Transcript: How Dan Ariely Applies Behavioral Economics to Investing

Dan Ariely is one of the most famous behavioral economists in the world. And in his latest act, he's attempted to apply his research to investing. His five-year-old firm Irrational Capital searches out companies that foster human capital: the belief that companies which do a better job of nurturing their employees see stock market outperformance. You can find the episode here. Transcripts have been lightly edited for clarity.

Joe Weisenthal:
Hello, welcome to another episode of the Odd Lots podcast. I'm Joe Weisenthal.

Tracy Alloway: 
And I'm Tracy Alloway.

Joe: 
So Tracy, something I've noticed before is we talk about ESG investing sometimes. And of course, as we've discussed in the past, you know, it's become this huge industry. The thing that I always think about in ESG is the ‘E’ — the environment. There is a lot of talk about climate and so forth. And it really is like, I don't really know anything about what the ‘S’ or the ‘G’ are all about.

Tracy: 
Yeah. That would be the social governance part of the equation. And it's absolutely true. When you think about the ESG space, most of the action tends to be on doing things to combat climate change. There's quite a bit, but not as much, about things like gender equality, but beyond that, the sort of social aspect you just don't hear about that much.

Joe:
Yeah, exactly right. And this sort of like connection between these social aspects and returns is always interesting. And it's always sort of one of the central questions of all the sort of ESG is how much is it about investing with one's values? People want to invest in companies where they feel comfortable with the values of the company, versus searching out sort of ESG signals that can actually deliver alpha and somehow generate higher returns?

Tracy:
Yeah, I think that's a really good way of framing it. And it's sort of unclear at this moment of time, whether or not you would expect outperformance of a good company because more people hopefully are interested in participating in a stock of a company that's doing good things. Or if the company itself is sort of outperforming because it's more conscientious on things like the environment or gender or wealth inequality and things like.

Joe:
That. Exactly right. So let's just get right into it. I'm really excited today. We're going to be talking about the ‘S’ in ESG and we have a world famous guest that I'm excited to be speaking with. We are going to be speaking with Dan Ariely. He is a famous behavioral economist at Duke University, and he is also the co-founder of a firm called Irrational Capital, it was formed five years ago. And it pursues the idea of looking at a company's human capital factor as something that could drive outperformance in an investment. So I don't even know what the human capital factor is, but I'm excited to hear Dan talk about it and what he's learned in five years. Dan, thank you so much for coming on Odd Lots!

Dan Ariely:
My pleasure. Nice to be here.

Joe: 
Well, first of all, I love the name Irrational Capital.  But I'm curious what is the founding story of this firm?

Dan: 
So the founding story is I'm a university professor. I do research on few things, but among them human motivation and, in my academic career, I've from time to time, I go to a company and I change things around. I change bonuses. I try to increase productivity, try to get people to care more about work. And my experience has been that it's always been very easy to come and improve what people do and how to increase motivation, because most companies just don't think about it very carefully. Like, you know, if you think about HR, HR is usually a function that is about legal issues. And I don't know, training modules. But it's not really a function that says let's just get the best out of people. Let's just think about how do we motivate people? How do we get people to come happy to work?

So I've been doing this for a long time and it's easy to do. And it's helpful. But when I met David [van Adelsberg], my partner, he asked me whether I think that we could also look at something broader. That instead of one company at a time, whether there's some way to look at companies, see how they treat their employees, see how the employees feel about the company and whether this could predict stock market return. And I said, I don't know. That's what academics answer. I don't know, that's the standard answer, but we can try it out. So we went on a hunt for data to see whether this hypothesis would hold up and it turns out it holds very well.

Tracy:
So can I just press you on one point, which is what exactly is the definition of human capital? What are you looking at as you undertake this exercise?

Dan: 
Yeah. So in this exercise, and there's lots of ways to think about it — you're absolutely right. In this exercise, we said, let's take everything. We can measure everything that we can have access to, and then let's see which one of those things correlate — actually predict — stock market return. And we had some theories from the beginning about what would matter and what would not, but we also gave the data and opportunity to speak. And most of the things we found are very, very consistent with what we find in social science. So for example, we find that absolute salary, levels of absolute salary, don't matter so much to outperformance in the stock market, but the perception of fairness of salary matters a lot. Right? We find that physical environment at work, things like tables, chairs, coffee don't matter so much. The sense of being appreciated matters a lot.

