Life-hacks, nudges and choice architecture Behavioral economics explained

24 March 2016

We all make bad decisions—but that doesn’t mean we make them for no reason. Behavioral economics aims to explain why we act the way we do, in large and small ways, and helps us better understand our family, neighbors, employees, customers—and ourselves. The goal: to put our natural irrationality to good use.


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They’re the people you study in any basic economics class. They’re really smart. They can make any kind of calculation. Never forget anything. Unemotional. No self-control problems. And they’re complete jerks. If you leave your wallet behind, they’ll take it if they think they can get away with it.

TANYA OTT: Who are these people? We’re going to tell you in a minute. Just know that you may—or may not—be one or know one.

Welcome to the Press Room, Deloitte University Press’s podcast on the issues and ideas that matter to your business today. I’m Tanya Ott, and today we’re taking a deep dive into the world of behavioral economics: the study of why individuals and organizations make the economic choices they do, from the very big, like high-speed rail systems, to the very small, like playing a game of basketball.

It’s 10 o’clock on a cool Saturday morning, and Elizabeth Markeles and her son Gabriel are shooting hoops.

ELIZABETH MARKELES: He and I usually just have competitions for who will make the most baskets.

GABRIEL MARKELES: If I make 50 goals, my dad will give me a dollar.

TANYA OTT: Elizabeth is a 35-year-old stay-at-home mom in Chelsea, Alabama. In high school, she played varsity soccer and softball. But after college and two kids—Gabriel is 9, and he’s got a 15-month-old brother—it got harder to stay in shape.

ELIZABETH MARKELES: I don’t want to get up 4:30 in the morning anymore to put that solid hour in. Nobody wants to! I tried it for a little while. I was miserable. I went to bed every night thinking about how much I didn’t want to get up at 4:30 in the morning. It kind of like controls your thoughts, a little bit too much, so I get it in when I can now.

TANYA OTT: She shoots hoops with Gabriel, uses a fitness tracker to compete against a friend, and only binges on her favorite TV shows while running on the treadmill. She makes all kinds of wagers with herself to meet her goals.

So does Daniel Reeves. When Daniel was in grad school and struggling to write his dissertation, his girlfriend Bethany created what she called the voluntary harassment program.

DANIEL REEVES: She would not talk to me until I finished a chapter. And at some point in that process, we hit upon the idea of using money: We taped a $20 bill to the mirror in the bathroom with a note on it that such-and-such had to happen or that money would get torn up—which we actually did sometimes. But mostly that actually works, and you avoid the pain of destroying money.

TANYA OTT: This life hack, as Daniel calls it, worked so well that he and Bethany built a website to track goals with friends and family. And a few years later—now married—they co-founded the website

DANIEL REEVES: Which is a quantified self-behavioral economics tool, where you pledge money to stay on track toward your goals, we send you reminders and show you graphs of your progress, and if you don’t do what you said you were going to do, we take your money!

TANYA OTT: Reeves says the most any user has ever paid for not making a goal is $810. Another website——also charges people for not making their goals. The money can go to a friend or family member they’re betting against. It can go to a charity chosen by Stickk. Or it can go to anti-charity.

JORDAN GOLDBERG: Where we take your money and send it to an organization that you hate.

TANYA OTT: Jordan Goldberg is Stickk’s CEO.

JORDAN GOLDBERG: We actually have five highly contentious issues for the anti-charity organization on each side. So we have global warming. We have gay marriage. We have gun control. We have abortion. And of course, with election season coming up, we have a conservative super PAC and a liberal super PAC.

TANYA OTT: Probably not surprisingly, those who choose the anti-charity option are much more likely to meet their goals. Underpinning all of this—from the online goal-setting betting to watching your favorite shows only while working out—are the principles of a field of study called behavioral economics. Businesses and governments are keenly interested in it these days, because it gives them insight into how we all make decisions.

But it wasn’t always so popular. Quick history lesson:

1759—Scottish philosopher Adam Smith writes The Theory of Moral Sentiments, in which he explores psychological explanations for individual behavior. A few years later, he expands on that work with The Wealth of Nations, a book that marks the beginning of classical economics—the free-market economy.

Fast forward about 150 years to 1900, when the term neoclassical economics is first coined. This idea minimizes individual psychology and focuses on the idea that people are rational and that they’ll always make the choice that maximizes utility for themselves and maximizes profits for their companies.

Fast forward another 70 or so years, to some academics starting to question this idea of perfectly rational decision making.

RICHARD THALER: I’m Richard Thaler. professor of behavioral science and economics at the Booth School of Business, University of Chicago.

