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Transcript: Dan Ariely – Investing in Irrationality (EP.93) Published Date: April 1, 2019 Length: 1 hr, 9 min Web page: capitalallocatorspodcast.com/ariely Dan Ariely is a leading behavioral economist, author, entrepreneur, and investor. He is the James B. Duke Professor of Psychology and Behavioral Economics at Duke University and a founding member of the Center for Advanced Hindsight. He recently also became a Founding Partner of Irrational Capital. He is the author of six books, most of which have the word Irrationality in the title and has a weekly column in the The Wall Street Journal called “Ask Ariely.” Dan’s TED Talks that have been downloaded more than 10 million times.

Our conversation starts with Dan’s journey studying pain and intuition and turns to applications of his research in the corporate setting. We discuss his research process, measurement of human capital, applying experiments to an investment strategy, employee motivation and compensation schemes as investment factors, and constructing a portfolio of factors based purely on human capital. We close by touching on Dan’s projects in government and with start-ups.

Edited by: Rev.com

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Ted: 00:00:05 Hello, I'm Ted Seides, and this is Capital Allocators. This show is an open exploration of the people and process behind capital allocation. Through conversations with leaders in the money game, we learn how these holders of the keys to the kingdom allocate their time and their capital. You can keep up to date by visiting capitalallocatorspodcast.com.

Ted: 00:00:32 My guest on today's show is Dan Ariely, a renowned behavioral economist, author, entrepreneur, and investor. He is the James B. Duke Professor of Psychology and Behavioral Economics at Duke University and a founding member of The Center for Advanced Hindsight. Dan is the author of six books, most of which have the word "Irrationality" in the title. And he has a weekly column in the Wall Street Journal called Ask Ariely. Dan's TED talks have bene downloaded more than 10 million times. Dan is also a founding partner or Irrational Capital, an investment firm that identifies and quantifies the nuanced relationship between companies and their employees, and invests in human capital factors that are linked to long-term stock price performance. Last month, Irrational Capital announced a strategic partnership with Jeff Ubben's Value Act Capital, a firm that shares their belief in the importance of the impact of corporate culture on long-term enterprise value.

Ted: 00:01:36 Our conversation starts with Dan's journey, studying pain and intuition, and turns to applications of his research in the corporate setting. We discuss his research process, measurement of human capital, applying experiments to an investment strategy, employee motivation and compensation schemes as investment factors, and constructing a portfolio of factors based purely on human capital. We close by touching on Dan's projects in government and with start-ups.

Ted: 00:02:06 Today's show is sponsored by Canoe Intelligence. Canoe's software allows you to read, process and extract data from emails and PDFs you get from your managers and send them directly to your portfolio reporting system with no heirs, and in next to no time. Visit canoeintelligence.com to learn more, and mention I sent you for a special offer. Please enjoy my conversation with Dan Ariely.

Ted: 00:02:35 Dan, thanks so much for joining me.

Dan: 00:02:37 Oh, my pleasure.

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Ted: 00:02:38 I don't know how someone becomes a behavioral economist? Why don't you just start with your path?

Dan: 00:02:46 So I was badly injured, and burned 70% of my body.

Ted: 00:02:50 How old were you at the time?

Dan: 00:02:51 It was very tough. Almost 18. Very, very tough injury. I was in hospital for about three years. And life in hospital gets you to think about lots of things. For me, the beginning was mostly thinking about how to minimize the pain from bandage removal. So imagine most of your body's covered with burns, you need to take it off, somebody needs to take it off, just to put ointment and then wrap it again and do the same thing again the next day, and the question is how do you take off the bandages in a way that creates the least amount of pain? And then nurses in my department had a theory that the right way to do it is to rip the bandages off quickly, and I hated that approach. And I would argue with them.

Dan: 00:03:31 Anyway, long story short, they kept on doing what they thought was right, I kept on complaining, and then when I left the hospital and I started studying psychology, I had a professor who lost both of his legs in a landmine, this was in Israel, to a landmine. And we started talking about pain. He had experienced lots of pain, I had experienced lots of pain, and I told him about this thing and he encouraged me to start doing research on this. So I didn't burn people, instead I found other ways to examine pain, electrical shocks, pressure, all kinds of things like that. And I basically found out the nurses were wrong. Right? I found out if you have a period of pain, and you make it longer, you don't actually remember it as worse. But if you change the amplitude intensity, you can make it much worse.

Dan: 00:04:20 And the nurses were doing the wrong thing. They were trying to minimize time ripping the bandages off quickly, and maximizing momentary pain, and that was absolutely the worst thing they could have done. And that initial insight gave me the idea that there are many intuitions that we have about what's the right thing to do that might be faulty, and it was true in pain with the nurses who were professionals, it might have been other areas. And I kept on doing lots of research that came out of my life in hospital, I kept on doing experiments on hopelessness and on

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placebos and so on, but more generally I've expanded to looking at all kinds of places where we have intuition about what's the right thing to do for people and why this intuition fails and we might want to do something differently.

Dan: 00:05:05 And my path since then has been to basically try to identify where intuitions are wrong, and what should we do differently given that our intuitions are different ... that reality is different than our intuition.

Ted: 00:05:19 You've done experiments in all kinds of things. Where do you start and what's the process to get to some reach or result?

Dan: 00:05:29 Many times, it can start almost at a random place, out of curiosity? So the first thing that needs to happen is some curiosity. And that curiosity can happen from, I see something bizarre and I say "Why does that happen?" So an example for that is while I was staying in hospital, we had a ration of how many painkillers we could get. We would get six shots of morphine a day, that was our limit. And you know of course, me and all the other patients, we would track how many injections I got, how many I have left, I want to make sure I have enough for tonight to sleep, and because I'm a little obsessive I would count my medications, but I would also track other people's. Just to make sure they're not getting too much.

Dan: 00:06:12 And one night, the guy next to me, Ronnie screams at night and he asks for painkiller and the nurse goes to his room and silence, and he goes to sleep. And I knew he got his seventh injection. So I called and I said, "What's going on here? I want another injection too." And she said, "No, no." She just gave him placebo, she just gave him IV fluid. And you know, it's one thing to read about placebos, it's another thing to experience pain, painful burns, to know that the person next to you is experiencing similar pain and to know that they are quietly going to sleep after that.

Dan: 00:06:46 So that's an example of something that I experienced something, it was bizarre and strange and interesting and I wanted to look more deeply into it and that lead to lots of lots of papers on that. So that's one example. A very different example is research that is directed towards some objective. So in this next example, this is an example where we did a study in Kibera, Kibera's a slum in Kenya, and we were trying to get

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people to save a little bit of money for a rainy day, right? So here, it's not about curiosity, about something that is happening, it is basically saying that people in Kibera have bad things happening to them multiple times a year, they're not set up for this, they live hand to mouth, when something bad happens they have to borrow, interest rate in the black market is 10% a week, and then of course things just deteriorate.

