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[Music]
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[Music]
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Michael
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we're delighted to have you here today
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to talk about your book the success
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equation totally fascinating welcome
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thanks Adam great to be here I I would
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love to hear you talk a little bit about
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this paradox of scale that you've
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discovered sort of getting us to rethink
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the relationship between luck and skill
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yeah when we first tell you what the
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paradox of skill to find it specifically
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and it basically says in activities
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where there a skill and luck it defines
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outcomes as skill improves luck becomes
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more important to determining outcomes
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that means more skill means more luck
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which seems very paradoxical I she's not
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my idea I learned about it from Stephen
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Jay Gould very eminent biologist at
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Harvard and he talked about in the
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context of Ted Williams the last player
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to hit over 400 major league baseball
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what she did in 1941 and Gould was sort
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of wondering like why is no one being
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able to achieve over 400 since that time
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and he looked at things like maybe
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because the guys play at night or they
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travel too much really none of those
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things checked out and they said maybe
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maybe Williams just this amazing player
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you know sort of immortal among mortals
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and he said you know but if you look at
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every other sport for example things
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measured against the clock there has
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been absolute performance everywhere you
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look so that doesn't seem to be the case
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and then he sort of thought about it
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more careful and you realize the actual
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result is because everyone's gotten
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better and as a result the standard
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deviation of skill has actually narrowed
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right so if you think about batting
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average for your season your player it's
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some some level of skill plus some level
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lock gives you your outcome what's
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happened generally is the standard
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deviation of skill has gone down why
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because you're recruiting players from
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the world now versus just parts of
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United States your your training better
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your coaching better all those kinds of
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things so it turns out just to be
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statistical for a second the standard
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deviation of batting average in 1941 was
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about 0.32
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they
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say notes point zero three two pardon me
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and now it's 0.28 so saying this
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differently Ted Williams was a four
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standard deviation event in 1941 if you
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were to be a four standard deviation
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event in 2011 now you'd hit 380 which is
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still awesome right but it below 400 so
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the point is this paradox of skill we've
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seen the differential skill narrowing we
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see really all over the place we see it
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in the world of invest we see in the
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world of business so I think it is very
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interesting as skill improves especially
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in competitive markets luck becomes more
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important determining outcomes it's
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incredibly interesting and much the
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opposite of what most of us want to
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believe so what do you do about this if
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you're taking this knowledge as a
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business professional or a leader well
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the couple things are possible one is to
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think about finding fields where there
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is differential skill right so if you if
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you see something that's very highly
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competitive you really have to have
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something completely different to get
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you on the right side of the tail just
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the tail of the skill distribution so
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that's probably the easiest things to
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think about things where there is
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differential skill or try to attack a
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more skillful player using an unusual
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tactic for example mm-hmm that makes a
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lot of sense and how do you explain
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obviously there's some outliers that
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sort of don't fit this picture I think
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of Miguel Cabrera winning the Triple
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Crown of course this past year is that
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luck or is there a way still to
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cultivate scale even though you're
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dependent on luck more than yeah and
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athletics is a great example so one of
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the points I would make which i think is
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a pretty common sense once I say it is
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that whenever you see an outlier in
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sports it's almost always where it is
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always a combination of really good
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skill and really good luck and and one
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of the best ways we can measure that for
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example is through streaks so for
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example Joe DiMaggio had this 56-game
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hitting streak but if you look at all
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the players in Major League Baseball
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history who have had 30 or more hitting
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streak hitting streaks their career
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batting average is over 300 so they're
