So what these guys do is kind of cool, right? So they look at the
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variance of actual outcomes. So for example, the wind loss, the variance in wind loss records for,
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the NBA, let's pick that as an example. And we know with statistical modeling, what the variance
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will look like if it was pure luck. In other words, if a coin toss determined the wins or losses of
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every game. So instead of, uh, the two teams playing against the Warriors, don't play the
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Cavaliers. They just go out in the middle of the court, flip a coin, whoever calls the right wins,
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and they go back and shower and go home. So we know what that distribution. So in other words,
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we know two out of the three, we know what the empirical outcomes are of a season.
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We know what luck would look like. And the difference between this, that luck and the
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outcome is basically the contribution of skill. So it's a kind of a neat little trick to allow us
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to get some sense of the relative contributions of skill. By the way, by applying that, you can rank
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order, for example, professional sports leagues based on one season of performance. And it turns out
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that North American sport with the most, uh, skill is the NBA. So the NBA shows us being the most
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skill laden, or maybe more accurately, the farthest away from luck. And then it's major league
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baseball, uh, the NFL, and then ice hockey, the NHL is the sport that's actually the closest to being
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random. Now, baseball and football are interesting because of course, baseball teams play 10 times
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as many games as baseball teams, right? So they have huge sample sizes and you can see baseball really
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does have a lot of parody because if you win, I don't know, 57 or 58% of your games, you're almost
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locked, uh, into the playoffs, right? So it's a sport where even the very best teams rarely win 60%
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of their games over the course of a full season. Gotcha. And that, that, that emphasis on sample
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size is important in trying to figure this stuff out. Cause you talk about in the book that, um,
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if you don't have a large enough sample size, you can fool yourself into thinking that you won
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because of skill, uh, but not luck. Totally, Brett. It's a great point. So let's first say that in,
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in activities that are almost all skill sample size becomes much less important, right? So if
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you and I sprint against Usain Bolt, I think we can safely say one race will tell us how we need
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to know about the relative skill of our, our, our, um, our relative skill. But when, when there's
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only a dollop of skill and there's a lot of luck, as you point out correctly, you need to increase
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the sample size to start to understand or detect the signal from the skill. So yeah, the, the sensitivity
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of the sample size that you're looking at, the number of events is, is highly conditional on
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how much skills in that particular activity, right? So it does, again, it runs the gamut from
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relatively small sample size doing the job to needing quite a bit of, uh, time or sample size
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to be able to discern a skill from luck. Right. And you talk, you use poker as a good example of
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this. Um, you know, a beginner can play poker and don't, doesn't really know anything about,
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you know, the skill of poker playing and when, and they might leave thinking, Hey, I'm a great
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poker player. But as you allow that, a beginner to play more and more, uh, games, um, his,
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lack of school will start showing up. Yeah, exactly. And you think about even professional
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poker players, uh, you know, it's not a glamorous job if you're a professional poker player, but you
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have to, you have to sit and play for many, many hours on end for your skill to be sure that your
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skill reveals itself. So it's, you have to slog it out. And again, your skill, your, your better
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skill will ultimately prevail. But, uh, as you point out for very short, you know, just a few hands
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or what have you, there's a lot, a lot of variance that can overwhelm even your, your
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skillful edge. So this idea that we can sometimes fool ourselves into thinking, you know, we're
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being skillful when it was actually luck was determined our success. Any examples from the
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world of business or sports that highlight this tendency that we have to do that?