Dan: 00:07:34 How do we help them save? So that kind of research is not driven by curiosity about, "Hey, I see a phenomena, what's going on here?" It's driven by, "Hey, I see a behavior that I want to change, how can I do it?" By the way, the end story of that was kind of interesting for us. I'll just deliver it quickly, we tried to incentivize them in different ways to save. We tried text message, we tried text message from their kids, we tried 10% match, 20% match, we tried lots of versions and we also tried a coin. We gave them a coin with 24 numbers written on it and we asked them to put the coin somewhere in their hut, and every week take a knife and scratch the number for that week. Week one, two, three, and scratch it like a minus if they didn't save, and up and down if they saved.

Dan: 00:08:16 And it turned out that the coin almost doubled savings compared to everything else, including 20% match.

Ted: 00:08:22 So just tracking it?

Dan: 00:08:23 So it wasn't tracking, it was a good hypothesis. But it's actually a more interesting story. So I'll tell you how I started thinking about this. So I was in Zutto, a different slum in South Africa, and I was sitting in a place that saves funeral insurance. And in South Africa, funerals are very very expensive. People in Zutto spend up to three years, sometimes, of income on funerals. It's the biggest celebration of their lifetime, right? People in the US spend crazy amount of money on weddings, in South Africa it's funerals. And by the way, from a rational perspective, funerals do make more sense because with weddings, you don't know how many you'll have.

Dan: 00:09:00 So anyway, I sat in this place where they sell funeral insurance, and a father comes in and he buys funeral insurance for a week. Just to be clear, it means it will only protect him if he dies in the next seven days. These are very poor people, they only sell funeral insurance for a week, or for a month. There's nothing

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longer than that. And he gets the piece of paper and in a very ceremonious way, gives it to his son. And as he does this, I think to myself, "What is this father doing? Why the ceremony? Why does he bring the son?" And I realized the following.

Dan: 00:09:29 Think about a very poor family, where the breadwinner of the family directs someone into savings or to insurance. What is the family going to see tonight? Less. Right? At that level of poverty, there'll be less food, less water, less kerosene, less something tonight. Less terrible poverty, there will be less this week, this month and so on. But the notion is that every time we save, or buy insurance, we don't get any positive reinforcement. Not from ourself and not from other people around us. So think about a time when people used to save in goats. Right? If you saved in livestock, you could come home from the office and you can see how many goats your neighbor has and you could compete. Now you can't compete anymore, right? So this whole category of saving and insurance is invisible. Think about, "What do you know about what your neighbors are saving?"

Ted: 00:10:20 Nothing.

Dan: 00:10:21 Nothing. What do you know about what they're spending?

Ted: 00:10:23 Something more.

Dan: 00:10:24 Yes. So what happens is we have this tremendous asymmetry and what his father was trying to do in his way, what we were trying to do with the coin, was to basically make things visible. By the way, since then, we've done lots of experiments on changing visibility of money. And every time we do it, we see an improvement in how people behave. We've shown this with opening savings accounts for kids, we've shown it with the 401K retirement. So just as an example, think about 401K. You go to a new job, you sign up for 401K, does your spouse say, "Thank you" for the money that you're going to put away? Maybe in 30 years. But the rest of it is not visible. So we just asked people to call the significant other and say, "Hi honey, I'm in this new job, they're matching a dollar for dollar, what do you think I should do? What do you think we should do?" And what happened?

Dan: 00:11:15 When you make this call, you get brownie points. Right? You're saving for the whole family. Now, does your significant other remember this three months later, who cares? The five minutes

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in which you make this decision, you get brownie points in people. People save more. Anyway, lots of things like this. So that's an example of a research project that starts with a problem. I don't think people save for emergency, let's help them out.

Ted: 00:11:36 True different, right? So one is you're deeply curious about something, another you try to find a problem. You create a hypothesis and is this just traditional research? You just sort of find and experiment, you test it, you do enough of it so that it's statistically significant and then?

Dan: 00:11:51 Absolutely, yeah.

Ted: 00:11:53 You reach some conclusion?

Dan: 00:11:54 Yeah, I think most of the traditional research is more driven than curiosity than my problems? That's what I did, I think, in the beginning part of my academic career. Sometimes it's multi-variate, my problem. I care about pain, or I care about something, but it's not often very specific problem, but over the years I become more and more interested in solving problems. So I'm a big fan of research, a big fan of science in general, but my own preference is to help things quicker and not to wait until we have the perfect solution.

Ted: 00:12:28 Do you have either a favorite experiment you've done or a favorite finding that came out of it?

Dan: 00:12:35 It changes by the day, depending on what I'm thinking about and so on. But if I think about what did I, for me, find that was the most deeply interesting for a long time, I think it was some of our findings on placebos. Placebos really work, right? People don't recognize a placebo really working. Placebo is basically the idea that the mind can change your physiology and change your physiology in a way that solves a problem. So the Pygmalion effect is one example. You take teachers and you say to them, "Half of these kids are just not that good, the kids sitting here on the left are just not that smart, and the kids that are sitting on the right are really smart and intelligent," and then you wait until the end of the semester. You find exactly what you told them, even though you told them random. You randomly assigned kids to that. Not very ethical, but it works.

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Dan: 00:13:32 And that's because what happens is the teachers act on their beliefs, right? So a kid that's supposedly not that smart says something and they read into it, not being so smart, oh it's a mistake. The kid who is very smart, they say, "Oh, maybe there's something in there." Encourage them more and so on.

Dan: 00:13:47 Another part of the placebo, the self-fulfilling prophecy, it's a little bit like Pavlov's dog. So if you remember the story with Pavlov's dog, you have bell, meat, saliva, bell, meat, saliva, bell, meat, saliva. And then eventually, the saliva shows up to the bell, you don't need the meat anymore. And that's kind of the story, that our mind often predicts the future and changes your physiology to fit with that future. So you're getting ready to go to dinner, your brain says, "Hey, dinner, dinner, dinner" and you start secreting saliva, stomach juices and so on. And this is what happens with pain. So somebody comes and gives you an injection to relieve pain, and your mind says, "Oh, pain relief is coming. Let's secrete internal opioids."

Dan: 00:14:28 We have opioids that are very, very similar to opium, just internal into our brain. And we can secrete them. And you sadly cannot close your eyes and say, "Please, please, please, can I have this substance?" But if a physician injects that, your level of belief is going to control how much of that substance is released. So in one study, we checked what happened when we gave people expensive medications and cheap medication. And we showed that the expensive medication creates higher belief, and therefore they're also more effective. So we gave people electrical shocks and we saw how much the painkiller that we gave them could reduce the pain from electrical shock and the expensive painkillers did better.