So when we think about human capital, we start with the academic definition of let's take everything we know about what creates motivation. And for example, I did a study in which we showed that a pizza delivered to somebody at home, can be much more motivating than a bonus. If you think about the goodwill, that results from that, right? So we've done lots of research on appreciation. So we said, hey, appreciation is really important. Let's see if we can find signals that companies that treat people in a way that they feel appreciated actually do better in the stock market. And of course our exercise is to take the human capital in company X in year one, and predict the stock market return the following year. Right? We're not trying to estimate at that moment. We're trying to say, how is this human capital going to basically translate into better procedures, better products, more innovation and so on.

So there's lots of things like that. And we have data that goes back to 2006, which we based  a lot of our analysis on, but we also went and doubled down during COVID. We studied 1,400 companies during Covid and everything we found that was important before Covid, became even more important during Covid. And the reason is, think about kids. If a kid is in the classroom, the teacher can control them to some degree, right? Sit straight, don't look at your phone and focus on this. And the same thing is true for us in the office, right? Nobody says, sit straight, but we're being seen by other people. We go to meetings, we have to focus. We can't do completely different things. All of a sudden when people work from home, the role of intrinsic motivation is increasing dramatically. And because the kind of things we test are basically the things that lead to goodwill, the things that lead to extra performance, extra motivation, the role of everything we studied has increased quite dramatically during Covid.

Joe:
So this raises the obvious question, which is with traditional factors, of course, you can look at a 10K or an earnings report with environmental factors. Increasingly companies are putting out some sort of a separate, perhaps an environmental scorecard that talks about climate and what they're doing on sustainability there. How do you gather data in a systemic way, on the types of things you're talking about, such as fairness, perception and employee appreciation.

Dan:
Yeah. So there's lots of ways to think about data. You can think about data from LinkedIn, and you can think about data from Glassdoor, and you can think about those. There are  also companies that collect surveys about how employees feel about their company. And we take all of that. And in the first few years of our endeavor of Irrational Capital, we basically said, let's just get as much data as possible and see what matters and what doesn't matter. But once we found out what matters, now we can focus. And I want to kind of give you an example of why this is so important. So think about gender equality. What an important topic, right? How important. It’s incredibly important for investors to care about gender equality? And there are two reasons. One is, you know, the moral issue. And the second one is performance. If you discriminate half of your workforce, that can't possibly be good for business.

So there is something called the SHE Index and the SHE Index counts how many women are in top positions and how many women are on the board. And if you think about what that means, the people who created this index had the thought that this is a good proxy for how a company is treating women. But if you look at the performance of the S&P P 500, compared to the SHE Index, the SHE Index is dramatically underperforming the S&P dramatically every year, systematically. Now is this because it's not a good idea to treat women equally? Of course not, but it's a proxy that doesn't really capture the essence of what it means to be equal.

In contrast, we took our data, and in our data we looked at how women feel compared to men and all kinds of things. And it turns out that the delta between women and men is incredibly important. You know, it doesn't matter so much if you're a company that treats everybody well, or everybody badly, that doesn't matter so much. It's the inequality that is very hard to get to. Because if a company treats everybody — by the way, I'm not recommending that people start treating their employees badly — but in general, it matters less if you're an equal offender, because people get used to it and that's the level in which they evaluate themselves. But if you're a woman and you feel that somebody next to you in the cubicle next to you is treated slightly better because they have a different chromosome structure, it just bothers you no end and it doesn't go away. So as an example, if we take our data set from 2006, and every year we calculate which companies are the ones that are treating their women most equal to men.

And we buy the top 20% companies every year who are doing that. And we construct a portfolio like this, that portfolio has a return of about 5.4% a year above the S&P — just adjust by looking at equality, nothing else. Saying let's just invest in the top 20% of companies who are treating women the most equal. And you compare that to the SHE Index, the SHE Index is underperforming. So it's incredibly important to actually do the research correctly and to start focusing on what's important to measure, right? In the same way that I told you, salary doesn't matter so much. Relative salary fairness in salary matters a lot. We need to figure out first, what are the things that are actually good proxies of motivation? And what are the things that we think are predictive of motivation, but really have nothing to do with it.