TANYA OTT: Thaler is also the co-author, with Cass Sunstein of Harvard Law School, of a book called Nudge that helped push behavioral economics into the public conscience almost a decade ago. Oh—and an aside. If you saw that recent award-winning movie about the financial crisis in 2008, that was Richard Thaler at the Vegas blackjack table, explaining how mortgage-collateralized debt obligations—or CDOs—seemed like a good bet at the time.

But back to the early days of behavioral economics: the 1970s.

RICHARD THALER: Early in my teaching days, I gave a very hard exam. The average grade on the exam was 72, and the students were furious with me. I was teaching at Cornell, and Ivy League students aren’t used to getting grades with such low numbers.I had to figure out some solution to this problem. And after a few months of pondering, I decided that my next exam would be based on a maximum score of 137. And on this exam, they didn’t do quite as well percentage-wise, but the average score was well into the 90s—and they were thrilled. This is behavior that no economist would think is remotely sensible.

TANYA OTT: So basically, you were getting at the idea that humans aren’t perfectly rational. You describe Homo Economicus versus Homo Sapien. What do you mean by those two terms?

RICHARD THALER: Homo Economicus—I call them Econs for short—they’re people you study in any basic economics class. They’re really smart. They can make any kind of calculation. Never forget anything. Unemotional. No self-control problems. And they’re complete jerks. If you leave your wallet behind, they’ll take it if they think they can get away with it. These aren’t the people I know, and for the last 40 years or so, I’ve been trying to build economic models based on real people and based on the findings of real psychologists.

TANYA OTT: You started presenting this idea in the world of economics. What was the reaction you got from traditional economists?

RICHARD THALER: It varied between hostility and dismissal, with a tiny few people who thought, Oh yeah, that’s interesting. But I would say that was the tiny minority. So the first decade or so, basically I was wandering around the wilderness, and the only ones who were paying attention to me were some of my psychology friends like Daniel Kahneman.

TANYA OTT: And then after a decade, it started getting a little bit more traction? Was it just a gradual, continual chipping away at the concern, or was there a moment when something happened and people kind of went, Oh, this actually kind of makes sense?

RICHARD THALER: You know, I don’t think you can point to a single moment. I think the fact that we started finding some anomalous behavior in financial markets created a lot of attention, because the thought was these are the most efficient markets and any misbehavior would immediately get eliminated there. And then in October 1987, the stock market crashed 20 percent in a day in which there was no news, and that caused many financial economists to rethink their views about markets, because markets just aren’t supposed to fall that much when nothing happens.

TANYA OTT: Thaler and other behavioral economists couldn’t explain why the market crashed. But through a lot of research in the lab and testing it in the field, they started drawing up the psychological framework for why people routinely make bad—or maybe I should say “illogical”—economic decisions in their personal lives.

To get a taste of some of Thaler’s findings, we’re at The J Clyde, a tavern in Birmingham, Alabama, with 60 taps for craft beer. I figure this is as good a place as any to—unscientifically—recreate some of Thaler’s research.

So here’s his hypothetical: You’re sitting on the beach. It’s hot and you’ve got water, but you’re really in the mood for a beer. A friend says he’s got to buy something at the only nearby place where you can buy a beer. And he will get you a bottle of beer there. Here’s the catch:

RICHARD THALER: There were two versions of this. In one case the friend was going to a small, rundown grocery store. The other, he was going to fancy resort hotel.

TANYA OTT: You have to tell your friend how much you’re willing to pay. He’ll buy it only if the cost is equal to or less than what you say. So what do you say?

JOHN DANTZLER: I am John Dantzler. I am an academician. I’m going to pay probably more than I normally would for a beer because I’m near a resort. I’ll tell this friend of mine, because I really want this beer, the most I’m going to pay is $15. Here’s $15.

LILLA HOOD: I’m Lilla Hood. I’m 43 years old, and I’m a graphic designer. $7.50 . . . um . . . ’cause that’s as much as I want to pay for a beer. That’s why. That’s all I want to pay! $7.50’s a lot for a beer. One beer. Not a six-pack. No, one beer. No, $7.50 is all I’m doing.

TANYA OTT: What if you were not next to a rundown little market, but you were on the beach at a fancy resort, and he or she says, “I’ll go to the bar and get you a beer at the fancy resort.” How much are you willing to pay for that?

LILLA HOOD: I don’t know. Sometimes I could potentially get swayed to pay more if it’s being charged to the room, because then I don’t really realize what I paid for it.

JERRY HARTLEY: I’m Jerry Hartley… the owner of The J Clyde.

TANYA OTT: You’re willing to pay how much for that beer?

JERRY HARTLEY: With the expectation, knowing that the beer at the resort is going to be overpriced, so at a resort a bottle of beer, maybe $45.