Dan: 00:15:08 But here's another version of this; we gave ... how many listeners, do you think, are golf players? A lot?

Ted: 00:15:15 No idea, but some.

Dan: 00:15:16 Okay, some must be.

Ted: 00:15:18 Enough.

Dan: 00:15:18 We gave people Callaway, Callaway's a ...

Ted: 00:15:21 Sure.

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Dan: 00:15:21 We gave them Callaway clubs and we told them that some of those clubs are real and we told the other half are fake, and we saw what happened to their golf performance. This was hitting and putting, something you can more easily measure the performance. And what do you think? Does it matter if the clubs are said to be ... they're all real clubs by the way, we didn't buy fakes ones. But it did matter. And who do you think were more affected by it? Good golfers or beginner golfers?

Ted: 00:15:51 I would think good golfers.

Dan: 00:15:53 That's right. So what happened is that the amateur golfers don't care. They don't have expectations, so they get the real ones, they get the fake ones, they don't care. The ones that are not expert like the top experts, but they're good golf players, their expectation was that the fake clubs would not work as well. And again, it was a self-fulfilling prophecy. And the reason I like this research so much is that for me, it's a fascinating way to think about the mind-body relationship, right? The mind does play a big role. We can change our natural killer cells in times of stress, we can change our physiology so this connection that we have between our expectations and our beliefs and what happened to us in reality is just an amazing, unclear story and I think the amount of human potential in there is very, very large.

Ted: 00:16:46 And at what point in time did you shift or just find your way from human behavior to the financial economic realm of behavior?

Dan: 00:16:57 So I was a very happy PC student, then I got my first job as a faculty member at MIT, and I joined also the media lab. And the media lab was always a really fun, exciting place that looks at technology and I started to become interested in both technology, but also countries who would adopt them and don't adopt them and what are the processes and so on. And so that was sort of step one of my familiarity, at least, a little bit with companies. And then the other thing, the second thing that happened, was that I became interested in motivation. And from time to time, I got invited by companies to do research internally on motivation. I did some experiments on bonuses, experiments on gifts, all kinds of things on that. And then people often asked me the question ... so I could go to a company and change motivation within a company or change bonus structure and get people to perform better. And I would

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get a question from my Wall Street friends of saying, "Can you identify the companies who are doing well on this and not?"

Dan: 00:18:03 And I decided to take that challenge seriously. So about three years ago, I started looking for data that could teach us something about human capital, about how companies treat their employees. And I started looking for data, and I look and I look and I look, and eventually I get the said data set on hundreds of companies and how they treat their employees. All kinds of ways, you could think about quality of coffee or quality of furniture or difference in salary between men and women. Think about lots of these dimensions, almost 80 of them. 80 dimensions and the data goes from 2006 until today. Right? So hundreds of companies, all of these dimensions and how companies do on them.

Dan: 00:18:51 And I played the following game, right? So this is ... a back test, but it's really a simulation. Right? So I say, "Imagine it was January 2006," and I got the first set of data. The first data is 2006, and I saw that the companies on each of those dimensions separately. So I take one dimension, that's called quality of coffee. We actually don't have quality of coffee in the data set, but it's an example, right? You have quality of coffee, and I saw the companies from the best quality of coffee to the worst quality of coffee. And I say let's build a portfolio of the top 20% of the companies that treat their employees best in terms of coffee quality, and let's just buy those stocks at the stock prices of January 1st, 2006 when you have the data.

Dan: 00:19:35 And let's hold that portfolio. And let's hold it, hold it, hold it, until we get new data. Maybe we get the new data in January 2007. And maybe one company improved in quality of coffee and we reached the top 20, and one company dropped. And we keep on having a portfolio of quality of coffee, quality of furniture, benefits, all of those things. Almost 80 of them, and what we could do with these portfolios is just say, "How much does it make? How much does it make compared to the S&P?" For example. And the reason this exercise is important, is it tells you what the building blocks are. We're going to think about other strategies to create from those dimensions, but to start with you say, "Right I could look at everything I could measure on human capital, which one mattered and by how much?"

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Dan: 00:20:23 And it turns out, the results, because you've seen some of the data, but it turns out that all of those strategies but one, all of these building blocks but one, beats the S&P on that time period, and the one that does worse is like a tiny bit worse. Not all of them do as well as others, there's a range. But one from those does slightly worse, the rest of them do just as well or better than the S&P. And this for me was an important step, because it says I can invest, in principle, without looking at quarterly reports, yearly reports, nothing about ratios of whatever. I can just look at how companies treat their employees. And not only that, it's very hard for me to find something that I could measure that does much worse than the S&P. Right? Everything I could measure does just as well.

Dan: 00:21:19 Even if you say this attribute doesn't do much better, it's still quite amazing. By the way, there's also a signal on the down side. So you could ask the question, "What happened if you buy the bottom 20%? Do those things perform worse than the S&P?" And the answer is absolutely, right? So it has a signal both on the top and the bottom. And it turns out that the dimensions that end up mattering, some of them surprised me.

Ted: 00:21:47 Tell me more.

Dan: 00:21:47 So think about something like health benefits, or benefits in general. Should matter. It turns out, they don't score that high. I mean, it's not negative but it's not very positive. Or another thing, I always show the job titles would be really good. That people would love going to places with more job titles. Turns out not a big deal. Quality of furniture, sorry to say to WeWorks and the like, it doesn't seem to make a big difference. The big difference seems to come from things, some were things we know like autonomy and trust and transparency and feeling that the company has a mission. If you look at the things that really matter, they're certainly not the things that are easily measurable. If it was quality of furniture, you could go and measure it more easily. If it was just bonuses, you could measure it more easily. If it was just health benefits, you could measure it.

Dan: 00:22:50 The things that seem to matter is the emotional connection. And I think that the reason for that is that if you get to a different level of salary or benefits or whatever, you get used to it and you don't think about it very often. How many days a year

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do people go to work and say, "This is my salary." Right? It's just not that much in the mindset. What is in the mindset is feeling trusted or getting examples of not being trusted for the worse side. So those are the things that end up mattering a lot.

Ted: 00:23:26 If we shift a little bit to some of your research and how that does or doesn't overlap. So we're gonna start with the obvious one that I would have thought of, which is compensation. You look at companies and how they compensate people compared to others. I know you've done a bunch of work on compensation as a form of motivation. I wanna talk a little bit about that work and then how it does or doesn't factor in to these models.