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Yeah. I mean, I think that one of the matrix I, and I love, and it's, it's not for me, it's
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this guy, Paul Shoemaker and Jay Russo came up with this as they have a matrix on process versus
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outcome. And, uh, you know, you can imagine the columns being good outcome, bad outcome,
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and the processes, you know, the rows being good and bad process. So if you have a good
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process and a bad outcome, you know, it's bad luck and, you know, pick yourself up and
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dust yourself off and do it again. If you have a good process and a good outcome, this, you
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know, deserves success. But the trickier column is, is that you point out is bad process, good
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outcome, right? And that's one where you start to trick yourself into thinking that you're
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actually know what you're doing. Bad process, bad outcome, of course, is sort of poetic
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justice of failure, right? So, so this idea of bad process and good outcome, you have
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to be very mindful about that. I think we see a lot in, you know, there's an example
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I mentioned in the book of a friend of mine who's actually a sports executive and he's
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playing blackjack in Vegas and, you know, he's sitting around the table and this guy
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is Delta 17, right? So if you know, in poker, blackjack, pardon me, if you're Delta
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17, you're supposed to sit on your hand and the guy, you know, sort of weighs, the
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weighs in the hit and, and that, you know, the dealer sort of pauses and flips the
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card and turns over a four, right? So it makes the guy's hand and he wins and, you
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know, so the crowd breaks out and high fives and so forth. But, and the dealer
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actually says to him, good hit, right? And, and you're saying to yourself, well, of
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course, that's a, it's a ridiculous play because if you do that a hundred times or
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a thousand times, of course, you're going to be assured of losing. But in the very
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short run, you're going to see this success that comes as a consequence of a poor
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decision. You see it a lot actually in professional sports as well, where it's
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actually almost the other way around, which also often teams don't do what they're
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supposed to do. One classic example is going forward on fourth down in the NFL.
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There are now, there's a lot of work on this and statistically valid work showing
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that teams should be going for it more than they actually do. And they, and they
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tend not to, so it's a bad process. And so you, you actually don't see what the
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outcomes would be had they done the proper strategy. But it's, it's very
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interesting to see that there are a lot of cognitive, you know, biases that still
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prevent teams from doing what they should probably ultimately do.
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Right. I also like how you talked about in the book that this tendency for us to tell
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these narratives about, you know, the cause and effect leads to these sort of like
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when companies hire rockstar CEOs or a team brings in a hot, you know, wide
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receiver and they think this is going to change the game. And because they were
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successful in this other domain or this other company, they're going to do the
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same here and it doesn't work out. And in fact, it's an utter failure.
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Yeah, that's super interesting. That is work done by Boris Groisberg up at Harvard
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Business School. And, you know, it's basically, it's called, the book he wrote is
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called Chasing Stars. And he documents in sort of devastating fashion that this idea
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of hiring a superstar from another organization tends to be almost always
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universally disappointing. And, you know, the main, there are a couple of reasons
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for it. One is that superstar may have just been lucky at his or her prior
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organization, right? So there may be just a classic regression toward the mean. But
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also the second thing, I think what he emphasizes is, you know, you're changing
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organizations, you're changing structures. And as a consequence, the things that
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were maybe probably very helpful for you in your prior organization may not be
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in the same place in your new organization. You mentioned, I'll finish on the
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football thing, which is really interesting. You pointed out wide receivers
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training and changing teams. And it is the case that their performance tends to
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degradate when they go to the new team. There's actually, there are actually a
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couple positions in football where that doesn't happen. And that is the kickers.
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So the punters and the field goal kickers, their performance basically stays the
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same. And that's really interesting, right? Because those are the guys that have the
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least interaction effects. I mean, you need a snapper, but that's basically it,
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right? Everything else remains roughly constant. So it's actually for an
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interesting case to demonstrate that point. So yeah, building just by bringing in
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superstars tends not to be the ideal way to do things.
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Exactly. When there's more interaction effects, whenever there's, when there's an
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organization or interaction effects that are contributors, major contributors to
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success, you have to be very, very careful about extrapolating
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So one concept you talk about in the book that I think is really relevant to our, to a lot
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of our audience and to this like modern economy that we live in, where everyone wants to be an
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information worker, they want to, you know, write the next big book, they want to start the next big
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blog or whatever, is this idea of cumulative advantage. Can you explain what that is and its
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connection to power laws? And what is a power law?