RICHARD THALER: What you find is people are willing to pay much more for that bottle of beer even though they’re going to end up with the same bottle of beer consumed on the same beach, so what difference does it make where it came from? If you go into a fancy resort and you buy a bottle of beer, you expect that it’s going to cost a lot of money. They’re paying a lot of people and built an expensive resort and so forth and so on. And so if you have to pay $6 or $7 for a beer, you suck it up and do it. Whereas if the local store was selling beer that normally costs $1 each for $6 each, you feel like throwing a brick through their window.

TANYA OTT: Behavioral economics research—and common sense—tells us that people don’t want to feel like they’re being taken advantage of.

Another example from Thaler’s research, this time replacing beer with wine.

RICHARD THALER: So yeah, this is the good old days for Bordeaux pricing, I must say. But we asked a group of wine drinkers and collectors: Suppose they bought a bottle of wine for $20 and it was now worth $75, and they could sell it for $75. What would it feel like when they went to drank one of these bottles? And we made it multiple-choice.

TANYA OTT: Option #1: $0—I already spent the money. Option #2: $20—that’s what I paid for it. Option #3: $75—that’s what economists would say would be the right answer, because that’s what you could get for it.

RICHARD THALER: And my favorite, the mental accountant’s answer: I saved $55 by drinking this bottle, because it’s worth $75 and I only paid $20.

TANYA OTT: So back to the bar patrons. This time, a four-top: two sisters and their husbands.

SHERRY KRELL: I’m Sherry Krell, and I’m from Birmingham. I am a Hebrew and Judaic teacher at a Jewish day school. So I chose the $55, because I guess I was thinking that the value had gone up, that I was definitely drinking something better than when I purchased it for $20.

JIMMY KRELL: My wife is all about getting a bargain. And the bargain in this case is it went up to $75. So she’s thinking she made that money and that’s gonna make the wine taste that much better.

TANYA OTT: That’s Sherry’s husband Jimmy Krell. He’s a dermatologist, and he freely admits he’s more a Scotch guy than a beer or wine guy.

JIMMY KRELL: I’m like: It’s the same damn wine, and we paid for it and we own it. It’s not worth $100. It’s not worth $20. The only way that it would be worth more is if we didn’t drink it and we were going to sell it, and then you have the money to do whatever else you want with it. I think definitely it’s a $0 bottle of wine.

RICHARD THALER: The most popular answers were $0 and saving money. So these are wine drinkers that don’t think that their expensive habit actually costs them any money.

TANYA OTT: That’s because, Thaler says, the decoupling of the expense—the original $20 paid for the Bordeaux—from the actual consumption makes the drinker feel like it’s free. Apply the same mental accounting to other types of purchases—say, a time-share vacation property. Thaler says the initial purchase of a week every year at some resort feels like an investment, so the subsequent visits feel free. And it doesn’t just apply for things you pre-pay. Think of fixed-fee vacations that include meals, lodging, and recreation all in one package. Sure, it’s convenient: Pay once, get a whole lot. But if you actually looked at an itemized list of what that “whole lot” cost—piece by piece—a vacationer might get sticker shock and reconsider the whole trip.

Now, let’s go back to the bar and hear from the other wife-husband pair. What would they consider the value of that Bordeaux?

MICHELLE BEARMAN-WOLNEK: Michelle Bearman-Wolnek. I would choose $75 because I feel like that’s what it’s worth now. I feel like I made a really good investment, and if I was going to sell it that’s what I’d get for it. I would think it would be a treat because it was something really expensive versus my regular $7 to $10 range (laughs).

SETH WOLNEK: I’m Seth Wolneck. I’m a financial adviser. The bottle today is worth $75. That’s what the market is, and therefore that’s what I’m drinking, and in my business that’s exactly what we deal in every single day. The value of different assets and commodities change on a daily basis, and if I have something on my hands that on the market is worth $75, that’s what I’m drinking: $75. And enjoying it!

TANYA OTT: So Seth is the closest to a Homo Economicus that we find in the bar today. Not terribly surprising, given his day job.

SETH WOLNECK: When individuals tend to latch onto the value that they actually paid for something, that’s where, in my business, we have a lot of buyers’ remorse. In a global economy, where the prices of things are constantly moving, what you paid for something has a lot less to do with the asset or the commodity that you’re actually buying as opposed to what you do with it in the future, whether it’s a day later or it’s years later. That’s really what you’re buying into.

TANYA OTT: Let’s move out of the bar and into the lab.

JAMIE FOEHL: I’m Jamie Foehl. I’m senior applied researcher at the Center for Advanced Hindsight.

MARIEL BEASLEY: I’m Mariel Beasley, also a senior applied researcher at the Center for Advanced Hindsight.

TANYA OTT: The center is at Duke University in Durham, North Carolina. I drove up there for the day to learn about how they’re applying the concepts of behavioral economics in the lab—and in the field.