Dan: 00:23:51 Here's an example of a piece of research that fits very well. So this was a study in a production facility at Intel. This is a factory where people come for four days on and then they have four days off, four days on, four days off. And on the days that they work, they work for 12 hour shifts, long days. And the people at Intel said after four days off, maybe people don't come back that excited about work, maybe we need to get them to start the right way. So let's get them to start by giving them a target and giving them a bonus, 30 dollars. So you come back after four days off and they say, "Hey, please aim for 13000 chips, computer chips, today and you'll get 30 dollars." Now that system was very interesting for me because it has both a goal and a target on the first day, and nothing on the next three days. And one of the things I want to measure is goodwill, and if you think about what good will is, good will is when you're not rewarded for something exactly, how much do you pay attention?

Dan: 00:24:55 Sometimes you say, your contract is to do X, would you do Y? You're a janitor, and somebody falls, it's not in your description of your job but you still do it. But here, we have a chance to examine goodwill, right? On the first day you come, you get paid and you get the goal, the next day you don't so you have both of them. So I approach Intel and I asked them if they would allow me to do an experiment, and eventually we did the following things. We had their condition, the money on the first day. We had a control condition, with nothing. We had a pizza condition, I really wanted to send a people a pizza, and it was the idea to get people to be heroes in the eyes of their family. Right? So it's a gift and it's not money and it's social, it goes to

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the whole family. It turns out HR at Intel is unable to send people pizza at home, too complex.

Dan: 00:25:46 Amazing computer chips, no problem, pizza at home too complex. So we sent them a voucher for pizza. Not the same, and then we did a compliment. So here's what happened. People came on that day, quarter of the people got nothing, the control condition. A quarter of the people were told, "If you produce 1300 computer chips, you'll get 30 dollars," a quarter were told, "If you get to that goal, you'll get a voucher for pizza," and a quarter were told, "You'll get a text message from the boss saying nice job".

Ted: 00:26:15 Called ahead of time?

Dan: 00:26:16 Ahead of time, in the morning. And then what happened on that day? And it turns out all three methods were better than the control condition by about six percent. The money was slightly worse, one percent worse than the other two, but all of them worked, right? So any incentive you do, it basically works. But what happened the next day? And remember, the next day's important because that's goodwill. And in the money condition, it went up by about 6% on the first day, went down by 12% the next day. It actually backfired. And went slightly up over the control condition on the next two days, not catching up though to the control condition. And in general, Intel paid 30 dollars to lose about five, six percent of productivity, which is a huge ... in a production facility, that's a big deal.

Dan: 00:27:04 With this data I went to Intel's management in California, I said, "Look, clearly your intuition about what motivates people is wrong. Your system that you created has been costing you about six percent of productivity and costing you money on top of that." So I said, "Maybe your intuition is wrong about employee motivation, maybe we should examine also that you give to top management. Maybe they're not motivating there as well." How excited do you think they were to let me? No excitement whatsoever. We did fix a few things, but okay. So I told you what happened to the money, it went up and then backfired. What happened the compliment? Went up slightly more than the money and slowly went down over the next few days, but never backfiring, creating a total just benefit from that.

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Dan: 00:27:51 And the pizza condition was between them. And I suspected if the pizza was more real, gift-like, it may would have been even better than the compliment, and if it was more transactional and valid only on Tuesday at eight without black olives or something like that, and so on. By the way, I told this story when I was visiting a big insurance company in Israel, and I told them this story of motivation. The next day, the CEO sent 5000 pizzas to employees, and I met him a few weeks after that and he said he was shocked by how much positive comments he was hearing weeks after that. And you know, you're talking about people who could get pizza, right? But there's something very different about it. And here's an important thing; if I pay you, what is the time horizon of payment?

Dan: 00:28:45 The time horizon usually, you've done something for me and I'm paying you back. The books are closed, right? It's backward-looking. It's not, "I'm paying you now, you owe me." It's like, "You did something, I'm paying you back." It's short-time, and it's backward-looking. A favor is very different, right? It's open-ended and it's future-looking. But if I gave you a new pen, right? It wouldn't be, "You've done this for me, I'm giving you that," it would be forward-looking, it would create something. And companies want to create something that is future-oriented, right? You don't want to say, "Oh, I'll just pay you for the past, we're done." It's about this deep connection that has to do with we're together. That's an example of a study that fits very much in.

Ted: 00:29:33 Is there a way to then say there's certain forms of compensation structures that your hypothesis would be those companies would do better because they're motivating their employees better than other companies?

Dan: 00:29:44 The principle is that it's about caring, trust, and moving forward. Not, "I owe you", backward. So think about friendship, or romantic relationship, right? We have a very incomplete contract. In a marriage, for better or worse, we'll make it work, and you know it works in 40%, 50% of the cases which is shocking that ... it works in that high percentage. But if you think about the contract, it's basically saying we're looking forward, there'll be ups and downs, we'll make it work. So the companies that you use compensation in that regard, I predict will be much more successful, and I'll give you an example of what I do in my research center. One of the best gifts I gave

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people for the end of the year, I asked everybody in the center ... so here's the principle. I wanted to get people to recognize that I care about them as people, not just as working bodies. It's forward looking, and I wanted them to remember the gift.

Dan: 00:30:55 Seems like good principle for design, then gift certificate doesn't answer any of those things. It only answers the criteria of, "Let me do the thing that needs the least amount of work." So what did I do? I asked each person to write me half a page telling me something they want to learn somewhere in the world, up to two weeks, and I said, "I'll send you there. I'll pay for it." And people, you know, cheap hotels, coach travel. But people ended up wanting to do all kinds of things, all the way from drumming to cartoons to meditation to yoga to watching some rituals in Indonesia. It was an amazing year, it was another proof to the people that I care about them and people kept on going and coming back and anticipating and sharing, it was incredible. Now that was last year.

Dan: 00:31:46 And this year, I wanted to do the opposite. So I wanted to basically do something ... that year was about 3000 dollars on average per person. Not too high, but still an amount. So this year, I tried to do something that is very, very cheap. Just to make sure that it's not the cost. So what I did was, I created my own version of a card game. And these are all scratch-cards, and everybody has 40 cards, everybody has this pack of cards, and every Friday, sometimes every Friday, sometimes every other Friday, I tell them it's time to scratch the next card, and then they have a task. And the task is supposed to get people out of their comfort zone and get them to experience something that they might not, and reflect on it to see whether it made them happy or not. So these things involved doing things for themselves and doing things for their families, I mean there's all kinds of adventures there, and the idea is that everybody in the lab, we're about 40 people, are going to do it at the same time.

Dan: 00:32:56 We're on card number two, so card number three will come soon, and that's a very different type of gift, but I think it communicates in the same way, right? It communicates forward-looking, not backward-looking. It communicates I care about them as a person, and some of the missions, I hope nobody would listen, but some of the missions are for example to try to sleep early for a whole week, just to experience something that all know we need. It's about increasing the

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social relationship with other people in the lab, it's doing things for charity, for themselves, it's trying to be more courageous in all kinds of ways. So in the year, we can talk about how that would work. But those I think are the principles of what separates compensation from saying to somebody, "I really care." And when you think about what creates ...

