The Art of Manliness - #226： The Success Equation

00:00:00.000 Brad McKay here and welcome to another edition of the Art of Manliness podcast. So when it comes

00:00:19.700 to the factors that lead to success, there's a tendency in folks to discount the role of luck.

00:00:24.220 We like to think we're the complete masters of fortune, that we can control everything that

00:00:28.280 happens to us and make our own luck. But by not giving luck its due, we actually prevent ourselves

00:00:33.520 from effectively managing this force so we can experience success in the long run. My guest today

00:00:38.040 has written a book on the math of success, skill and luck. His name is Michael Mobison, and he's

00:00:42.160 the author of the book, The Success Equation, Untangling Skill and Luck in Business, Sports

00:00:46.220 and Investing. Today on the show, Michael and I discuss the philosophy and math of luck, which

00:00:50.940 activities in life rely more on luck than skill to be successful, and what you can do to manage

00:00:54.980 luck like a poker player in order to be more successful in life. Lots of great practical

00:00:59.420 takeaways in this episode. You won't want to miss it. After you listen to the show, check

00:01:02.920 out the show notes at aom.is slash luck for resources where you can explore more about this topic.

00:01:13.880 All right. Well, Michael Mobison, welcome to the show.

00:01:17.320 Thanks, Brad. Great to be with you.

00:01:18.660 So your book is The Success Equation. And this is a fascinating book because it takes a look

00:01:23.520 at the role of skill and luck in success or failure across a wide variety of domains from

00:01:29.760 business, investing to sports. I think it's an interesting topic because I feel like us Americans

00:01:35.820 particularly, we like to discount luck. We like to talk about how any success we have is because

00:01:41.100 we worked hard, we developed our talent, and we made our own luck. Why is it that we discount

00:01:47.540 luck so much? And why is it important for businesses and individuals to take an account luck?

00:01:52.360 Yeah, Brad, it's a great question. And I have to say, in some realms, you know,

00:01:56.800 hard work probably is the key to success. If you think about, for example, some elements of

00:02:00.980 athletics, if you're a sprinter, or you know, or you're a rower, or even some kinds of businesses,

00:02:06.400 like if you're a plumber, you know, most of your success is going to be by dint of your

00:02:10.260 capabilities and your hard work. But as you point out, in other domains, there are huge doses of luck,

00:02:16.060 especially things, for example, that have social processes attached to them, you know,

00:02:19.440 the success of a book or a song or, or a film or something like that. And, or even businesses,

00:02:25.960 like you said, you know, Bill Gates in an alternate universe, would Bill Gates be Bill Gates? And the

00:02:30.800 answer is, in all likelihood, probably not. So in those instances, as you said, we have a very

00:02:35.580 difficult time understanding the substantial contribution of luck. And I think the key to this

00:02:42.040 is actually a psychological process. And there's some fascinating research done by neuroscientists who've

00:02:47.240 been able to pinpoint part of your left module in your brain, where they have a module they call

00:02:53.460 the interpreter, the job of the interpreter is to close cause and effect loops, right? So if I give

00:02:57.700 you an effect, some sort of an outcome, your mind's going to come up with a story to explain it. And

00:03:02.460 basically, the interpreter doesn't know anything about luck, right? Whenever you see a good outcome,

00:03:07.020 you assume something good was behind it, typically skill. And you see a bad outcome, you assume that

00:03:11.180 something bad was behind it, typically a lack of skill. So I think that I think we have a natural

00:03:15.860 tendency just as humans to attach more skill than we probably should. And again, the significance of

00:03:23.060 luck is different by different domains, but I think that's the fundamental problem. The last thing I'll

00:03:28.320 say is, you know, if you really sit down with thoughtful people, especially thoughtful, successful

00:03:32.800 people, almost always they acknowledge the role of luck in their process. They just understand that

00:03:39.220 certain forks in the road, they had gone the other direction, they probably wouldn't be

00:03:42.640 where they are today. So it is important for us to sit back from time to time, especially if you've

00:03:47.200 enjoyed some success. And A, be grateful and B, to recognize that, you know, that luck has probably

00:03:52.940 smiled on you along the way.