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Yeah. And by the way, this is, this is really difficult for people to wrap their heads around,
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and I'll tell you a funny story about it. So a power law is a certain kind of a distribution of
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outcomes. And, you know, without getting super technical, what you do is you, you plot one thing
00:20:00.460
on the x-axis on a logarithmic scale. So the difference between each of the tick marks is the same
00:20:05.360
percentage difference, right? And then you put something on the y-axis, again, a logarithmic scale,
00:20:11.420
again, each tick mark difference is the same percentage difference. Let me give you an example
00:20:15.360
to try to, and just give you an example to make it concrete. One of the classic power laws is the
00:20:20.720
size of cities in the United States. So on the x-axis, you put simply their rank. So you put
00:20:25.380
number one, number 10, number 100, number 1,000, those are the tick marks. And then you put the
00:20:29.580
population, how many people live in each of those cities. And if you plot that, it turns out that it
00:20:34.140
follows a straight line, a so-called power law. So basically, you can express it mathematically
00:20:38.320
very simply with a simple power or exponent, right? So that's the basic idea. Cumulative advantage is
00:20:45.220
this idea that essentially the strong gets stronger. So small advantages at the outset can lead to huge
00:20:52.140
advantages over time, cumulative processes, and that there's very difficult to predict which
00:20:58.760
particular good product or service is going to do that. So I'll give you one example, one story on this
00:21:04.760
that I think one experiment, I thought, brought home this point really vividly. It was an experiment
00:21:10.260
done by a number of sociologists at Columbia University called Music Lab. So this is ostensibly
00:21:14.360
about musical taste. They had 48 songs by unknown bands, right? So no one's ever heard of these songs
00:21:19.400
or these bands. And they went to college students, and they said, hey, we'd love to hear your opinion
00:21:24.000
about this music. So it's ostensibly about musical taste. So the subjects go into the site,
00:21:29.460
unbeknownst to them, by the way, 20% went into what they called independent condition. So
00:21:33.640
you could see the songs, you're asked to rate them, you know, five stars, I love it, one star,
00:21:37.760
I hate it, and download it if you really liked it. But the key was they could see what no one else
00:21:42.120
did. So they're basically in the record store by themselves. The other 80% went into 10% each into
00:21:47.680
eight, so they call them social worlds, right? So these are almost like parallel universes.
00:21:53.780
The initial setups are identical to the independent condition, but now you could see what others did
00:21:58.440
before you. So you could see what songs they downloaded, you could see what songs they liked.
00:22:02.040
And the question was, would the patterns of people preceding you affect what you said you liked and
00:22:08.000
what you downloaded? And the answer was, absolutely. So just to be clear, that the better songs,
00:22:13.280
the independent conditions had a much better chance of success in the social world. So quality does
00:22:17.640
carry something. But by and large, if you're in the top, say, quarter or top half of the,
00:22:23.540
you know, in the independent condition, basically anything could happen. And there was one song I
00:22:29.400
thought captured the whole experiment brilliantly. It was a song called Lockdown. It was number 26
00:22:33.440
in the independent condition, right? So basically the definition of average out of 48 songs. In one
00:22:39.760
of the social worlds, it was the number one hit. In another one of the social worlds, it was number 40,
00:22:44.820
right? So in one alternate universe, it's the top hit, right? So it's this cumulative advantage. What
00:22:50.080
people did before you affect what happens next. And so, you know, how does that relate to cities?