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about one and a half or two standard
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deviations away from the average so
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saying it differently not all skillful
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player have skillful players have
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streaks but all streaks are held by
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skillful players so so I think you can
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almost be assured that whenever you see
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really really good results it's skill
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and luck combined by the way you almost
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never see it on the other side right
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which is like really bad luck in really
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bad skill because those people either
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metaphorically or literally kind of died
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off right in a population so so we
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mostly see the outliers on the on the
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positive side versus the negative side
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we don't see the failures so much mm-hmm
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and so I guess that raises the question
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for me are there ways that you can
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improve your luck yeah well maybe I
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should step back and define lot because
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I think that it's actually a fascinating
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topic and when you think about luck or
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read about it it really spills into
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philosophy like a philosophy very
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rapidly so and by weather as you know
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there are tons of aphorisms about lock
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right you know luck is where success
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meets preparation and you make your own
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luck but the way I'm going to define it
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actually those aphorisms while they have
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an important sentiment aren't actually
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not accurate so I'm going to define luck
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I'll say luck exists when three
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conditions are in place number one is it
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happens to an individual or organization
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so it could be you or your team or your
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company second is it can be good or bad
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and I don't mean to say that it's
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symmetrical so it could be you know they
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could be asymmetrical but but there's a
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positive sign and a negative sign and
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the third and i think a really essential
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one is it's reasonable to expect a
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different outcome could have occurred
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it's reasonable to expect a different
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outcome could occur so when those three
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things are in place I think there is
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luck now by my definition another
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simpler way to think about it is kind of
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what's in your control versus what's out
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of your control and luck would be sort
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of what's out of your control so when
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you hear the people say like well you
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know you make your own luck what they're
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encouraging to do is work harder or be
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persistent or be gritty and those are
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all really important things but if
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that's within your control in a sense I
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put that into the skill bucket so how do
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you how do you manage luck right a
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couple ideas i'll share one is there's a
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really simple heuristic that when you
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are the favorite the stronger player you
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have positive asymmetric resources you
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want to simplify the game when you're
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the underdog you want to complicate the
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game so that would be one example and of
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course the canonical example does David
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versus Goliath and by the way it's a
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which is a really a wonderful story if
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you read the whole story but interesting
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sort of David comes up and he's
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delivering stuff to his brothers and he
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sort of like there's this ruckus going
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on like oh what's going on this guy
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Goliath he's a 65 dude you know 130
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pounds of armor sort of threatening
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everybody and so david says yeah I can
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take this guy on and originally they put
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him in armor he's going to go in and go
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toe-to-toe with Goliath he's his little
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skinny shepherd boy and David gets us
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quickly like this ain't going to work so
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so he immediately takes off all the
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armor of course his famous slingshot and
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takes five stones from the creek and
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then he goes out and uses his own
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technique so in business that would be
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for example disruptive innovation so
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rather than going straight at the leader
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you kind of come out with a flank
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strategy in warfare would be gorilla
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stir oh jeez versus again toe-to-toe in
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in football it might be trick plays
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versus you know running straight down
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the middle and trying to do so so that
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would be one way for example that would
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be a classic way to and you say it's
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common sense when you say it but it's
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remarkable in business and spores and
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even in military how underutilized
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that strategy is yeah I think that makes
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a lot of sense and it raises sort of
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another interesting question which is
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you're familiar with the really robust
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evidence for over confidence that you
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know if you take any sort of standard
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study David Donny's colleagues I think
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I've done some of the most interesting
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ones people assume about ninety percent
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of any people you would ask would assume
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they're above average on any given a