Mariel and Jamie complement each other well. Before joining the center, Mariel worked in Medicaid outreach and eligibility and got a master’s in public policy. And Jamie worked in the advertising industry for a decade. It may seem like an odd transition, but consider that advertisers have been nudging people to make choices for as long as people have been selling things. You might say they’re the original behavioral economists.

Mariel and Jamie have worked together for only two and a half years, but they seem to read each other’s minds, and they definitely finish each others sentences.

JAMIE FOEHL: We’ve shared an office. We’ve traveled to different parts of the world together.

MARIEL BEASLEY: We’re also friends, so that also makes a difference.

JAMIE FOEHL: We have brown hair. We both have glasses.

MARIEL BEASLEY: We actually almost bought the same glasses, unbeknownst to each other, which we think would only confuse people further because we also have sort of the same haircut.

JAMIE FOEHL: Well, no: I get a haircut and then Mariel copies it!

TANYA OTT: Today, we’re in a small room outfitted with camp chairs and a large futon-like couch. Jamie and Mariel sit, legs crossed and tucked underneath them, on the couch, wearing jeans and shirts that are almost interchangeable.

They talk excitedly about the work they’re doing around topics like honesty—or, rather, dishonesty.

JAMIE FOEHL: You can have training on ethics and then be asked to do something two weeks later and prove to be very unethical. Whereas if we do an intervention right before you’re in this situation we’ve created in the lab where you can be dishonest, you’re less likely to be dishonest.

TANYA OTT: So, here’s what they do: Because it’s a lab and they need to have people being dishonest right then and there, Jamie and Mariel give participants an opportunity to be honest by asking them to take a math test and then grade it and report how many they got right.

JAMIE FOEHL: And sometimes we have them throw away their paper. Sometime we actually—and this is the good one—we have them shred their test and then report to us how many they got right. What the people don’t know is that the shredder is fixed, and so they put it in and we can go back in and see how many they got right for real versus how many they reported. And we find in general people report they get six right. But look in that shredder, and they only get four. So we see lots of people cheating just a little bit.

MARIEL BEASLEY: Yeah, there are always going to be some people who are completely honest, and there’s always going to be some people that are going to cheat a lot. But actually it’s a very wide group of the population that cheats just a little bit. Most people cheat, but just enough to kind of preserve the idea that I’m not a bad person. It’s just so that that they can kind of convince themselves that they haven’t totally lied or totally cheated. So we can make up these stories to ourselves.

TANYA OTT: That’s what they did in the lab. But then they took it out into the real world.

JAMIE FOEHL: Princeton has this very, very strong honor code, and they spend a lot of time freshman week learning about it, and so what we did is: We had Princeton students do that, and then two weeks later we give them that math test that I talk about. And in one condition on the math test, they have to sign and say, “My answers on this are consistent with the honor code. I’m following the honor code.” And the other condition, they don’t have that. And what we find is that the training the two weeks before has no bearing on the differences in the result for those two groups. The group that had to sign and say the honor code—they were very honest. Whereas the other group, without the honor code, was less honest. And again, all those people had the ethics training beforehand, and that didn’t seem to make the difference as much as in-the-moment interventions. And if you think about a lot of professions, they often have like a continuing-education credit on ethics. It’s a course you do for a few days. And we find that right afterward there’s some effect, but over time it just kind of flattens out. So we think a lot about how can we get people in the moment they’re trying to make a decision to be dishonest or honest or save for retirement or not save for retirement? That’s really a place where we go in.

MARIEL BEASLEY: Just to even more emphasize this idea that the course didn’t make a difference is that we also ran this at a comparison school that has no long ethics training; they don’t even have an ethics code. And again, half of the students were asked to sign, “I will answer this according to the ethics code,” which doesn’t actually exist at that school. The other half didn’t have it. And basically, the cheating and non-cheating mirrored the same as Princeton. So that’s how we know it’s not the presence of the ethics course plus the ethics code and the signing it in the moment that makes the difference. It’s just the signing in the moment that made the difference—and the getting people to think.

We’ve done other studies where we’ve asked people to think of the Ten Commandments before taking the test. It’s doesn’t matter if they’re religious or not. It doesn’t matter how many of the Ten Commandments they know. Getting them to reflect on some sort of idea of ethics or some sort of code of ethics kind of reminds them and takes away that ability to sort of deceive ourselves about whether or not we’re cheating.

JAMIE FOEHL:It’s not the type of person that you are. It’s the environment that you’re in that tends to be the bigger driver of your behavior.

MARIEL BEASLEY:It’s very consistent with the idea of behavioral economics as a whole in that it’s not sort of these personal, deeply held personal beliefs that motivate our behavior. It’s actually environmental cues and context that really influence it.