00:22:54.400
You might imagine that, you know, often people want to go where other people are. So there's this
00:22:58.720
idea of a preferential attachment model that allows that mechanism to take place. So I'll tell you,
00:23:04.500
this is my funny story to wrap this up. So one of the big magazines asked me to write a little article
00:23:11.060
on the heels of the book coming out about sort of this idea of cumulative advantage. So I was looking
00:23:16.060
around at the time, and I thought, you know, what is the greatest example, current example? And it
00:23:20.440
was Gangnam Style, right? That's the famous song. I think now it has two and a half billion downloads,
00:23:25.120
right? So I started writing this thing. It's got like 500 million downloads, and I'm sort of into
00:23:28.860
it a little bit. It's got 800 million downloads. You know, by the time I'm ready to submit, it's got
00:23:32.040
like a billion dollars of downloads, right? So it's this incredibly popular thing. And I submit the
00:23:37.400
article, and I say Gangnam Style is a function of this cumulative advantage, right? It's a good song,
00:23:41.240
but it's sort of caught on. And the editor writes back and says, you know, you don't seem to
00:23:46.800
understand that Gangnam Style has got this, you know, sort of these incredible dance moves and
00:23:50.780
this great, right? So in other words, what happens is once something's been successful, we attach this
00:23:55.580
sort of impossibly great set of attributes to it without recognizing the incredibly forceful role of
00:24:01.520
this cumulative advantage. So it's a really, really big deal. The very last thing I'll say is I teach at
00:24:08.020
Columbia Business School, and every year we bring executives in, and, you know, one of the executives
00:24:12.020
I like to bring in comes from Time Warner. And, you know, they, I think, have the largest film studio
00:24:16.520
in the world. They're one of the largest TV producers. And the guy basically said, look, we have enormous
00:24:20.520
incentive to figure out what the future hits will be. And obviously, we're very serious about this, but he's
00:24:25.380
like, we really don't know what's going to be a hit and what's not going to be a hit. So even the guys who have
00:24:29.820
the most interest in getting this right, who have the most at stake in getting it right, don't really know
00:24:34.780
what's going to happen. So again, you mentioned before, sort of our desire to link causality or
00:24:40.120
create narratives to explain outcomes. That's an area where we really, really tend to mess up.
00:24:44.060
This cumulative advantage is really tricky. And again, if we replayed the tape of Time, it's very
00:24:49.620
unlikely that Harry Potter would be Harry Potter and Madonna would be Madonna and so forth, right?
00:24:54.280
And it's hard for people to get their heads wrapped around that.
00:24:56.520
Right. But you have on your website, you have this great thought experiment where people can see with
00:25:01.220
like the jars with like colored balls that I think perfectly explains cumulative advantage and how
00:25:08.700
Yeah. I appreciate you bringing that up. It's called the Paul, your earn model. And, you know,
00:25:12.540
people should go to that. And the website is www.success-equation.com. And you'll see a bunch
00:25:18.340
of these little models. And just play around with it. You just click on the thing and let it simulate
00:25:22.440
over and over. And the basic idea is that some, it's a jar, you imagine a jar filled with marbles of
00:25:27.560
different colors. And so we're going to say the quality is going to be indicated by how many
00:25:31.780
marbles. So let's say there are five red marbles. That means the highest quality, four blue marbles,
00:25:35.740
less quality, three yellow marbles, and so forth. And the model itself is you draw one out and then
00:25:40.840
you match and then you put it back in. So if you draw a yellow one, you take another yellow, put it
00:25:44.560
back in and so forth. So you do the simulation process, which actually is very simple, but not
00:25:49.580
completely dissimilar to cumulative processes. And you can see that, again, the better skill tends to win
00:25:55.200
more of the time. But there are a lot of cases where you see sort of the middling ones take off,
00:25:59.300
or even though the lowest quality ones, again, because of these random occurrences, sort of
00:26:04.460
take off. So it's a fun way to visually get a sense of this notion of cumulative process.
00:26:09.560
Right. And I imagine the internet and social media has just compounded this idea of cumulative
00:26:14.200
advantage in the business world and music, whatever.
00:26:17.540
Massive. And I think there's a whole, there's actually a very famous paper written about 35 years
00:26:22.640
ago by a guy named Sherwin Rosen called The Economics of Superstars. And the argument he
00:26:27.300
said was basically that technology has really accelerated a lot of these events. And it
00:26:31.980
turns out, you think about it this way, you know, before, for example, phonographs or records
00:26:36.860
like that, so let's say 200 years ago, if you want to hear someone sing or hear music, you'd
00:26:41.340
have to go to your local, you know, local venue. And the number two player was, you know,
00:26:46.120
going to do almost as well as the number one player in a different community. But now, because
00:26:50.680
everyone can listen to recordings, you know, which great, with great fidelity, you're going
00:26:54.500
to basically, you, we can all avail ourselves of the very best in each field. Right. So
00:26:58.440
it's this really interesting compounding factor. Definitely.