Dan: 00:33:48 Let's go back to the topic of goodwill. Think about the gap between the minimum you need to do to keep your job, and the max you could do if you're truly excited. That's goodwill, right? And as a university professor, for me, the gap is very large. I've tenure, they presumably can't fire me right? So the minimum I need to do is very, very low right? The maximum is every waking hour plus coffee to try and even sleep less. And that range is completely up to me. But this range is very large for everybody. Everybody in a knowledge economy has a large range and that range is only going to increase. And this is why I think it is so important to invest in human capital. One of the things that shocks me about human capital is that when you look at companies annual reports, if a company buys a warehouse, it's an investment. If they invest in human capital, it's a cost.

Dan: 00:34:43 Where does it show, right? It doesn't show as an investment. And I think we need to change it. A couple of times, I went to talk to investors about irrational capital and I say, "Imagine that we're on day one, and you get to design annual reports. What do you really want to see there? And don't you want to see investment in human capital and success in human capital," right? There's no question that human capital is the driver of growth. What else is there? I mean, you can buy whatever warehouses you want. All right, sometimes you have market situations and a company is well-suited to do one thing or another because of some changes, but to a large degree I don't think anybody would argue that if you could draw anything you want to know from a company, you would want to know human capital is probably number one.

Dan: 00:35:34 And it's kind of shocking when you think about it, that we settle for the current annual reports and we don't almost insist as investors that we want people to know. We want to know about how they're treating their employees, what are they investing in their knowledge, in their ability, how much autonomy they're giving them.

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Ted: 00:35:55 And so these different metrics that you've used, are they difficult datasets to attain?

Dan: 00:36:03 Yes. Almost all of them are basically proprietary dataset. I think the good news is that each company that wants to do it can relatively easily start an internal process of improving human capital. And I think step one is to put HR ... HR I think is maybe the worst, least reputable department in almost every company. Maybe compliance is worse, but it's a hierarchy of the company. HR rather than being considered the R&D of the company, it's considered in bureaucracy that people don't like. But I think that the good news is that I think there's lots of steps that companies can take internally. As investors, we have this data and we're using it but it's tougher to get.

Dan: 00:36:57 And it also represents this approach, I think, of investing by getting outside data. So there's some people who are investing in agriculture based on satellite images. To some degree, this is the same thing.

Ted: 00:37:10 One of the areas that always comes up around the behavioral economics is this question of decision making and the challenges that we all have as humans in making accurate decisions.

Dan: 00:37:21 Good decisions.

Ted: 00:37:21 Forecast good decisions about the future. Is that part of the lens that you're looking at in evaluating companies?

Dan: 00:37:27 In evaluating the companies, I basically took a very simple metric approach. We said, "This is the data, that's all we have right now, we're looking for more data all the time. But that's all the data we have, and let's see what matters or not." And so it was a very much data exercise. Now within that, we looked at all kinds of things that the research lens gave us. So for example you could say, let's think about a company's potential growth. Is it affected by everybody in a company? So let's say we have a dimension like, "Do you feel safe at work?" You could imagine that every unit increase is the same, or you can imagine I really want some people to really feel safe. I want some people not to feel unsafe, right? You can say, "Is it moving from the top? The people who are extra happy? Or is it moving from the bottom, that's not having people who are behind," like you think about

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the note you left behind approach, and one, let's just talk about the low-end of the tail, or you could say, "Think about excellence" which is the top end of the tail.

Dan: 00:38:34 So there's all kinds of things like that that we're informed based on what we know from research, but to a large degree, it was, "Let's take all the data we can and trust the data." But moving forward, now there's time to ... "Okay, what else do we want to know? What else do we want to examine? So for example, one of the things we have no data on but we're really curious about is what is the role of incorporating people with very different skillset? So David, my partner, is very interested in learning what is sometimes called learning disabilities. Like think about dyslexia. Dyslexia, really interesting neurological state. Lots of very successful people historically have dyslexia. We don't know what's causing what. But you can wonder in the team, what do you need?

Dan: 00:39:33 He calls it neuro diversity, right? What's the neurological diversity? What's happening with people with disabilities? And so I have a lot of disability. I can't move my hands very well, I also have all kinds of pain still. But for example, I find that when I work on anything with young people. First of all, their eyesight is much better right? So they write apps with eight point font, which ... they have their intuitions, "Ah, this is readable." No, no, it's not readable. But also because I'm disabled, every mouse click, every button click for me is a big deal. So my designs are much more efficient than theirs. I do everything I can to reduce every mouse click and every button click on things we do. Even we do surveys and so long, for me this is such a heightened area. So anyway, this is a long way to say that I think there's other ways to examine functionality of companies and what would make companies successful.

Dan: 00:40:39 And we want to take irrational capital in that direction, is to examine the functioning of groups and the inclusion of different perspective and of course, human capital and equal treatment of gender and so on.

Ted: 00:40:55 Yeah. And how about leadership?

Dan: 00:40:56 Leadership, really interesting. Certainly very, very important. We don't have a particular angle on it yet. I will tell you that we find that in every company, when the gap between how

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leadership feels about the company and how the rank and file employees feel about the company, as this gap grows, it's a good sign to short the stock. So I think leadership is clearly very important. I don't know how to quantify it. I mean, we know leading by example, we know that those things work. So we know that leadership is important, there's no question about it.

Ted: 00:41:32 So when it comes to creating investment products out of this research, how do you decide if you've found causation?

Dan: 00:41:42 We use everything we can in terms of good statistical knowledge. And particularly for these kind of things we use models with a delay. So what you want to do is you want to say, "Oh, it's not just a correlation, it's causal." Right? What does it mean causal? One thing happened before the other one. If they happen at the same time, you might say, "Oh, I don't know which one is causing which." Most of the things we have are not quick, right? It's not ... oh, there was a press announcement and now something happened. So we work with models that have a delay in them, and we try to estimate the delay. And if you got in a model like this, the delay was reversed, right? You said, "Oh, first the company made money and then they made the environment safer," then you would say, "Oh, it's not causal." So that's one part of it.

Dan: 00:42:30 We also look at what we know from research. So we didn't approach all 80 questions with equal belief about the work, right? We have some things ... for example, sense of purpose. Right? We know that the sense of purpose works for all kinds of other things, findings itself of purpose works is not very surprising in some way. And then we also look at different dimensions. So for example, the dimension of benefits. That one changes much more as a result of how companies do financially, rather, as a lead indicator. And actually in our data, we don't see much of an effect for that. So we tried lots of different strategies. I think actually in our case, we were maybe too academic in the sense that we worked very hard for a very long time to try and come up with all kinds of scenarios while our results were wrong.