JAMIE BEASLEY:Although that’s kind of a hard thing for some people to come to terms with, because we like to think that our actions are consistent with our views. And that just isn’t always the case.

TANYA OTT: One of Jamie and Mariel’s next projects will take them from the classroom—to the trash room.

MARIEL BEASLEY: Trash collection compliance. So, um, yeah—not a sexy topic for people, I think. But for local governments it’s hugely important, because that’s a major interface for government and citizens. And if that trash collection is not going well, that’s when citizens are most upset with government services. So some of them are receiving this extra, sort of salient sticker that will get put on top of the trashcan that is a very simple visual of how you should put your trashcan out. The tops of the trashcans have embossed arrows that show which direction they’re supposed to be in, but it’s very easy to miss that information when you’re actually rolling out your cart.

JAMIE FOEHL: Especially when you’re rolling it out the night before. It’s dark. It’s tough.

MARIEL BEASLEY:Right, so these are very bright stickers that will go right on top of the can, with three illustrations for how to put your can out. Some of them will get the sticker. Some of them will also get a letter from their trash collector that basically says, “Hi, My name’s Sam. I’m your garbage man. And it will make my job a lot easier if you do this right. Here are three steps to do this right.” So it’s using this idea of the messenger effect and the idea of an identifiable beneficiary—like, who does it impact if I don’t do this right? So let me make sure I do this right. Giving a name attached: who is picking up your garbage for you.

TANYA OTT: Life is all about choices—small ones, like whether to put the trashcan out on the curb facing the right way, and big ones, like whether or how to save for retirement. And Jim Guszcza thinks about this stuff a lot. He’s chief data scientist of Deloitte Consulting in the U.S.

JIM GUSZCZA: People just do a terrible job weighing factors. They can’t hold more than four or five factors in their mind at a certain time. They’ll weigh those factors together differently before lunch versus after lunch—literally, your blood sugar levels will influence how you weigh these factors together. And so when I started reading about all these biases that can affect the way we process information and arrive at judgments and prioritize cases, that’s what made me realize the reason why there’s such a huge need for business analytics in the business world and in public policy—it’s because decision-making is the heart of all business.

TANYA OTT: Guszcza says: Set up the choices in a way that nudges people to make the right choice—the one they would make when they’re their most rational selves—and you can help humans overcome some of their own humanness.

JIM GUSZCZA: The idea of choice architecture, the idea of nudging people, is let’s take into account the fact that the brain is set up to kind of give into temptation, be biased toward present pleasures rather than future rewards. Let’s use insights from human psychology to set up choice environments in ways that prompt people to make decisions that our future selves would be happy with. So if we all had unlimited information, unlimited processing power, unlimited self control, we’d sign up for retirement benefits; we’d always be rebalancing our portfolio; when I go shopping, I won’t be influenced by the fact that I’m hungry—I’ll buy just the right amount of food. You know, I’ll make all these right decisions. But given the fact that we really aren’t that way, rather than try to force us to be something we’re not, maybe what we can do is we can make little tweaks to our choice environment, that kind of prompt people to make better decisions. The classic example comes from Richard Thaler and his collaborator Shlomo Benartzi: If you just set up a default differently, people are more likely to follow through and save more for retirement. They call this Save More Tomorrow.

TANYA OTT: So they have to opt out instead of opting in to save for retirement—things like that?

JIM GUSZCZA: That’s right. There are two pieces to it. One is that you’re automatically enrolled, and you have a one-click option to opt out. That’s one thing. And then they came up with a more clever spin on it, which is “save more tomorrow,” which is maybe when you first take a job you don’t have a lot of money and maybe you want to save just a small amount for retirement. But 10 years from now, if you’re still at the same employer, you’re making a lot more money and you really should be maxing out your 401(k), but you just never really bothered to getting around to doing it. And the reason is that you have fill out some form, you have to figure out who to talk to, you have to gather some information. And it’s always something you can put off till tomorrow. And rationally it’s crazy. There’s no way we’d let filling out a two-page form stand in the way of being more prosperous when you retired. But in fact, that’s what happens. And so Thaler and Bernartzi came up with a brilliant idea, which is: Let’s use this inertia to a positive affect. Right now, inertia kills us, because inertia keeps us from signing up for the benefit. So they say: When you first sign up for benefits, also sign up for a scheme where every time you get a pay raise your savings for retirement goes up proportionally. Inertia now plays to your benefit, because every time you get a raise, without even doing anything, you’re saving more for retirement.

TANYA OTT: Another example would be, like, with my current employer I have a lifecycle retirement plan so it automatically readjusts based on how far I am into my career, how old I am, how far away from retirement and that sort of thing. And I just have to choose that one time when I first signed up and I said, “Oh, well, that looks smart.”