We found that sometimes when companies appoint women to high positions, it actually backfires. And the reason it backfires is because they make it clear in some way to the women working there, that they don't care about women issues, they’re only doing things for PR purposes. Think about the woman engineer at company X and one day the company is appointing a wonderful woman to the board. If nothing follows in terms of her daily life, she is going to basically say, this company doesn't really care. They doing things for PR, they're checking the box. That's not... So it actually creates sometimes what we call window dressing that is just for outside purposes, and then it backfires.

Tracy: 
So I love the nuance that you just described in measuring gender inequality, the difference between just counting up the number of women in leadership positions or who are on the board, versus the discrepancy in how women and men perceive that they are actually being treated. And I guess this is a topic sort of close to my heart, but I really think people should think more about it.

But in thinking about this issue, there are clearly different ways to ask the question of how do you feel the company is doing on gender equality? Does it treat men and women the same? How do you feel the company treats you? I'm curious, just on the data collection side, how do you control for different surveys that are being done by different consultancies for different firms? Cause that seems like a pretty big challenge.

Dan: 
Yeah. So first of all, we've worked with all kinds of data providers and of course it's easiest to work with one, right? Because then the consistency of the question is equal. And then when the questions are not the same, it does provide a challenge. But because a lot of these data providers work with lots of companies, there are statistical ways to try and calibrate them to each other. But we don't ask women, how do you feel women are treated? It's not about asking them explicitly about this, but it's, for example, you look at the difference between how women feel that promotions are fair versus how men feel that promotions are fair.

By the way, the same thing that is true about men and women is also true about employees versus management. If you look at the company and you say, you know, feeling appreciated ends up being important. What happens to a company — let's just take a simple case — imagine it's a five point scale. How appreciated do you feel? And let's say you have a company where the employees are at three and the management is at three and a half. Or we have a company where the employees are at four, much higher, and the management is at five. So the employees are better and the management is much better. The gap is different. Which of those companies is going to be more successful in the stock market, according to our results? It's the first one. Why? Because a lot of things are about relative happiness. Think about your own life, right? A lot of it is about where you feel compared to other people and sources of injustice are usually us compared to other people, men compared to women, women compared to men, management compared to the employees. So having a consistent strategy is very important.

And one other thing that we found incredibly important for motivation is, so I told you that feeling appreciated is one, and of course during Covid, it was harder to communicate to people that they matter, and the companies who did this did much better. But another important thing is feeling that people can make honest mistakes. And this is why it's so important. You know, think about it. Every company wants people to innovate. But some companies want people to innovate, but they also get into feel that if they'll make a mistake, they will be punished, right? They might not get promoted. They might lose something. And every time you try something different, you take a risk. So on the one hand, companies declare that they want people to take a risk. On the other hand, lots of companies behave as if people take a risk and don't succeed, they will get penalized for it. And the companies that score high on that, people feel they will be penalized if they try something new or didn't succeed, of course do much worse in the stock market.

Joe:
So, you know, you founded the firm five years ago with the intent to see if there was useful signal in searching out this data. And five years is not actually that long of a time, really, in terms of market history and what's a durable signal. And I know a lot of like approaches, they talk about the idea of out of sample data. And so you like look at something, but you want to make sure you're not getting correlation and causation backwards or something. So you need time. How do you, sort of as an investor or someone selling investment products built on this, how do you establish that what you've identified — these links between some of the survey data — is real and not just maybe a couple of years worth or something, and something that actually stand the test of time?

Dan:
So a couple of answers for this, the first one is even though we started five years ago, we were lucky enough to get data that goes more backward than that. So we have data going back to 2006. So, you know, slightly better than five years, but you know, it doesn't solve the problem in general. The other thing is that, you know, there's lots of modeling approaches out there that are kind of black box models. Our approach is not a black box model. Like I start with things that are already proven in the social science world, right? So when I looked for relative salary matters, fairness matters a lot, much more than absolute level. This is not, hey, I just discovered a feature in the data. This is based on the hypothesis that we have from lots of other sources. So, you know, it's a little bit like you create a vaccine out there, you use a lot of data about biology.