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track you know intelligence scale etc
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and so you know what you're saying
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basically requires people to assess
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whether they're a favorite or an
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underdog we know people are biased
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toward thinking that they're favourites
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so how do you temper that level of
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overconfidence to make good judgments
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about how to change the rules of a game
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yeah I mean that's a really interesting
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one I mean part of this is I want to
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frame once I like on this is going back
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to sort of the I think the Danny
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Kahneman Kahneman really Tversky idea of
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inside versus outside view right so
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you're very familiar with this but you
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know the outside views well the inside
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view says when we're trying to solve a
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problem or tackle something the typical
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way that we do it and this is where I
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overconfidence plays into this is we we
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kind of you know gather lots of
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information about the situation we
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combine it with our own poets and then
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we project into the future right so sort
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of almost idea Socratic might be strong
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but it's sort of your own point of view
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the outside view by contrast is I'm look
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at that problem as an instance of a
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larger reference class so i'm going to
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ask what happened when other people were
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in this situation before and i think
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that's one of the ways to sort of temper
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temper that overconfidence to say rather
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than looking at this sort of my own
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unique situation where i think i'm above
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average i'm going to look at what's
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happened to everybody else has tried
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this before now i actually ambivalent
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about this argument on one level right
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because if you're an entrepreneur like
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we want entrepreneurs but we know that a
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high percentage of them are going to
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fail right but we know that some small
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percent are going to succeed and create
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enormous amount of value for you know
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for society and so forth so so you want
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the our chores to get out of bed in the
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morning go like I'm going to go take the
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mountain right but if you step back and
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said no statistically right that's
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probably not a great so so I'm a little
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bit about the arm but that would be one
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of the ways I think you try to temper
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that the other thing I mentioned quickly
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on this is I think there's a really
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interesting literature this you know
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it's called under sampling failure right
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which is people a company or our team
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will pursue particular strategy and
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they'll succeed wildly another team or
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company will pursue a very similar
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strategy and fail but of course the
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failures go away and so what happens is
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you walk along go okay what strategy
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works and you see that strategy and you
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see success and so you say that's got to
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be great you understand both a yer so
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that's another way to sort of temper
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some of the thinking is to say I won't
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understand really the entirety what's
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happened with this strategy for example
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so that might be some ideas about how to
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how to mitigate the overconfidence yeah
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I think that's very helpful and it
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actually connects to one of your other
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really interesting points in the book
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which is about using better statistics
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can you talk to us a little bit about
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about how you would do that as a
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business leader yeah so you know we're
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awash in statistics right you watch a
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ball game or you read the business page
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of a newspaper or what have you and we
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know that they're not all created
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equally right so what makes for a useful
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statistic and what I basically argue for
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why you're uh she gets us from the
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sabermetrics guys that sports statistics
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guys is you really want two things one
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is you want persistence and the second
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is you want predictive value so
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persistent simply means that the actual
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statistic is correlated from one period
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to the next so for instance if I know
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your batting average for 2012 it would
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correlate highly with your batting
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average in 2013 or how well would
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correlate would be a measure of
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persistence the second thing is
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predictive value so you want that
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statistic to actually correlate highly
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with the objective you're trying to
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achieve so for example in baseball on
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offense you're trying to generate runs
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so the question is how well does batting
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average correlate with run production
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let me tie this back to Moneyball right
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I mean this is there are a lot of
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different themes in Moneyball but one of
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them was a simple one which is on base
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percentage is a better measure of
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performance than batting average and