JIM GUSZCZA: Exactly. So instead of giving people hundreds of choices, give them a few choices that are smart choices based on what you know about this person. Design a smart menu of choices for this person. Make it so that they can make one decision now and things automatically adjust as time goes on.

TANYA OTT: So the basic mantra of behavior economics is, “Make it easy for people.”

JIM GUSZCZA: First, sign up for something that’s smart, and then make it that it goes on autopilot. And they can always go in there and rebalance it actively, but the idea is to make the default smart so even if you don’t go in and rebalance—or even if you don’t investigate all 100 options—you’ve made a pretty good choice. Maybe it’s not the absolute optimal choice, but it’s a better choice than if you had no help whatsoever.

TANYA OTT: Behavioral economics is playing out in interesting ways in companies and in governments. Take what’s happening in New Mexico right now. In New Mexico, if you’re laid off from your job, the Department of Workforce Solutions is where you turn. When times got tough in 2008, that phone number got a lot of use. Joy Forehand is deputy cabinet secretary of the department.

JOY FOREHAND: The Great Recession hit every state hard, with the huge layoffs and with so many people looking for work. Our little state went up to 60,000 individuals who were certifying for benefits every week, when in regular, normal economic times we’re around 12,000—so a huge jump. Huge strain on the system, and huge strain on the staff to be able to start processing things faster and to still keep high levels of accuracy and collecting the right information while being bombarded and try to serve all of the customers who had just lost their jobs.

TANYA OTT: They also had to be on the lookout for fraud and overpayments. The US Department of Labor estimates that in 2014, states made more than $5 billion in improper unemployment insurance payments. In previous years, that number was even higher. Some of it is fraudulent claims, but most is simply because unemployed people fill out paperwork incorrectly or don’t understand eligibility requirements. When that happens, the New Mexico Department of Workforce Solutions has to track down everyone who’s been overpaid and get that money back.

JOY FOREHAND: It takes a lot of staff time and a lot of resources to be able to chase and to be able to get back improper payments. And so that was one of our priorities: How do you work smarter and not harder?

TANYA OTT: To do that, Joy called Mike Greene, a data scientist with Deloitte Consulting.

MIKE GREENE: In the last few years, companies have started really wanting to analyze all of the data they’ve been collecting, since it’s gotten cheaper to have big databases and big data revolutions. And somebody finally asked: Well, why are we storing all this stuff? Can we actually get some kind of benefit out of it? Could we figure out in advance where they were paying people who were ineligible—the improper payments?

TANYA OTT: Mike and his team scoured state databases—the ones with unemployment claims, the ones with payroll taxes. They hunted for anything that might help them better understand why someone was overpaid and be able to better predict future overpayments.

MIKE GREENE: There’s no silver bullet here. It’s not like we’re able to say, okay, if we see this one thing, then that’s it—we know they’re going to cheat a little bit or not enter accurate information. But it didn’t work that way. Most people are fully honest, fully accurate with what they enter. We needed to find a combination of things. We found that we needed to use 40–50 different variables which, when all combined together, gave us a better idea that maybe this is a situation where we wanted to act.

TANYA OTT: Before we get to what the team actually did, it’s important to understand how people file for unemployment in New Mexico—and in most states around the country. Gone are the days of walking into an unemployment office, sitting down with a caseworker to explain your situation, and filling out paperwork. These days, it’s mostly done online or by calling that toll-free phone number. That means it’s easier to cheat or to just get something wrong. You can’t ask a computer screen to explain a question in more detail. Mike and Joy’s teams drilled down into the data and discovered there were certain points in time—certain screens on the computer—where users entered the most inaccurate information.

MIKE GREENE: And then we went back to the screen in the system to figure out what it looked like. What was it people were seeing, and how could you misinterpret or answer differently in that situation?

TANYA OTT: So you were actually looking at the way it was phrased on the screens they were looking at, to go: Is it a matter of somebody misinterpreting and being confused by the question, or, on the other extreme, did they consciously answer incorrectly in order to get a benefit?

MIKE GREENE: Right. And we don’t know what any individual person’s motivation was. We’re not inside anybody’s head.

TANYA OTT: So what they did is: They ran a little science experiment, testing various messages. Some people saw the old language the New Mexico’s Department of Workforce Solutions had been using for a while, and other people saw new messages.

JOY FOREHAND: To us it became: Let’s provide messaging where it has the biggest impact, where it can really affect somebody’s decision and nudge them, sway them into providing really robust information and correct information.

MIKE GREENE: The behavior did shift pretty dramatically—and, actually, pretty quickly.

TANYA OTT: Can you give me an example of a switch in wording? Is there something that stands out where it was worded this way and then you changed it and worded it that way and then got completely different results?