You're not doing a random model and creating a vaccine. So we have a better starting point because we start with what we know matters. We have a model of human behavior. But by the way, the reason that furniture don't matter and the social retirement benefits don't matter and health benefits — these are things that we predicted upfront. And the reason they don't matter is they just fade to the background. You know, you might be excited when you get hired by all the benefits you have, but how many days do you wake up or go to work and think about your retirement?  

Joe: 
Yeah, but I love our iced coffee here at the Bloomberg office. Every day, it's the first thing I do when I get in is I pour myself a big cup of the cold brew that we have on tap here. So I just want to say, I just want to give a shout-out to our cold brew.

Dan: 
I hope they will not listen to our show and take and take away your ice coffee. This is not my intention.

And the third thing, when you think about what's causal and correlational, you can actually look at the data. So we, as I told you, in our modeling approach, we take employees’ state of motivation in year one. And we predict, let's say in 2006, we predict the stock market in 2007. We take 2019, we predict 2020. But also it's a question of what matters. You know, when a company does well, there some things they can do better easily. They can increase employee's retirement benefit. They can buy better furniture and so on, and we see that happening, but it turns out that's not the important thing. If you look at what we found that matters, for example, the sense of feeling appreciated. That's a deep cultural thing, not easy to measure, but it's a deep cultural thing. And when companies do better financially, it doesn't necessarily mean that all of a sudden we're better at appreciating our employees. So between all of those, we do have more data than when we started. We're starting with a strong theory about what motivates you. And the date, we explore it as much as possible to see what matters and not. And we feel quite confident that it is a predictive model.

Tracy:
So Joe and I started out this conversation by talking about how the ‘E’ in ESG tends to get a lot more attention. Why do you think that is, is it a problem of data? This notion that maybe you can quantify more easil what a company is doing to reduce its carbon emissions, but quantifying what it's doing to make its employees feel a sense of wellbeing and appreciated is much more difficult?

Dan:
I think so. You know, in the same way that I told you about the SHE Index, I think we often go to the things that are easy to measure rather than the things that are important. Now let's take, let's take ‘E.’ And you mentioned it in the beginning and you basically said there are two paths for ‘E’ to be a good alpha strategy. One is more people would want that stock, so that stock will go up. That's one approach.

The second approach is saying somehow being environmental would create more motivation for employees. The employees will be more proud to work there. Well, that's actually true. We find that most of the effect of ‘E’ comes from human motivation, right? And if you can measure human motivation directly, you do much better and you can be an ‘E’ company and the employees don't know about it, and therefore you're not increasing their motivation. And you can be an environmental company and the employees could be incredibly involved and connected and feel more proud and now you get also the benefit from that.

So I look at companies as a mechanistic thing. It's an engine. It's an engine of innovation and creativity and thought and ask what fuels that engine and what creates friction? And, you know, dust, and slows it down. And bureaucracy slows it down. And people feeling connected to the company and feeling that their utility function is aligned with the company and people wanting to be part of a successful company — all of those things are, it's what fueled the machine. And from my perspective, the human capital part is to say let's just quantify that because you know, the reality is that lots of people are not happy enough at work. And it's kind of a waste partly we're investing in this strategy because it has a good alpha, but partially I think it's just kind of the moral thing to do. You know, if people come to work unhappy, everybody loses. The people are miserable. Management is miserable. Shareholders are miserable. If people come to work happy, everybody benefits, right? I can't tell you what, what it's like to work in a place that you love is just a complete transformation. Why don't we invest more in getting people to love the place that they work?

Joe:
Well, actually that raises a question. You know, you said at the very beginning that you could go into a company and without actually too much effort improve their ability to, you know, employee motivation. Could you have  a firm that took a stake in a company and then hired you as a consultant, improved employee motivation, and then got better returns?