00:03:54.260 Right. Be humble about it. So let's start off with some definitions. I mean, how do you define

00:03:59.080 luck in your work? Because I've read a whole, like, surprisingly, in philosophy, there's like a whole

00:04:05.020 segment of philosophy dedicated to luck, and they have all these like really complicated definitions of

00:04:09.160 luck. How do you define it in your book? Yeah, Brett, super important. And I got to say,

00:04:14.780 as you said, you know, it spills over to philosophy very quickly. But the definition I settled on was

00:04:20.360 one, and by the way, even things I'll mention, too, words like luck and chance and fortune are

00:04:24.380 things we tend to use interchangeably day to day. But of course, they have different etymologies.

00:04:28.680 The definition I settled on was by a philosopher. And he basically said luck exists when three

00:04:33.540 conditions are in place. One, it operates for an individual organization. So it happens to you or your

00:04:38.760 favorite sports team or your company. Second is it could be good or bad. So I don't mean to suggest

00:04:44.960 that it's symmetrical because it's not, but there's a possible good luck and possible bad luck.

00:04:49.480 And third, and I think this is sort of the pivotal one, it's reasonable to expect a different outcome

00:04:54.000 could have occurred. So if we could somehow rewind the tape of time and play it again,

00:04:59.080 it would be very reasonable to see a different outcome unfold. And so when those three conditions

00:05:04.220 are in place, you can sort of check those off, I think you can suggest that luck is around.

00:05:09.600 And another way to think about it, maybe even a more basic way to think about it, and especially

00:05:13.560 when you're communicating to younger people, for instance, or giving people advice, is to think

00:05:17.060 about what is in your control and what is not in your control. So if it's in your control, it's not

00:05:20.900 going to be luck, right? Because that's, you know, it's your effort, it's your preparation,

00:05:24.660 it's your hard work. If it's out of your control, we'll call that the realm of luck.

00:05:29.740 And so as is, you know, always good advice for everybody, whether they're athletes or

00:05:33.440 business people is to focus on what you can control and do everything you can to succeed

00:05:37.040 and to recognize what's out of your control is beyond your capabilities. And you should

00:05:41.740 take it with some sort of a, you know, reasonable philosophical attitude.

00:05:44.760 Right. Um, so how is, uh, I mean, we often associate luck with like gambling, right? And

00:05:48.600 gambling, we associate with sort of randomness and chance. How is, is luck the same as randomness

00:05:53.640 or is like randomness just a part of luck?

00:05:55.460 Yeah, we talked about it a little bit of a different, you know, um, we talked about

00:06:00.120 randomness more on a system level and luck on a more individual level. So for example,

00:06:04.220 you just pointed out really good example. Let's say we have, you know, a bunch of people in

00:06:07.760 a room, we flip coins and we ask them to call heads or tails. You know, if we have 30, let's

00:06:12.440 say 50 or 60 people, we know statistically that it's very likely that one person will get four

00:06:17.060 or five in a row. Correct. So that's the element of randomness we know ahead of time. If you happen

00:06:22.820 to be the guy that calls them right, I'm going to call you lucky. Right. So, so randomness,

00:06:27.340 I think of more as a higher level, it's more of a system level and luck would be more of an

00:06:31.860 individual situation. So that's how I try to parse those two things. But these are, I mean,

00:06:36.580 you're grazing really important issues. And I think thinking about these things carefully

00:06:39.740 can provide some insights to allow you to, to understand the whole concept more effectively.