MIKE GREENE: The one that’s really my favorite: You file your initial claim and figure out, “Okay, I’m eligible to get paid.” Then what happens is you have to come back every week, and there are requirements so that you get your benefit check every week. You have to be actively looking for a job. If one comes up, you have to be available. There’s a series of things, and there’s basically one page with five or six points on it, and it’s the key page—you see this page every single week that you get paid for benefits. So you see this page a lot. And the first few weeks you read it, it’s kind of novel, but after that you kind of know the answers to the questions. And one of those questions in particular says, “Did you work last week?” And if you click, “No, I didn’t work,” then you go forward, and you get paid. If you click, “Yes, I did work,” then it brings up another page, and it asks you to report how much you got paid, who paid you, etc. What happens is the amount that you get paid, the amount you earned, gets deducted from your benefits. So your incentive is to click, “No, I didn’t get paid.” But that’s also easily verifiable, and that’s one of those types of overpayments that I talked about we found earlier as we were going through their data.

TANYA OTT: Essentially, the question initially said, “Did you work last week?” and somebody knew they’d have to click no in order to get their full benefits. How did the question then change?

MIKE GREENE: So this is the sort of interesting part: We didn’t actually change the wording of the question. What we wanted to do was have the experience on the page be a little bit different—but only in weeks where we thought people weren’t being, maybe, fully accurate. So let’s say you were eligible. You got your benefits. You come in for maybe a few weeks—two, three, four weeks, whatever. You’ve seen this page. You didn’t earn any money, and you honestly and accurately click, “No, I didn’t earn anything.” But then you show up the next week, and you did earn a bit of money. Well, that’s the point where you really have a chance to affect someone’s behavior, because in the back of their head they probably know that they earned some money, and they may know that question is sort of getting at that. So if by using predictive analytics, we can figure out this is the likely time and situation where we should intervene, and you click, “No, I didn’t work,” that’s when a pop-up would show up on the screen that you’ve never seen before. And in there would be a message. And one of the most effective messages that goes up there says, “Nine out of ten people in your county accurately report their earnings every week.”

TANYA OTT: That message is what behavioral economists would call social norm. You and I might call it peer pressure: Most people don’t want to be the outlier in their group. Compared to those who didn’t get that message, New Mexicans who did get that, “Nine out of 10 accurately report their earnings” message were twice as likely to go back and report new earnings. New Mexico continues to test messages and refine the way it interacts with people filing for unemployment.

And that’s what research is about, right? Figuring out how and where something is effective, and when it’s not, why not? To close out this podcast, let’s hear from some big minds and rising stars in behavioral economics about what most occupies their thoughts these days.

MICHAEL NORTON: We had this intuition . . .

TANYA OTT: That’s Michael Norton.

MICHAEL NORTON: I’m Michael Norton. I’m a professor at Harvard Business School and a psychologist by training who actually became interested in behavioral economics because I was studying social interactions and happiness, and it turns out that we need money sometimes to interact with people and be happy.

TANYA OTT: That intuition?

MICHAEL NORTON: There’s a funny thing that happens in the world, where very often people at the lower end of the social hierarchy are arguing with each other, when you might think that certain groups in the United States would kind of band together and be mad at rich people. And instead we thought, it seems sometimes there’s more conflict down at the lower end about who gets what down at the bottom of the socioeconomic spectrum. One reason that that happens is that people have this fundamental last-place aversion. It’s just this idea that no matter what else is going on in the world, humans really hate finishing in last place. And the feeling of last-place aversion we all know because when we were in grade school and people were picking for teams in gym class, that feeling that you might be the last person picked was just about the worst feeling many people experienced in their whole lives. No one likes to be last. And what we thought was maybe this relates to people’s attitudes about public policy. One reason that, for example, a lower-income group might not want an increase in the minimum wage is because that might benefit people who are below them and make them now tied for last place. So being so sensitive to being near the bottom might actually make us be opposed to policies that in the end could help us. And because we like to do lab experiments, we want to do very, very simple tests in the lab where we create socioeconomic hierarchies, put people in different ranks. I can make you in first place; I can make you in last place, and then see how you behave. And one of the things that we did was we put people in a social hierarchy, and we had people who were in second-to-last place. They’re sort of precariously hanging on to second-to-last place, but they’re in danger of falling down there at any moment. What we let these people do was, we gave them a decision. We said, “Hey, you have a dollar, and you can give this dollar to either the person who’s ahead of you in the rank or the person who’s below you, who’s in last place. Totally up to you. You can give the dollar to whoever you want.” And what we find is that when people are in second-to-last place, they’re really, really unlikely to give the dollar to the person below them when giving them that dollar makes them tied for last place. So they’d rather give it to a wealthier person than give it to the person below them, just in case they get bumped down. And they’d do anything to avoid being in last.