Dan:
So absolutely yes, but I'll tell you even something else. I think when companies, when investors do due diligence on companies, I think they have to understand the human capital in that company. If you look to get a big position in a company in hoping to turn them around, and you're not getting a really good view of the human capital, you're missing something very big in your evaluation. And I know, you know, it doesn't feel as good to get numbers like 4.5 and it feels much better to get a number with a dollar sign and two decimals. But ignoring that information, I think ignores way too much in the real value of a company. So I think it's very true for any valuation of a company needs to take that into account. And then of course if you want to be activist, think about Microsoft as an example. Microsoft changed CEOs and had an amazing transformation. And if you look at that transformation, it was largely a cultural transformation, largely the transformation of how people looked at themselves, how management looked at the employees. I mean, that, that was, that was basically it. And, you know, it's been very successful.

Tracy:
Since you brought up Microsoft, I actually wanted to ask you about tech companies and maybe the difference with other firms. So one of the criticisms of the way ESG proponents go out and, you know, typically ESG will say, well, we outperformed over the past year, especially. So it proves that you should invest in ESG companies because we produce that alpha. But then a lot of people will point out in response that, well, the ESG statistics for tech look particularly good because they're not actually polluting that much. Most of what they do is intangibles. I imagine that could apply to the human capital argument as well. So tech companies would naturally be more aware and conscientious of their human capital than other companies. So I guess what I'm asking is, is that true in your research? And then secondly, how does that fit in to the alpha equation? Like, are you outperforming simply because you're buying more tech companies with a strategy that's focused on humanity?

Dan: 
So my strategy is to look at all companies and take the ones that are top on human capital and buy them. Now I do have a bias in the portfolio towards tech, but it's not fully tech and it's not close to being half tech. It moves, depending on the year, between 20% and 40%. Now, the interesting thing about our results that surprised me, I have to say was that we didn't find a reason to create a different model in different sectors. So you would say something like in manufacturing, you could say, oh, in manufacturing, how important is it to be appreciated? Turns out to be just the same. And since, since we got that result, I understand that phenomenon much better.

But even think about something like Target and Walmart. There was recently a study that asked what happens when a customer shows up and there’s something that is out of stock and they asked one of the salespeople to, to check if it's in the backroom, if they still have it, it turns out that at Walmart, they never check. You know, they're just not that motivated. And in Target, they go and check and they often find it. Now this is, it's not Google or Amazon, but goodwill is incredibly important. So we find that our model of saying, you know, what's important is to feel appreciated and you can make honest mistakes and you feel connected to the company and all the things that you find that promotion is fair. We find that all of those things are equal across the different sectors. And we also find that they are important across the rank within the company. So to answer your question, I think, yes, we are slightly heavy on tech compared to a sector neutral strategy. Of course, we can also have a sector, neutral strategy. We don't think that's the right thing to do, but you can do it. But it doesn't only hold for tech company. It holds for everybody equally, as far as we can tell.

Joe:
I mean, I guess we haven't talked, what are the results? Like what, what have you seen? What do you anticipate getting, what have you gotten? What does the data show in terms of making money?

Dan: 
So the historical return that we have is slightly more than 7% just by looking at human capital, right? So by the way, this is a pure strategy, but of course, if you want to do, you could combine it with other things, but it's important for us to prove like, how is just this one signal? What is this one signal worth? And from 2006, it's about about 7% over the S&P, but the things that are important underneath it is the things that I told you about, right? It's a lot about fairness. It's a lot about being appreciated, that there was another interesting factor that became more important, which we call inclusive innovation and inclusive innovation is how many voices around the table are being heard? And that was always important, but it became extra important during Covid.

And the reason is that when you sit around the physical table, the people who don't like to talk that much, still talk at some point a little bit. The social pressure is very high, but when people are on zoom, lots of people are just silent. They just basically drop off. You lose some insights, you lose some collaboration, you lose some opinions. And the companies that do better on that, find things much more important. The other thing that increased over Covid I told you was feeling appreciated. Companies, you know, it's hard to say thank you over Zoom. compared to when you're in the room. In the room, you can just tap on somebody’s shoulder. You could wink at them. On zoom, it's a little extra tough. People need to work at it harder, and some people are better at it and worse at it. And then feeling that people have a future with the company became more important. And I think it's because of this, there was so much uncertainty about what the job market would hold, what would happen to the turmoils. So that also became much more important. So CEOs that communicated and helped people understand where the company is going did did much better.