00:06:44.500 Gotcha. Um, so you make this interesting case in the book. It's like when I listened to

00:06:48.840 your talk, talking about what you define as luck and what you define as skill, you know,

00:06:52.260 skill is what we have in our control. Luck is what's not our control. I intuitively think,

00:06:56.220 well, if I increase my skill, it means I have more control over a particular domain because

00:07:01.100 I have more knowledge and ability to, uh, you know, to act in that domain. And so luck decreases,

00:07:06.620 but you make this counterintuitive argument that actually as skill increases, uh, luck plays

00:07:13.780 more of a role. Why is that? Yeah, Brett, it's super interesting writing and somewhat

00:07:18.700 counterintuitive. Um, I want to be super, super clear that it's not my idea. It was, um, I learned

00:07:23.280 this from Steven J. Gould, a famous biologist, but we called it the paradox of skill. And the basic

00:07:28.460 idea, as you said, um, is that it can be the case skill goes up, luck becomes more important. And the

00:07:33.880 way to, to, um, sort of understand that is to think about skill across two dimensions. The first is

00:07:39.920 absolute skill. And I think we can say, you know, pretty confidently as we look around the world,

00:07:45.200 the level of absolute skills never been higher than it is today. You know, athletics is a great

00:07:48.920 example. We know, for example, athletes, um, that perform against the clock, we're moving

00:07:53.980 asymptotically toward physical limits, certainly in the world of business, certainly world of

00:07:57.920 investing. So that's the first dimension. But the second one is the poor, probably the more

00:08:02.320 important one for distinguishing yourself. And that is relative skill, right? Which is how good is the

00:08:06.800 very best person versus the average person in that same, um, uh, business or activity. And there we

00:08:13.920 see quite consistently that relative skill is actually going down. So one concrete example

00:08:19.160 that Gould gave that we repeated was, um, baseball batting averages. So it turns out the average

00:08:24.380 batting average in baseball has been pretty consistent over time around 260 to 270. And that's

00:08:29.500 because both the hitters and the pitchers are improving roughly in lockstep. But it turns out

00:08:35.020 the last player to hit over 400 offensive player was Ted Williams, which was 1941. And the reason that

00:08:41.080 was so long ago is because there was a much higher standard deviation of batting average because

00:08:45.260 there was a higher standard deviation of skill. So over time, the capabilities of the players have

00:08:51.240 become more uniform, which means they offset. And so luck has become more important. So the paradox of

00:08:56.280 skill basically says, think about skill, not only absolute levels of skill, but also relative skill.

00:09:01.680 And if relative skill is narrowing, luck actually may be more important than dictating outcome.

00:09:05.720 So it's a really, it's a counterintuitive thought where it shows up the most vividly is probably the

00:09:10.220 world of investing. And you, I'm sure you've heard people say, you know, markets are random walks and

00:09:14.520 things like that. And, you know, the market looks like a big casino or gambling. I don't think those

00:09:18.700 metaphors are necessarily totally true, but this idea that basically the prices reflect most of the

00:09:24.440 information out there means that in effect, it becomes really difficult to beat it. So it feels

00:09:28.760 like a little bit like a random game. It's again, not because of a lack of skill of investors,

00:09:32.820 it's actually because of a surfeit of skill of investors, they basically offset and luck becomes

00:09:37.500 the determining factor. Right. So if people are at the same level of skill, high level skill, then

00:09:43.380 yeah, luck is going to determine whether, so it's like in football, right? You have two equally,

00:09:47.560 you know, uh, sized teams that are just equally talented, but maybe the ball fumbles, you know,

00:09:53.080 for some, whatever reason, you don't know why that's going to determine the game and not

00:09:56.320 particularly the skill of the player. Exactly. And that's a perfect, you know,

00:09:59.300 it's a great example where it might just be, you know, uh, you know, a fumble, there's a fumble

00:10:03.160 that gets recovered by team A versus team B. It could be a weird bounce of a punt. It could be

00:10:07.260 some unusual thing that under normal circumstances would be, um, relatively in unimportant in the

00:10:13.560 course of events, but for that particular game, because there's such an equal match and, you know,

00:10:17.660 you see it in professional sports, by the way, the other way to think about this is almost all

00:10:21.420 professional sports and probably more vivid example than the NFL. And it would be something like

00:10:25.920 the NBA is that they become very international, right? So these are, you're getting the best

00:10:30.360 athletes from around the world. There's big money. The training techniques have gotten quite

00:10:33.960 uniform. The coaching techniques have gotten quite uniform. So best practices spill over very quickly

00:10:39.260 with the very best athletes. And so by almost by definition, you get, uh, effectively this parity

00:10:44.580 and skill. And then again, the bounce of the ball, uh, becomes the determining factor in success or

00:10:50.160 failure. Gotcha. So in the book, you talk about how, um, uh, statisticians have been

00:10:55.800 able to, uh, just categorize different domains on this sort of luck continuum skill. So, you know,

00:11:02.000 some activities require more luck, some activities require more skill. How are they able to do that?