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what they found was on base percentage
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has a higher correlation from one season
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to the next which means it's more
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indicative of skill than batting average
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does so it's going to pass the
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persistence test and then secondly
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on-base percentage actually call is
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higher with run production
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then does batting average so that's
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going to say that is a superior
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statistic because it's more persistent
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and it's more predictive and I should I
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should have backed up said hi
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persistence is almost always indicative
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of high skill low persistence typically
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lots of luck so let's take sort of maybe
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an exception to that rule which is when
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you think about the interdependence of
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different players on a baseball team or
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for example in a company to you could
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assume that you know given on-base
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percentage is attributable to scale but
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then you end up batting right after
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another highly talented batter and
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that's going to increase in general your
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on-base percentage right now so how do
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you decouple sort of the individual
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scale from the context in which you find
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yourselves super difficult right super
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difficult so part of what I when I did
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the work on on-base percentage i
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actually did I step to try to sidestep
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the problem you just articulated I did
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it on a team level versus an individual
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level I think that of course they're
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going to roll up on some level but but
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you're right and so it's it's I think
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it's a major step in the right direction
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but in some ways it can be a fairly
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blunt instrument so I think they're
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really careful statistical people try to
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understand exactly if you're batting in
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a different order what have you what
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impact will that have and try to measure
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that out and try to extract that effect
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but this also leads to another port
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that's more more broad which is for
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example to take sports which is very
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simple you know tennis is one on one and
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we have a large sample if we play a
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five-set match there's a large sample
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size right so we pretty much know by the
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end of ten of match tennis match who
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which of us has been more skillful but
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as you said like you get into a football
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game or football you're you know a
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football for us at world right soccer
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there are a lot of players a lot of
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interaction and identifying those
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effects of individuals is a vastly more
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challenging task now again doesn't mean
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you shouldn't try or try to gain some
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insight into doing that but you're right
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that the degree of difficulty goes up as
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you add complexity and of course
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corporations same thing there's a lot of
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moving parts very difficult often to say
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this that or the other cause one thing
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or another so you mentioned Danny
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condiments work earlier and he's added
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another really interesting variable to
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the equation which is are you working in
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an environment that's stable and
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predictable or much more turbulent and
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he's made the point that you can rely on
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your scale and your expertise in your
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intuition much more in a predictable
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environment but most of us don't have
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the luxury anymore of working in these
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very predictable and fire it's so how do
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you think about navigating a more
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uncertain world yeah this is such a
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fascinating topic I wrote a chapter
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about this in my prior book and I call
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it the expert squeeze and I basically
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said the main way to think about
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expertise is to think about precisely
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that continuum you just laid out so
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what's interesting in some fields there
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things are the environment stable I like
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to often say it's stable and lynna
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linear so cause and effect are very
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clear and those realms you can train
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your system 10 Danny call so you can
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train your sort of subconscious to be
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really good the challenge is
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increasingly especially in a business
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setting is that computers are taking on
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those tasks professional tasks and can
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do them very efficiently and cheaply so
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experts are good at those but
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increasingly there's an encroachment
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from technology that's and that's been a
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very that's a challenging situation the
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opposite extreme is you point out our
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environments that are unstable and
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nonlinear and there we know that experts
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are very poor predictors and there's
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really no way to train your system one
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your subconscious and so I always love
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to make this distinction especially I'm
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in the finance business the big deal
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between experience and expertise and