Tracy:
So since we're on the topic of what changed during Covid, I'm curious if you did any research on flexible work arrangements and the idea of companies, you know, allowing their employees to work from home as needed because that's such a hot button issue right now, there's such a big debate over whether employees feel better about being able to do that or whether or not they enjoy the camaraderie of an office environment. I'm just curious whether that came up at all.

Dan:
So yes, we studied tens of thousands of people on this question. I'll give you kind of the highlights. The first highlight is that some flexibility is good, but people should go back to the office. It's also the fact that people are not good judges of whether they should go back to the office or not. After a year or so of being away, people forget what it is to work with people. You know, people are still a little bit afraid, Covid, distance, but the things that happen in this interaction between people, you don't recognize it and appreciate it. It's hard to quantify. It's hard to quantify chit chat at the water cooler and over coffee. I think work from home is important and some of it should stay maybe a day a week. If it becomes just work, the same work you do in the office, just do it from home, that's not as valuable. People should do different work at home. The kind of thing that the home environment is more suitable for.

Companies also need to co-collaborate on this. If you have a Zoom meeting or whatever technology you use, where half the people are physical and half the people are distant, the people who are distant are second class citizens. And because of that, unless companies coordinate and say, Tuesday, the whole team can stay home, unless it's coordinated, you know, people would say, oh, I was going to stay at home, but I have this one important meeting. I'm not going to be the only one on Zoom because I have something to say, I want them to pay attention. And if I'm going, I might as well go early. I think unless companies kind of coordinate on that, it would very quickly go back to people being in the office the whole time.

So I think it's important to keep a little bit of it. It needs to be a different kind of work rather than work remotely, but do the same things. And I think companies need to put some effort into it so that the coordination allows that to stay. And I'll say one last thing. I think that people are going to be concerned when they first come back. So I have the research lab here at Duke. We're about 50 people. I'm waiting for Duke to allow us in, I'm in the office right now, but I'm the only one in the office. I'm waiting for people to come to come back. And some people are going to be concerned, right? It's been a long time. People were anxious, Covid-related kind of things. What can we do to get people to drop their concern?

And what I'm going to do is I'm going to try and get people to come, I'm going to ask people to come every day, but tell them they can come for a short time if they want to. And the reason I want this is that we learn about risk from experience and not from statistics that we read. So I want for people to have the experience of coming to the office and nothing bad happened. Come into the office, that's going to be the best medicine against fear, right? Just practice it a few times and see that nothing bad happens. And then in a few weeks, people would be relaxed. But if we tell people, oh, you know, if you don't want to come to the office, don't come to the office. We're not going to help them subside that fear as much. So I think we need the correcting experience of coming to the office, meeting people, seeing that nothing bad happened and experiencing that for a while. 

Joe: 
So I just have one more question and you kind of hinted at this when you talked about your studies of Target versus Walmart, but we've been talking a lot about the Zoom class and the people who are sort of lucky enough to have been able to do their jobs over the last year over Zoom or the people who are lucky enough to have free coffee and water coolers at work when they come back and things like that. But obviously that is not the entirety of the workforce by any stretch. And we've seen a lot of stories in the last several months about lower paid workers, companies having trouble hiring them for various reasons, which you know, economists are trying to debate. Whether it, you know, all kinds of things, lots of frustration among fast food companies and retailers, restaurants, and other sort of service labor that they can't hire. And maybe wages are part of the answer. What is your sense? Like, you know, going at that level, I'm curious if you could talk a little bit more about how strong your signals are and what your research says about hiring and keeping those workers happy and motivated, you know, in what appears to be a very competitive job market right now.

Dan: 
Yeah. So I think it boils down to giving people the sense that they are substitutable very easily and that just makes people behave this way. Right? So, so if you think about a lot of those places, think about restaurants. A lot of them make people feel that we don't need you. We need a body here, but we don't need you. And then one day somebody wakes up and the bus is late, or they don't feel as good or they have something else. And they don't feel any obligation to show up. And then they don't show up and then they feel bad about not showing up. So they don't show up again. You know, a lot of those high-frequency jobs, people don't resign, they just stop showing up. And it's a part of no commitment. They have no commitment to their team and they have no commitment to the place.

