Everybody knows that outcomes are a combination of skill and luck, but we tend not to be very good at understanding the relative contributions of the two.

Question: Why is the "inside view" not wise when investing? 

Michaelrn Mauboussin: The inside view says that when we face a problem, what rnall of us typically do is gather lots of information about the problem, rncombine it with our own inputs and then we forecast into the future. So rnthat could be, you know, "How long is it going to take me to remodel my rnkitchen? When am I going to finish my term paper? How long will launch arn new product for a company?"

The outside view in contrast says rnI’m going to look at my problem as an instance of a larger reference rnclass. So it allows me to ask a really simple question which is, "When rnother people have been in this situation, what happens statistically or rnprobabilistically?" There are lots of problems that we face as rnindividuals that are unique to us, but lots of other people have been rnthrough before so there’s this thing called the database of humanity rnwaiting for you to tap into it. 

The inside view, by the way, rnimportantly, is the natural way to do things; it’s sort of how your rnmind’s naturally going to work. So the outside view requires you rnbasically to leave aside this cherished information that you’ve gatheredrn and your own point of view on things in order to forecast. 

So rnit turns out that we all tend to be too reliant on the inside view whichrn often leads to too optimistic assessments of our futures. So you know rnthe old things, people say "How long’s it going to take you to remodel rnyour kitchen," and people will say to you, "Whatever you think, double rnthe time and double the cost," right? Because you’re relying on the rninside, they’re telling you, they’re reminding you to go back to the rnoutside view. But it’s true for the world of investing as well which is rnwe have lots and lots of data about, for example, the growth rates of rncompanies or the return on invested capital patterns or the returns of rnassets over time and we tend to be caught up very much in the moment rnwith our own points of view, we tend to leave that kind of information, rnvaluable information, to the side. 

So the point is, when rnappropriate, always seek to look for the outside view and help that rninform your inside view and again, more times than not, it tends to damprn optimism that’s unduly generated. 

Question: How much rnshould an investor take past performance into account? 

Michaelrn Mauboussin: Everybody knows that the outcomes they observe are a rncombination of skill and luck, but I think as people, we tend to be not rnvery good at understanding the relative contributions of the two. So onern of the ways I like to think about this is there are some activities in rnlife that are pure skill. If you and I have a running race or something rnlike that, you know, the faster person will win almost every single rntime. And there are some activities that are pure luck. If you go rnroulette or you roll the dice, it’s going to be randomness and then rnalmost everything else in life is in between. But what’s interesting is rnthey're not right in the middle, they’re almost always leaning toward rnthe skill side or they’re leaning toward the luck side. 

So the rnquestion is always when you’re observing a particular activity, where isrn it on the continuum? One of the things I like to think about are rnsports, because we have a lot of data on sports and people tend to be rnvery familiar with them. But it probably wouldn’t come as a big surprisern that things like baseball or premier league soccer in the UK tend to bern a lot more on the randomness/luck side and things like basketball or rntennis tend to be much more on the skill side. So it’s an interesting rnthing that most of us know that skill and luck combine for outcomes, butrn we don’t have a good sense of where things lie. 

So that has allrn sorts of important implications. I’ll just mention a couple of them. rnThe first is whenever there’s luck in the system, there’s going to be rnlots of reversion to the mean. That means if you have an extreme event, rneither extremely good or extremely bad, you should expect the next thingrn to be closer to average. So that’s true, for example, for corporate rnperformance. If a company’s been doing really, really well, sales growthrn has been really rapid, you should expect that the next growth rate rnshould be something closer to average. 

The second thing that’s rnreally interesting is what kind of feedback you give people. Feedback inrn our society tends to be very outcome-oriented, based on what we have rnobserved, and does it really reckon with this issue of the skill/luck rncontribution. But if you’re giving feedback properly, it should be rnfocused only on the skill component, only on what people can control andrn to the best of your ability; you should leave aside sort of the rnrandomness or the luck component.