00:11:08.500 Yeah. And so this is a little trick, um, from the world of statistics and, uh, you know,

00:11:13.480 they sort of, the statisticians call it the Pythagorean theorem of statistics and I won't get too fancy

00:11:18.420 into it, but the basically the, the, the theorem is the idea is that if you look at the variance,

00:11:23.140 so basically the, the range of differences for an independent distribution a, and you add the

00:11:28.820 variance for independent distribution b, that equal the variance of independent distribution c,

00:11:34.620 right? So a plus b equals c, you're looking at the variance, right? That wages. And so variance of a

00:11:38.980 will call it skill, right? We'll call that variance, uh, distribution is skill. Luck will call it b,

00:11:43.840 and then c will be the outcome. So what these guys do is kind of cool, right? So they look at the

00:11:48.100 variance of actual outcomes. So for example, the wind loss, the variance in wind loss records for,

00:11:53.060 the NBA, let's pick that as an example. And we know with statistical modeling, what the variance

00:11:59.320 will look like if it was pure luck. In other words, if a coin toss determined the wins or losses of

00:12:04.220 every game. So instead of, uh, the two teams playing against the Warriors, don't play the

00:12:08.340 Cavaliers. They just go out in the middle of the court, flip a coin, whoever calls the right wins,

00:12:11.800 and they go back and shower and go home. So we know what that distribution. So in other words,

00:12:15.760 we know two out of the three, we know what the empirical outcomes are of a season.

00:12:19.460 We know what luck would look like. And the difference between this, that luck and the

00:12:24.320 outcome is basically the contribution of skill. So it's a kind of a neat little trick to allow us

00:12:29.540 to get some sense of the relative contributions of skill. By the way, by applying that, you can rank

00:12:35.700 order, for example, professional sports leagues based on one season of performance. And it turns out

00:12:40.460 that North American sport with the most, uh, skill is the NBA. So the NBA shows us being the most

00:12:46.820 skill laden, or maybe more accurately, the farthest away from luck. And then it's major league

00:12:51.540 baseball, uh, the NFL, and then ice hockey, the NHL is the sport that's actually the closest to being

00:12:57.520 random. Now, baseball and football are interesting because of course, baseball teams play 10 times

00:13:02.400 as many games as baseball teams, right? So they have huge sample sizes and you can see baseball really

00:13:07.860 does have a lot of parody because if you win, I don't know, 57 or 58% of your games, you're almost

00:13:12.480 locked, uh, into the playoffs, right? So it's a sport where even the very best teams rarely win 60%

00:13:18.840 of their games over the course of a full season. Gotcha. And that, that, that emphasis on sample

00:13:23.060 size is important in trying to figure this stuff out. Cause you talk about in the book that, um,

00:13:27.140 if you don't have a large enough sample size, you can fool yourself into thinking that you won

00:13:31.840 because of skill, uh, but not luck. Totally, Brett. It's a great point. So let's first say that in,

00:13:38.260 in activities that are almost all skill sample size becomes much less important, right? So if

00:13:42.640 you and I sprint against Usain Bolt, I think we can safely say one race will tell us how we need

00:13:47.040 to know about the relative skill of our, our, our, um, our relative skill. But when, when there's

00:13:52.760 only a dollop of skill and there's a lot of luck, as you point out correctly, you need to increase

00:13:56.600 the sample size to start to understand or detect the signal from the skill. So yeah, the, the sensitivity

00:14:02.820 of the sample size that you're looking at, the number of events is, is highly conditional on