TANYA OTT: That is really interesting. What can businesses or companies take away from that? Or even public policy organizations or governments? How would they use that last-place aversion knowledge to change behavior in some way?

MICHAEL NORTON: One of our favorite new follow-up projects that we’re working on—this is with my college Ryan Buell at Harvard with me—is looking at last-place aversion in waiting in line. So think about a time you’ve been in a line waiting for something at any retailer. You’re the last person in line, and you just feel like an idiot because everyone is ahead of you. No one is behind you. And you’re thinking, oh, if I’d only gotten here a minute earlier. But when there’s lots of people behind you, usually you feel more okay in the line. And the reason is because you’re not in last place. And we can actually see when we go to retailers that it is the case when people are last in line, they’re much more likely to quit the line—even though sometimes people are further back in line. As long as there’s one person behind them, they’re perfectly comfortable standing in line forever.

TANYA OTT: If I was a retailer, I might consider having somebody just in street clothes that stands by and waits and gets in line last behind people.

MICHAEL NORTON: This is actually the exact experiment we’re doing now. We’re going to plant people working for us in retailers and just have them shuffle into line behind people and see if that makes people wait for longer. The other thing that retailers have done when people are near the end of the line, they’ll send a worker out to take your order. It doesn’t speed up the line at all. It barely speeds up how fast you get your drink even when you get up there. But having someone near you in the line, even though they’re working there, likely gives you the sense that you’re not so far back and likely you’re making some progress.

TANYA OTT: For 40 years, Richard Thaler has been pushing the behavioral economics research agenda. What’s got his attention for the next decade? Data ownership. He says if a company is collecting data on his purchases, then they should be willing to share it with him because it’s his data and it might help him make better decisions.

RICHARD THALER: Suppose you’re shopping for a new calling plan for you smartphone. Do you have any idea how you use your smartphone and how many calls you make, how much data you use and how many texts you send and at which times of day and how that varies? Probably not. But suppose you could download all that information with one click and with one more click send it to some website that would look at your data and look at all the plans available and say, “Well you ought to choose one of these because it would fit the way you use your smartphone best.” And that would be true in all kinds of domains. In the UK they’re starting down this path, and the first market where it’s going to come into play is in the energy market. People will be able to get the data on how they use energy and how they use that to make choices, and then we’ll get to see whether any of this matters and whether they do a good job.

TANYA OTT: Thaler’s also really interested in applying behavioral economics to education.

RICHARD THALER: I must say that so far there have not been huge breakthroughs. Economists have tried all kinds of variations of paying students, teachers, parents, what have you for good performance, and most of those efforts have failed. But there are two intriguing success stories. One, by the economist Roland Fryer at Harvard, finds that if you reward students for what economists would call “inputs,” like doing their homework, that gets better results than paying them for outputs, like good grades. And the way I interpret that is students don’t know what economists would call the production function. So they don’t know exactly how you go about getting good grades. And so by rewarding them for taking the intermediate steps, that seems to help. The other intriguing finding by some of my colleagues at the University of Chicago, they tried various versions of motivating teachers. And the one they found most effective was they created some bonus—I’m not sure exactly how much it was, but let’s say it was $5,000—at the end of the year if students met some target. Now, there were two versions of it. In one version, you got the money at the end of the year if you succeeded in the goal. In the other version, they gave you the money at the beginning of the year and said you’d have to give it back if you didn’t reach the goal. The second one worked considerably better. And that’s a nice application of this idea of loss aversion. People hate losing. And so if I’ve got that money and I’m going to have to worry all year about having to give it back, maybe that will make me work harder than the abstract idea of getting the money at the end of the year.

TANYA OTT: Wow. That’s some politically fraught territory, because it sounds an awful lot like merit pay, which has been a lightning bolt in some education realms.

RICHARD THALER: Well, it’s worse. It’s not only merit pay—it’s giving people money and then trying to take it back. So it’s not clear how practical this idea is. But the finding is interesting. I will say that this is a field where it’s been hard to make progress.

TANYA OTT: And is it hard to make progress because people are averse to experimenting on kids?

RICHARD THALER: It’s a combination of it’s a fraught political environment with parents and teachers and administrators all having competing goals and views. And we still don’t know that much about what the best way of doing things is. So there’s a lot to learn.

TANYA OTT: There is a lot to learn about behavioral economics—in the classroom, in the lab, in government and in business. And many of the people you heard in this podcast today have so much more to say. We’ve collected some of their most interesting ideas and observations, and you’ll find them on our website, In addition to all our material on behavioral economics, there’s also a huge archive with interesting thought pieces on topics like the Internet of Things, the potential of 3D printing, and new ways of thinking about organizational design. Check it out, and be sure to tell us what you think. You can tweet us @du_press and email us at

I’m Tanya Ott. Thanks for listening, and have a fantastic day!

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