Dan: 00:43:23 Another thing that we do for example, we don't think of sectors. What they call the companies, we know you just buy the companies who treat their employees well, we don't think of sectors. We say, "Oh, maybe it's a sector strategy." So we can

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run a simulation for that, right? We say, "What if the sector that we chose, 30%, let's say it's consumer product. What if it was just a sector strategy?" But we can easily run that simulation and show it's not the case.

Ted: 00:43:49 And so even as an example on that, financial services. Which I think from the outside, most people would say, "Well, yeah, that's all that fuzzy stuff about compensation's nice, but financial services is about making money." And compare that to, maybe, healthcare or something like that where you would expect more intrinsic motivation for the employees in what they're delivering.

Dan: 00:44:12 So A, it's a good question of whether the financial services truly have just people wanting to make money, and also the question of what's happening in healthcare. So I actually wrote a paper last year on healthcare. You know that about 400 physicians kill themselves every year in the US? So one of the things we've done in healthcare is we've taken physicians, people who join medical school with the hope of curing people and so on, you wouldn't say that if you basically did a computation of how to get rich quick, you go to medical school. That's not the best. But you know, people go out with this intention and then eventually they are burdened by bureaucracy. Not long ago, somebody who was a physician, if you came to my house for dinner and it was Saturday, 9PM and you said, "Oh, I have to go, I have to be in bed before 10," I said, "Oh, tomorrow's Sunday, what's the ..." I mean even it's not.

Dan: 00:45:11 And he said, "No, no," he said. He has to wake up at 5:30 every day, he has to be in at 6:30, he has to be in the hospital. He does rounds, then he sees patients. He said he has patients every, I forgot every ... I think about 15 minutes. He said he has to schedule his bathroom breaks, right? He said, "You don't understand how lucky you are that you can go to the bathroom any time you want in the day." So we think about physicians as having a lot of autonomy, but we don't treat them this way. I mean, we do maybe in some of the TV shows, and I think in the Mayo clinic and a few other places, but mostly we take these people who really want to help people, we say, "Oh, if we give you a scalpel you can cut people any way you want, but if you want to prescribe a medication to them, that one we're not going to let you do."

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Dan: 00:46:03 And physicians often end up trying to fight bureaucracy and taking on extra work to fight the system. It's a very, very unpleasant situation. And so that's on the one hand. So you can have a profession that in principle has potential for tremendous intrinsic motivation, but it doesn't mean that we let them have intrinsic motivation. Teachers, we've done the same thing with the "No child left behind" to teachers, where we basically sucked away their joy of being teachers, because all of a sudden we said, "If you think that there's a way to teach your kids that is not the prescribed way, or if you think that one kid needs something slightly different than the other," No, no, no. You can't. Right?

Dan: 00:46:44 So that's on one side, and then on another side, in the financial world, often people say it's all about the money. But you know many of those people, I know many of them as well. I think that for many of the people I know, a big part of it is the game, it's the intellectual pursuit, it's the competition. Maybe not many people think they're doing good in the world. Some do, but not everybody, but I think it is about a competitive ... your mind is being challenged. And I think you could have taken the same group and let them play poker for points, and they would have been just as motivated to do that.

Dan: 00:47:29 So yes, the competitive nature is a big part of it, and I think that saying that it's all about making money is probably wrong. And here's an experiment I'm willing to play with you. I'm willing to take any company you want, go in there, and create a competition for an iPad and another competition for whiskey with the boss. And to see how much more we can get people to work compared to increasing the bonus pool by some percent.

Ted: 00:48:06 When you go to construct your portfolios, how do you think about taking this data. You have the top 20%, you have the bottom 20%, these are slow-moving factors. What does the portfolio look like?

Dan: 00:48:22 So first of all, the description initially, when I said we buy the top 20% it was just to look at each of the almost 18 building blocks, right? Once we had the 18 building blocks. And it was an important step for me to say, "Okay, everything we have is generally good," right? Let's just remember as well. A lot of times, when people show simulations, I worry about all the simulations they haven't shown. So, somebody shows you,

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"Here's five good simulations," how many bad simulations did you run? So for me, it was important to figure out how good are our building blocks, right? And if all the building blocks are good, then we're starting from a good perspective. We didn't have to have all but one being so good, but I want to show that in general, we have good building blocks.

Dan: 00:49:02 Once we have the building blocks, then we pick the 18 that we like the most. And we like them both on theoretical grounds and empirical grounds, and then we combine them. And we have what we predict will do well, and we have the one that we predict will not do well and we basically run this approach and we try eventually to pick about 20 companies and we go along with the 20 companies.

Ted: 00:49:29 And do you equally rate them?

Dan: 00:49:30 Yes, we do, we do. And you could imagine that we could play some game and say, "This is a [inaudible 00:49:35], we decided it's not the right approach," so we equally wait for it.

Ted: 00:49:40 And how do you think about rebalancing positions?

Dan: 00:49:42 So everything we do is automated, based on what the simulation told us from the past. So we rebalance four times a year. And it's, I would say, this approach gives me lots of joy. And part of the joy is that I think that it's good to reward companies who are doing well. It's also good to have a statement in the market. When we started this, somebody from [Ajuga 00:50:10] hedge fund, that I really admire as an individual, said, "Why don't we do it together?" He said, "Give me the data on that, I'll combine that with my financial data, and together it will be better than what you could do separately." And he's probably right. I mean, first of all he has a big hedge fund, he's been very successful, I'm sure he has insight into the performance data that we don't.

Dan: 00:50:35 But David and I felt it would take away from the mission of the fund. So part of the fund is, I want to say, "I invest only based on human capital, and here's what it does." If we did a mix, and said, "I invest in human capital plus this, and I have this return," nobody would know. But what we're hoping to do is to be driven out of the market by companies starting to treat their employees so well ... everybody would be treated very well. So

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it's both a move to say you can make money by investing in companies that treat their employees well, but it's also an attempt to focus all companies, traded and non-traded, on the importance of starting to pay attention to something that all CEOs say is the most ...

Dan: 00:51:18 I mean, how many CEOs don't usually say quality of my people is the best thing I have? Everybody says that, they just don't do it.

Ted: 00:51:24 And one thing that you didn't talk about on the financial side is just valuation. Lots of studies that show that valuation matters for future returns. How did you think about that when your lens has nothing to do with the price of the stock?

Dan: 00:51:39 Yep, and we left a lot of things out. And we basically said, "Look, we have this data going back quite a few years. We're going to ignore that and we'll see if there's still signal there." And the reality is yes. There's a lot of signal. Could we do better if we took other things into account? Probably. Would it hurt our mission? Yes. So we basically ignore everything else. And it's not that I don't think everything else is not important. I just think this is sufficiently important as a factor, and I hope to prove it over the years and I also think there's lots more to learn about human capital.