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people often think that experience and
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expertise sort of equal each other and
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that's true on the stable side of the
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continuum but when you're on the
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unstable nonlinear side of the continuum
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your experience really doesn't and the
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key to experience expertise part of me
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is having a predictive model that works
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and you don't really have a pretty good
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model that works so there we know that
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experts do very very poorly in their
00:15:04
predictions and by the way you know this
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is early 2013 this is the time of year
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everybody's making predictions about
00:15:09
what's going to happen and of course
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most people keep track of those things
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know that they're they're notoriously
00:15:15
very poor what's interesting though is
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that we're seeing in some cases called
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the wisdom of crowds that collectives
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can be more effective than experts in
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making judgments in those kinds of areas
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under certain conditions so I call this
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the expert squeeze because experts are
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getting squeezed on this unstable
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nonlinear side by wisdom of crowds
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properly harnessed and they're getting
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squeezed on the other side by computers
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and technology and there's less space in
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the middle for the experts to to
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navigate than they used to have so I
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think this is this is a fundamental
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first question to ask is the problem i'm
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trying to think about where is it on
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that continuing from stable linear too
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unstable nonlinear and that really
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dictates a lot about how you should
00:15:56
think about solving it and by what means
00:15:58
and techniques as well mm-hmm so to
00:16:00
build on that it seems like unlearning
00:16:03
is a big part of the equation there
00:16:04
there's some work that Nancy rothbard
00:16:06
here in Wharton was involved in showing
00:16:08
that people actually when they move from
00:16:10
one company to another end up getting
00:16:13
hurt by experience because they carry a
00:16:14
lot of baggage with them about what
00:16:16
worked in a particular context that's no
00:16:18
longer relevant to their new context do
00:16:20
any wisdom to share about how to unlearn
00:16:22
some things now I don't but you know
00:16:24
this is such a this is a I mean I big
00:16:26
obviously there's a big theme in all
00:16:29
social psychology right which is caught
00:16:31
the context of where you are is
00:16:33
incredibly important in shaping the
00:16:35
decisions that you make so right you
00:16:37
have certain experience your socialized
00:16:39
within an organization at certain way
00:16:41
and so those experiences and even
00:16:43
imprinting is you know so that the son
00:16:45
of first kinds of experiences you have
00:16:46
kind of deeply carry you through your
00:16:48
decision making for often the rest of
00:16:50
your career so I think it's a really
00:16:52
hard thing to unlearn but it's all it
00:16:55
can be at the same time very useful just
00:16:56
to be mindful that while we'd love to
00:16:59
think of ourselves as rational and
00:17:01
objective and fact-based in our own
00:17:03
decisions is it that social context be
00:17:05
it new or old organization or whatever
00:17:08
is going around you is deeply
00:17:09
influential on how you decide and that
00:17:11
that inserts a lot of humility but maybe
00:17:14
raises awareness to help people get more
00:17:16
effective at making their decisions
00:17:18
mm-hmm so you work in the world of
00:17:20
finance how do you take all this
00:17:22
knowledge and apply it to achieve
00:17:24
success in your own job yeah so there
00:17:26
are a number of different angles on that
00:17:27
one is that I like to I call it macro
00:17:31
where but macro agnostic which is to say
00:17:33
spend as little time as possible
00:17:35
predicting sort of big things in the
00:17:37
world you have to be aware what's going
00:17:39
on obviously and while those things may
00:17:41
in fact have an impact on various
00:17:43
scenarios that might happen for a
00:17:45
company or an economy but try to be
00:17:47
macro where macro agnostic now the
00:17:50
second thing is just thinking about what
00:17:51
statistics are useful for example to
00:17:53
apply that template to thinking about
00:17:55
money managers so for example hey who
00:17:57
which money managers likely to succeed
00:17:59
in the future and and we know that past
00:18:02
results are typically in
00:18:04
in effective way to anticipate future
00:18:06
results but an isolation on process a
00:18:09
manager's process might give us a better
00:18:11
insight so there are statistical ways
00:18:15
that we can start to take a glimpse get
00:18:17
a glimpse at process I think they can be
00:18:19
very helpful another thing I'll mention
00:18:20
is you know you mentioned overconfidence
00:18:22
before we talked about that that's
00:18:23
that's also rife obviously the
00:18:25
investment business and even as an
00:18:27
analyst trying to anticipate a company's
00:18:29
performance one of the classic ways that
00:18:31
that shows up is people project ranges
00:18:33
of outcomes for example sales growth
00:18:35
rates or profit levels that are vastly
00:18:38
too narrow in others there over call for
00:18:40
their own ability to understand the
00:18:41
future so just getting people to widen
00:18:43
out those ranges to think more robustly
00:18:46
about that can be very very helpful so
00:18:48
there's almost no facet of Finance where
00:18:51
these ideas don't touch and can't help
00:18:53
very hard to do a day to day but
00:18:57
awareness and then again tools and
00:18:59
techniques to try to manage it to
00:19:01
minimize the mistakes i think is a great
00:19:04
value so you managed to do all of this
00:19:06
and keep up to date on the latest
00:19:08
evidence that might inform these
00:19:10
practices how do you juggle these two
00:19:12
things simultaneously a part of it I'm
00:19:14
pretty bad at everything is yes sir so
00:19:16
no I think a lot of is just a natural
00:19:18
curiosity I'm also one of things has
00:19:20
been very helpful for me is teaching as
00:19:22
an adjunct so I'm not a real professor
00:19:24
like you are but a heralded professor
00:19:27
but but I'm being an adjunct for me has
00:19:29
been very helpful and in part the way I
00:19:31
think about it is to try to take the
00:19:32
very best of what academics bring to the
00:19:34
table and the very best of practitioner
00:19:35
so so what academics do I think that's
00:19:37
very helpful is tend to be rigorous to
00:19:41
eat their method using the scientific
00:19:42
method to understand and explore ideas
00:19:44
but they're not always totally practical
00:19:46
so I think what the practitioners bring
00:19:48
to it is hey you know we have to make
00:19:49
money and we have to have a practical
00:19:51
angle on it so so taking the best of
00:19:53
both of those worlds and trying to
00:19:54
combine them i think is what's been for
00:19:56
me the most satisfying aspect of this
00:19:58
and again if there's something you can
00:20:00
draw from the world of academia that can
00:20:01
improve your performance in some way
00:20:03
that's great and i'll say this that it's
00:20:06
interesting i've been at columbia I'm
00:20:07
about to start my 21st year teaching
00:20:09
there and when I started there there was
00:20:10
really no behavioral finance program in
00:20:13
fact I often recommend the students take
00:20:15
negotiation courses because that was the
00:20:17
closest you got to sort of tapping into
00:20:19
some of these ideas from what we now
00:20:21
call behavioral finance that's obviously
00:20:23
come a long way and I think these are
00:20:25
extraordinarily useful ideas but
00:20:27
shockingly there are whole generations
00:20:29
including my own generation of people
00:20:30
who never learn this in the classroom
00:20:31
unless you go out on your own in fact
00:20:35
and learn these things now and try to
00:20:37
put them into your process you're sort
00:20:40
of a blind spot in a lot of your
00:20:41
decision-making so that that's also
00:20:43
fascinating things a lot of people
00:20:44
running corporations have never learned
00:20:46
about these ideas and they have this
00:20:47
blind spot and trying to try to fill
00:20:50
that in a little bit i think it's been
00:20:51
really really fun activity i think
00:20:53
that's a wonderful call to action and
00:20:54
Michael thank you for joining us today
00:20:56
my pleasure thanks
00:21:00
[Music]
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you