00:27:02.280
Right. And what's interesting too, you talk about in the book too, and I think this is
00:27:04.480
good. I mean, I think it's good for people to understand because they kind of buffer some
00:27:08.460
of the, maybe the sense of failure they might have. There might be instances where there's
00:27:12.840
two companies or two individuals who are equally talented, but for some whatever reason,
00:27:16.860
one guy became a superstar because of this cumulative advantage and all this, this power
00:27:23.440
Exactly. I mean, the case, we, we give sort of a thought experiment in the book of two,
00:27:27.260
say, you know, graduate students and, you know, again, by luck or by, you know, a set of
00:27:32.440
circumstances, one gets to a little bit of a better university as a professor than the
00:27:36.340
other, even if they're essentially identical. And then over long periods of time, the one that
00:27:41.680
is at the better university may teach better students and have more access to resources
00:27:45.200
and have more productive colleagues and get more grants and so forth. And at the end of
00:27:48.780
the career, you'd look at the two and say, gee, this person, you know, person A seems to
00:27:52.160
be much more capable than person B, whereas really it was the opportunity set that came
00:27:57.240
along. And if you, you know, another way to think about all this is often success is a
00:28:00.200
function of your skills times your opportunity set. And if opportunity sets differ, even the
00:28:05.900
same skill will lead to very different outcomes. So it's really an interesting, very rich
00:28:10.820
Right. So Michael, what should we do with this information? I mean, how do we, how should we
00:28:18.760
So it's a really great question. I mean, there are tons of aphorisms about luck, you
00:28:22.740
know, preparation, you know, luck is where preparation meets opportunity or the harder
00:28:27.900
I work, the luckier I get. And, you know, and if you accept them, accept our definition,
00:28:31.960
our working definition of luck at the outset, those are actually not valid statements, right?
00:28:35.960
And again, it's what's in your control, what's not in your control. Now, I like those
00:28:39.820
aphorisms mostly because they encourage people to work hard and to prepare and so forth.
00:28:44.800
And those are all things that clearly are very important and useful. So by my
00:28:48.440
definition, you can't really change your luck, right? You can't improve your luck.
00:28:53.400
You can manage it to some degree. And a couple examples I give is, the first is
00:28:58.520
in competitive interactions, and we talked about this just a few moments ago, but
00:29:02.620
competitive interactions, the key is if you're the stronger player, what you want to
00:29:07.640
do is simplify the game as much as you can. And by simplifying the game, you assure that
00:29:12.380
your skill overwhelms that of your competitor. If you are the weaker player, what you want
00:29:16.960
to do is complicate the game, right? Add dimensions to the game. And so a couple of concrete examples,
00:29:23.160
you know, in football, it would be, for example, introducing trick plays, right? So you're still
00:29:26.720
going to be the weaker player, but the stronger team's not used to seeing certain formations or
00:29:30.680
certain types of plays. In the world of business, it would be disruptive innovation. So rather
00:29:34.720
than going toe-to-toe, releasing products to compete with the incumbent, you're going to launch
00:29:38.940
sort of these flank strategies that try to take advantage of weak spots. And then clearly in
00:29:42.920
warfare, it's guerrilla tactics, right? You don't go toe-to-toe. You use guerrilla tactics to try to
00:29:47.380
beat your enemy. So that's one strategy. The second one is really, I think what technology has allowed
00:29:53.600
us to do today more than we've been able to do in the past is so-called A-B testing. So really what
00:29:58.960
we're doing is trying to tease out causality more effectively. The great example of A-B testing is,
00:30:04.020
you know, you're an internet retailer or something, or even your website, right? You say, you know,
00:30:08.360
which website will get people to engage more with the site, you know, site A or site B? And then you
00:30:14.740
just randomly show different people A and B, and then whichever one tends to encourage more engagement
00:30:19.800