00:14:07.720 how much skills in that particular activity, right? So it does, again, it runs the gamut from

00:14:12.660 relatively small sample size doing the job to needing quite a bit of, uh, time or sample size

00:14:18.260 to be able to discern a skill from luck. Right. And you talk, you use poker as a good example of

00:14:22.660 this. Um, you know, a beginner can play poker and don't, doesn't really know anything about,

00:14:27.060 you know, the skill of poker playing and when, and they might leave thinking, Hey, I'm a great

00:14:31.540 poker player. But as you allow that, a beginner to play more and more, uh, games, um, his,

00:14:37.720 lack of school will start showing up. Yeah, exactly. And you think about even professional

00:14:42.020 poker players, uh, you know, it's not a glamorous job if you're a professional poker player, but you

00:14:46.360 have to, you have to sit and play for many, many hours on end for your skill to be sure that your

00:14:50.580 skill reveals itself. So it's, you have to slog it out. And again, your skill, your, your better

00:14:55.680 skill will ultimately prevail. But, uh, as you point out for very short, you know, just a few hands

00:15:01.040 or what have you, there's a lot, a lot of variance that can overwhelm even your, your

00:15:05.300 skillful edge. So this idea that we can sometimes fool ourselves into thinking, you know, we're

00:15:11.240 being skillful when it was actually luck was determined our success. Any examples from the

00:15:15.700 world of business or sports that highlight this tendency that we have to do that?

00:15:20.900 Yeah. I mean, I think that one of the matrix I, and I love, and it's, it's not for me, it's

00:15:24.680 this guy, Paul Shoemaker and Jay Russo came up with this as they have a matrix on process versus

00:15:29.020 outcome. And, uh, you know, you can imagine the columns being good outcome, bad outcome,

00:15:33.720 and the processes, you know, the rows being good and bad process. So if you have a good

00:15:37.120 process and a bad outcome, you know, it's bad luck and, you know, pick yourself up and

00:15:41.380 dust yourself off and do it again. If you have a good process and a good outcome, this, you

00:15:45.560 know, deserves success. But the trickier column is, is that you point out is bad process, good

00:15:49.940 outcome, right? And that's one where you start to trick yourself into thinking that you're

00:15:53.780 actually know what you're doing. Bad process, bad outcome, of course, is sort of poetic

00:15:57.360 justice of failure, right? So, so this idea of bad process and good outcome, you have

00:16:01.640 to be very mindful about that. I think we see a lot in, you know, there's an example

00:16:05.140 I mentioned in the book of a friend of mine who's actually a sports executive and he's

00:16:09.800 playing blackjack in Vegas and, you know, he's sitting around the table and this guy

00:16:13.640 is Delta 17, right? So if you know, in poker, blackjack, pardon me, if you're Delta 0.92

00:16:18.180 17, you're supposed to sit on your hand and the guy, you know, sort of weighs, the

00:16:22.160 weighs in the hit and, and that, you know, the dealer sort of pauses and flips the

00:16:26.040 card and turns over a four, right? So it makes the guy's hand and he wins and, you

00:16:29.780 know, so the crowd breaks out and high fives and so forth. But, and the dealer

00:16:33.560 actually says to him, good hit, right? And, and you're saying to yourself, well, of

00:16:38.500 course, that's a, it's a ridiculous play because if you do that a hundred times or

00:16:41.100 a thousand times, of course, you're going to be assured of losing. But in the very

00:16:44.260 short run, you're going to see this success that comes as a consequence of a poor

00:16:47.280 decision. You see it a lot actually in professional sports as well, where it's

00:16:51.040 actually almost the other way around, which also often teams don't do what they're

00:16:53.880 supposed to do. One classic example is going forward on fourth down in the NFL.

00:16:59.420 There are now, there's a lot of work on this and statistically valid work showing

00:17:02.960 that teams should be going for it more than they actually do. And they, and they

00:17:06.460 tend not to, so it's a bad process. And so you, you actually don't see what the

00:17:10.240 outcomes would be had they done the proper strategy. But it's, it's very

00:17:13.540 interesting to see that there are a lot of cognitive, you know, biases that still

00:17:17.820 prevent teams from doing what they should probably ultimately do.