Ted: 00:52:20 Yeah. There's another part of behavior that goes into the implementation of investing, so whether it's trading and the psychology of traders, the decisions of chasing performance and things like that. I know that what you've laid out is different, but now you're in an investment strategy. How have you thought about what you know from your research that isn't exactly, "Oh, human capital, positive human capitals for companies long, and negative human capitals for companies short."

Dan: 00:52:53 Yeah, so one of the things we know and this is actually true for lots of things. For example, interviews. Job interviews are notoriously terirble. You take somebody and you get their GPA, GRE, whatever. And then you add an interview, your prediciton is worse. If it's a non-structured interview. And the reason is that every time you do an interview, you say, "Oh, this person is great because A, B and C", and then you say "This person is great because of F, G and R". You know, every time you change your criteria. And you make exceptions every time.

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Dan: 00:53:25 So one of our approaches was we don't make exceptions. We know that sometimes we'll be tempted to make exceptions, but the algorithm did not make exception. So imagine that we said, "Oh, the algorithim will tell us what companies we'll get." But then we will come and revisit it and buy the ones we feel we like and don't buy the ones we don't think, and we'll have a discussion about this. But you know, the algorithm was not built on that. The algorithm was based on just that, and you have to leave it to the algorithm. And so, we know lots of things about failing in investing. And a lot of it is the buying high and selling low and the herd mentality and bubbles and so on. And by creating an algorithm and sticking to it, with tying our hands, not to panic when bad things happen and to be true to the data.

Dan: 00:54:20 So we have an investment committee and sometimes questions come up, there's a merger or things happen and we have to ask ourselves what it is. We always return to the question of not what we feel like is the right thing to do, but what is the closest to the original intention of the algorithm. All right? So you have two companies merging, one buying the other one, and then you ask yourself, "What's the culture like? Do we take A or B, which one? Is this the average?" So we have some questions like this, but we always say not, "Do we like that company?" Or "What is the market expectation of this," but we say, "What is the algorithm going to say about this?"

Dan: 00:54:58 That I think is our approach to protect ourselves against acting not in a systematic way.

Ted: 00:55:05 And the implementation as you described it is almost the most unconstrained version of taking this hypothesis and implementing it. Have you thought about isolating the alpha signal more so you could do a fund or strategy that's more neutral across sectors or that weighs sectors according to the market, but that within that tries to create the differentiation of human capital?

Dan: 00:55:30 Yeah, we've played with things like this and we can? We just don't see a reason for this yet. So far, there's a lot to gain in terms of returns by not doing that.

Ted: 00:55:41 How far along are you in this business?

Dan: 00:55:44 Not that far.

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Ted: 00:55:44 Exciting and new.

Dan: 00:55:46 Yeah, exciting and new is right. Exactly.

Ted: 00:55:50 I'm gonna turn to some closing questions, but before I do that, I'd be remissed if I didn't ask what else is exciting and new in your research?

Dan: 00:55:58 Well, so my life, my professional life, has three parts. I have a research lab at Duke called the Center for Advanced Hindsight, and we mostly do research on financial decision-making for lower income ... middle to lower income, trying to help people save, spend a little bit less, spend better, pay debt on time and so on. We have research on health, getting people to exercise, take their medication, sleep better and so on. Mostly in the US, some in Africa, some in Europe, and tomorrow I'm off to China. We might start something there. So that's mostly changing health habits and financial habits. That's one life.

Dan: 00:56:36 The second life I have is I have a group in Israel who is working with the Israeli government. So once a year, we meet with all the offices, almost all the offices of the government. They tell us what their big problems are, and we kind of bring the behavioral economics perspective. We go ahead, we do research, and this ranges from education to lend disputes to traffic to tax evasion. I mean, we cover the whole realm and that's amazingly exciting.

Dan: 00:57:06 And then the third life is that I have a few start-ups. And from time to time, when I think I have a good idea and nobody else is picking it up, I do it myself. So I have now a start-up that does food. We have capsules about the side of a mug, and we have a machine called Genie and within 60 to 90, sometimes two minutes, we make a healthy dish with no preservatives, no additives. It's quite amazing. And the idea is that it's food that can be prepared very quickly and eaten at the right time, that is crucial, and the right portion size. I have a company that is a health company. We created a scale with no display. A bathroom scale. We found that the display on the bathroom scale is very confusing, right? It goes up and down, it varies like ... basically, it gives you noise.

Dan: 00:58:04 So we use the same approach from Balenger Bands in finance, where you say, "If it's in one standard deviation, it's just noise, don't treat it." So we have a scale with no display and we give

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people the feedback on a five-point scale. You're just the same, nothing bad happened, congratulations. The trend is slightly worse, much worse, slightly better, much better. It's a running trend over the last three weeks, and we show that that scale actually does much better than a regular scale. First of all, because people step on the scale and they say ... on the regular scale, people just stop. It's bad news. And the second thing is that it gets people to understand the relationship between cause and effect. I started running, here's what happened. I stopped eating cheesecake, here's what happened.

Dan: 00:58:45 And then I am part of another start-up which is very important to me. We created an insurance company with no conflicts of interest. The idea was that in the regular insurance company, you have built-in conflicts of interest. So you have consumers, an insurance company, consumer pay, pay, pay, at some point the insurance company needs to pay back for some claim, and the insurance company wants not to pay back, right?

Dan: 00:59:08 You split a pie ... insurance company prefers to keep more of the pie. Not because they're bad people, just because there are conflicts of interest. And consumers know that the insurance company wants to keep more, so they exaggerate and the insurance company knows that they exaggerate, so they make it difficult. So the whole system is based on mistrust. So we decided to create an insurance company that takes a fixed amount of profit. When people sign up, they sign up around a charity. So let's say there's 1000 people that sign up around the World Wildlife Fund. They sign up around the World Wildlife Fund, they pay the insurance company, the insurance company takes a fixed amount, pays claims. And if there's money left over in the pool at the end of the year, it goes to the charity. Right?

Dan: 00:59:50 So now think about user-consumer. First of all, you say the insurance company doesn't care if they pay me or not. They're not going to make a different amount, there's no conflicts of interest. And also if you cheat, you cheat your favorite charity. So this little insurance company is called Lemonade. We started here in New York, and from the expression "If life gives you lemons, then make lemonade." And a couple of weeks after we started it, we got the first nice email. Since then, we've got many. And the email said, "You insured my apartment, somebody stole my laptop, you paid my claim but turns out, nobody stole it. I found it. I just misplaced it." And they said,

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"How do I return the money?" Since then, we've had quite a few of those.