And  you want to try and create that commitment. That was true even with jails. And if you think about a place like San Quentin, you know, some, some tough jails, the moment you have team cohesiveness, people feel like they owe something to each other. By the way, that's true also for high-tech. In one of our studies, we found that people are more willing to stay late at night to help a friend than to finish their own project. Right. Because if I need to stay until 2:00 AM for my own project, you know, maybe I'll finish it another day. But if a friend is asking me to do it now, now the social pressure is higher and people are more likely to do it. The way in which our commitment to the work shows up, it's to the mission of the company. It's to the CEO, it's for direct management, but also to our fellow fellow employees. And we need to create those conditions. You can't expect that just to emerge by itself. And what so many companies are doing under the idea of kind of mass production is treating employees as mass production. Come in, here's the training, here's your badge, here's the thing. Start working. You're, you're basically, a part of an efficient process. That doesn't create loyalty. 

Tracy: 
Man, I could talk about this literally for another five hours at least, and do really, really deep dives into workplace policiesthat work the best in terms of employee satisfaction. I would love to do that, but Dan, I'm very aware that you have an appointment and so you have to go, but thank you. This was so fascinating.

Joe:
Yeah. This was great. Dan really, really appreciate you, uh, taking the time and joining us.

Dan: 
My pleasure, you know, the question of how you improve the work conditions for people is central. And I think it's one of the places where the financial markets can play a big role, right? If we only invest more in companies that treat employees better, if we make it clear what it means to treat people better. If we got people to think about it more, I think everybody could be better off

Joe: 
Great stuff, and we'll continue to watch your work. Dan Ariely. Thank you so much.

Dan:
My pleasure. Take care

Joe:
Tracy. I didn't know. This was such a huge topic for you.

Tracy:
I feel very passionately about several of these themes. I'm trying... I had to hold back quite a lot because I don't want to make the podcast about, you know, how Tracy feels about flexible work conditions. But man, as someone who works across time zones, you know, we're recording this at 9:50 PM [in Hong Kong]. I have strong opinions about flexible work.

Joe: 
Come on, just come back to New York, Tracy, come on. Then we don't have to worry about that.

Tracy:
It would make my life easier. But I got to say like, one thing I really loved about that conversation was Dan's emphasis on relative versus absolute gains, because I think so much of finance and economics, and we've spoken about this before. But so much of it is based around the idea of people acting rationally and kind of working together and saying, well, this person might, you know, if we do something, this person might get more out of it than I will, but we both benefit in one way or another. But, as Dan was saying, in the real world people often aren't that rational. In the workplace, especially, there's much more of a tendency to look at the colleagues around you and say, Hey, they're getting a better deal than me. And much more of a tendency to focus on sort of relative advantages versus what's going on absolutely at the firm.

Joe:
The firm. Yeah. I mean, that makes a lot of sense and it's definitely highly intuitive. I just want to say like, and I totally believe Dan and the data, but I still want to check back in 20 years because you know, it still seems like, obviously this is the collecting of this type of data is new. The data, the period is not that long. Even going back to say 2006 is not that long and market time. As you pointed out a lot of this may, you know, they've been overweight tech for some of this, although not radically. So I do want to have Dan back on in 20 years when we get like a really long stretch of, out of sample data to see how well it holds up, but it is fascinating. And if you could sort of capture it with the numbers, it's intuitive.

Tracy:
That's the other big takeaway from this, right. Is how much of it depends on how you're measuring it, the strength of the data, whether or not it actually bears out over a longer time period. And that's basically the reason that so far there's been this emphasis on the ‘E’ in ESG and not so much on the social governance side. So maybe that's starting to change and maybe we're going to see more rigorous collection of social and human capital-related data, but we are in the early days. That's very true.

Joe:
Exactly. Right.

Tracy:
Shall we leave it there?

Joe:
Sure. Let's leave it there.

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