00:17:20.880 Right. I also like how you talked about in the book that this tendency for us to tell

00:17:23.780 these narratives about, you know, the cause and effect leads to these sort of like

00:17:28.880 when companies hire rockstar CEOs or a team brings in a hot, you know, wide

00:17:35.140 receiver and they think this is going to change the game. And because they were

00:17:38.480 successful in this other domain or this other company, they're going to do the

00:17:41.280 same here and it doesn't work out. And in fact, it's an utter failure.

00:17:44.200 Yeah, that's super interesting. That is work done by Boris Groisberg up at Harvard

00:17:48.280 Business School. And, you know, it's basically, it's called, the book he wrote is

00:17:51.940 called Chasing Stars. And he documents in sort of devastating fashion that this idea

00:17:57.100 of hiring a superstar from another organization tends to be almost always

00:18:00.880 universally disappointing. And, you know, the main, there are a couple of reasons

00:18:04.360 for it. One is that superstar may have just been lucky at his or her prior

00:18:08.020 organization, right? So there may be just a classic regression toward the mean. But

00:18:12.160 also the second thing, I think what he emphasizes is, you know, you're changing

00:18:15.820 organizations, you're changing structures. And as a consequence, the things that

00:18:19.240 were maybe probably very helpful for you in your prior organization may not be

00:18:22.420 in the same place in your new organization. You mentioned, I'll finish on the

00:18:27.500 football thing, which is really interesting. You pointed out wide receivers

00:18:30.000 training and changing teams. And it is the case that their performance tends to

00:18:34.760 degradate when they go to the new team. There's actually, there are actually a

00:18:37.980 couple positions in football where that doesn't happen. And that is the kickers.

00:18:42.400 So the punters and the field goal kickers, their performance basically stays the

00:18:46.180 same. And that's really interesting, right? Because those are the guys that have the

00:18:49.120 least interaction effects. I mean, you need a snapper, but that's basically it,

00:18:52.540 right? Everything else remains roughly constant. So it's actually for an

00:18:56.680 interesting case to demonstrate that point. So yeah, building just by bringing in

00:19:01.740 superstars tends not to be the ideal way to do things.

00:19:04.600 Right, because it's complex, right?

00:19:06.460 Exactly. When there's more interaction effects, whenever there's, when there's an

00:19:09.880 organization or interaction effects that are contributors, major contributors to

00:19:14.720 success, you have to be very, very careful about extrapolating

00:19:18.840 performance from one organization to another.

00:19:21.260 So one concept you talk about in the book that I think is really relevant to our, to a lot

00:19:27.100 of our audience and to this like modern economy that we live in, where everyone wants to be an

00:19:31.780 information worker, they want to, you know, write the next big book, they want to start the next big

00:19:37.060 blog or whatever, is this idea of cumulative advantage. Can you explain what that is and its

00:19:43.420 connection to power laws? And what is a power law?

00:19:45.840 Yeah. And by the way, this is, this is really difficult for people to wrap their heads around,

00:19:50.500 and I'll tell you a funny story about it. So a power law is a certain kind of a distribution of

00:19:55.940 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

00:25:06.740 it can affect outcomes.

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, 0.86

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

00:27:21.280 law aspect.

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

00:28:10.300 thought.

00:28:10.820 Right. So Michael, what should we do with this information? I mean, how do we, how should we

00:28:15.180 manage the role of luck in our lives?

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.

00:33:00.440 Thank you, Brett. My 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

00:33:55.740 stay manly.

00:34:08.260 Bye.

00:34:09.700 Bye.

00:34:10.260 Bye.

00:34:10.380 Bye.

00:34:11.620 Bye.

00:34:34.000 Bye.

00:34:35.940 Bye.

00:34:37.000 Bye.

The Art of Manliness - August 17, 2016

#226： The Success Equation

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