Dan: 01:00:30 And for me, this is a great story because it says if you create a company that is built on trust and you build trust in the mechanism of the company, the DNA of how its structured, you don't just tell people "Trust me," you build it with trust and good things can happen. So that's basically my three lives. Just so it doesn't sound too positive, I also travel about 300 days a year in the last few years and there's some cost to that as well.

Ted: 01:01:02 All right, let's turn to some closing questions. What's your favorite hobby or activity outside of work and family?

Dan: 01:01:09 I actually don't do much outside of work and family, as I just said. But I will tell you that I am trying to experience more new things. I think inherently I gamble with my time. Not with money, but with my time. And I get to try lots of new things, so people give me a challenge or ask me to do something that I've never done before and it actually caused me some hesitation, I often try to go for it and expand my horizon. So it's not exactly a hobby, but that's the closest I have right now.

Ted: 01:01:45 What's your biggest pet peeve?

Dan: 01:01:47 I don't like arrogance. I think for me, social science is a constant exercise in experiencing how wrong I am. Right? I do lots of experiments, sometimes I predict them, sometimes I don't and I get the continuous reminder of, "Oh, I was wrong here again." And people who are overly sure in their opinions as an approach for life, that looks to me like it's not just lack of awareness, but it's a barrier for progress.

Ted: 01:02:16 What do you read that you almost never miss?

Dan: 01:02:20 So there's nothing that I read regularly, really nothing. Because so often my life is so hectic that I try to get through my email ... you know what? That's the thing, I get a ton of email, including lots of requests from kids for help with science projects? I can't tell you how many science projects I helped with over the years, and I get lots of requests from people with disability, to help them understand how life will be next. So it's not exactly the answer to your question, but I would say I always answer kids and I always answer people with disabilities. I try to answer

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everybody who writes me, but those two categories, I'm extra sensitive to.

Ted: 01:03:03 With all the travel you do, what are your favorite travel trips?

Dan: 01:03:08 For me, I have very good eye covers. I get on the plane, I put them on, I ask the air crew to not wake me up for anything. I never drink alcohol on flights, I try not to eat this terrible ... I mean, sometimes it's okay, but it's never really that exciting and I try to sleep as much as possible. The rest of the time, I used to work. And I stopped that, I stopped working on flights. I decided flight is sufficiently unappealing that now I either read fiction or listen to podcast or watch a TV series. I never watch TV outside, movie outside of that, but that's ... so I try to take the time on flights and make it either sleep or fun. And the other thing I do is that every time I land somewhere after a long flight, nothing with a couple of hours, I try first thing to go to the gym. I land, I get to a hotel, I go to the gym, then I shower.

Dan: 01:04:10 I maybe have the record for traveling with carry-on, I never take anything more than carry-on even if I'm on the road for six weeks. I always have mismatched socks. I found that if you have pairs of socks, it's always a mess. I just bought lots of socks that look very, very different from each other. And you know, if you have one brown, one blue, it might look like you're making a mistake, but if they're drastically different from each other, it's a fashion statement, it's not a mistake. So I have lots of socks that look very, very different from each other, and I just throw them in the suitcase, and that's that.

Dan: 01:04:48 The other thing that I try to do from time to time is I ... and this is ... I don't know for how many people it would work, but it works for me. I have on my website my travel schedule. So it has which city I'm going to be in every day of the year. So right now, for example, I know almost all of 2019 where I'll be on every day, and it's there, and on one hand it reduces serendipity and randomness and so on, but on the other hand what I find is that people see that I'm coming somewhere and invite me to do all kinds of interesting things. So for me, that strategy of saying, "I'm going to be in Prague on the 21st of March", is interesting. I'm saying this because this morning I got an email from somebody from Prague, and say, "Hey, I see you're coming on the 21st. Do you want to have beer?"

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Dan: 01:05:40 So it's a combination of letting the world know where I am, and encountering some interesting serendipity with work, and I think it's often really fun.

Ted: 01:05:50 What teaching from your parents has most stayed with you.

Dan: 01:05:54 My mother was very trusting. She told me that she doesn't like me to take an hour off from school here and there when I need a break, but she said when I need a whole day off, she'll write a note to the teacher and I could take the time to do something useful. So it was an interesting thing where she said, "If you need any time off let me know and as long as you use the time well, I'll let you have that." So that was, I think, this trust was something very important to me. And my father was always not just ... my father was also a very good friend. I felt I could talk to him about everything, and that the type of conversation has stayed with me with other people as well.

Ted: 01:06:41 What did you learn most from the traumatic burns injury and healing that you went through?

Dan: 01:06:49 One of the things ... didn't strike me for years but became apparent only in the last few years. You read payoff, so I write about this in the introduction, it happened only a few years ago when I was helping somebody else. And I realized the difficutly of being helpless. I realized all the parts with the pain and the challenges and removing bandages and surgery and failure and looking different, all of that was very clear throughout. But the part of helplessness and how deep it was ingrained in me, how deep it is, how difficult it is to feel that I've no power over my life, it took years for this lesson, for me to realize that and had a deep impact, very deep impact on me.

Dan: 01:07:41 And now I look at lots of cases. Poverty, illness, where people have no control. And I think about it very, very differently.

Ted: 01:07:51 All right, last one. What life lesson have you learned that you wish you knew a lot earlier in your life?

Dan: 01:07:57 Take more risks. There's a general finding that there are lucky people. And it's not that they're lucky people in the casino or stuff like that, but they're people who try more things. So you can imagine two people are playing basketball, one is waiting for something to work 100% of the time and they shoot twice and they get 100%. The other people wait to 50% chance and

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they shoot 40 times and they get 20 baskets. Which one is more successful in life? But life is also not just like basketball, because life is not a binary outcome. Almost everything we do has steps in it. And lucky people are people who try lots of things and then cut out the things that don't seem to work and continue doubling down on the things that do work. And I think, for me especially because of my injury and some of my disability, I've been a little timid in some aspects of life.

Dan: 01:08:54 And I've wished I've taken more chances earlier. So that would've been my lesson. And also, what I hope to achieve more in the years to come.

Ted: 01:09:04 Dan, this has been so much fun, I think we could probably go on and on and on, but we'll leave it there and maybe we'll check in in a bit and see how this financial risk-taking plays out for you.

Dan: 01:09:14 I'm looking forward to it.

Ted: 01:09:15 Thanks.

Dan: 01:09:15 Thank you.

Ted: 01:09:18 Thanks for listening to this episode. I hope you found a nugget or two to take away and apply in your investing and your life. If you like what you heard, please tell a friend and maybe even write a review on iTunes. You'll help others discover the show, and I thank you for it. Have a good one, and I'll see you next time.