is the one you go to. So you're constantly testing A versus B to see what encourages certain types of
00:30:25.820
behavior. So again, you're teasing out causality. So those are a couple ideas. Taking one big step back,
00:30:31.760
though, I think that this idea of understanding the contribution of luck and where things are on
00:30:36.880
the so-called luck skill continuum, I mean, basically the contribution of luck, I think can
00:30:41.200
really change your attitude and philosophy about different types of activities. And again, where
00:30:46.240
it's all skill, you don't have to worry about the role of luck. But when you get to the all luck side,
00:30:51.280
understanding that things like focusing on process versus solely outcomes become much more important
00:30:56.380
and sort of having an attitude of equanimity toward luck. If you you know, if you've done
00:31:00.780
all the things in your control, successfully, and you've had a bad outcome, you know, that's that's
00:31:05.520
how it goes. That's just a bad break. And you should just wake up tomorrow morning and go out and do it
00:31:10.560
again. Right. I love that idea of focus on process, like be a poker player, they have a system, they know
00:31:15.440
what they need to do, and they're going to lose some, they know that, but they just accept it because
00:31:19.240
they know in the long run, if they stick to the system, they'll likely come out on top.
00:31:22.660
Exactly. And you know, there are a lot of things, even in athletics, you know, you'd say,
00:31:27.440
you think about many of the great sports franchises, many of them do have great players,
00:31:31.400
of course, but many of them, as you point out, same as your poker example, they have great systems.
00:31:35.580
And those systems, and they often tell the players, rely on the system, right? Because if you do your
00:31:39.480
job within the system, we will be successful. Now, it may not be successful every play or every game,
00:31:45.180
but over long periods of time, we know that those good processes lead to better outcomes. And so there
00:31:49.480
is a bit of a faith in doing that. But again, we still struggle with this, you know, we tend to be
00:31:54.160
very outcome focused because of our little interpreters in our minds, right? So you have
00:31:58.400
to be just sort of aware of that. And again, in some realms, skill is the dominant factor. So it's
00:32:04.500
really, again, where luck becomes an important contributor to the results we see.
00:32:10.440
Right. Well, Michael, this has been a great conversation, and we just scratched the surface
00:32:13.420
of the book. But where can people learn more about your book and your work?
00:32:17.020
Thanks, Brett. It's fun. Probably two things. One is michaelmobison.com. So firstname,
00:32:24.260
lastname.com. And there's references of the success equation as well as some other books.
00:32:30.380
And then we've already talked about it, but I'll just reiterate success-equation.com,
00:32:35.860
which, as you pointed out, has a couple of little fun mental exercises. Also has, by the way,
00:32:40.840
a full bibliography of the book. So if any of the particular ideas we've talked about today or
00:32:44.860
anything else in the book strikes your interest, you can typically dig into the original resources
00:32:50.980
and get more details on it and so forth. So try to give something fun for everybody who goes to the
00:32:56.760
site. Awesome. Well, Michael Mobison, thank you so much for your time. It's been a pleasure.
00:33:01.960
My guest today is Michael Mobison. He's the author of the book,
00:33:04.040
The Success Equation. It's available on Amazon.com. Go check it out. Really fascinating book.
00:33:08.260
Also check out his website, success-equation.com. He's got a lot of these probability games you can
00:33:14.560
play around with to see how skill and luck are entwined together and how you can suss things out.
00:33:21.180
It's a lot of fun to play with. Also check out the show notes at aom.is
00:33:25.200
slash luck for links to resources where you can delve deeper into this topic.
00:33:38.260
Well, that wraps up another edition of the Art of Manliness podcast. For more manly tips and advice,
00:33:43.800
make sure to check out the Art of Manliness website at artofmanliness.com. If you enjoy the
00:33:47.620
show, I'd appreciate it if you'd give us a review on iTunes or Stitcher. It helps us out a lot.
00:33:51.860
As always, I appreciate the continued support. And until next time, this is Brett McKay telling you to