The whole point of PeopleScience is to discuss how behavioral science research can impact real-world organizations. As a whole, the content we post is designed to be a conversation among academics, industry and informed observers about just that.

Sometimes, though, it’s better to just get everyone together in a room and have the conversation like real human beings.

That’s what we did here. And we didn’t just pull some random panelists off the street, we got the leaders in their fields.

Dan Ariely ("Predictably Irrational," Duke University, Lemonade, Common Cents Lab) and Charlotte Blank (chief behavioral officer of Maritz) discuss the behavioral science, practice and challenges of testing of workplace motivation and incentives.

This is a PeopleScience Table Talk at the Behavioral Marketing Summit in San Francisco, moderated by me, Jeff Kreisler (editor-in-chief of PeopleScience.com).

As before, we have video*, audio and a written transcript, so you can consume and share this content however you’d like (buttons on the left in desktop, on the bottom on mobile).

Enjoy, send feedback and thank you.

The Video*:

* In case you a) can't handle a 30-minute video and/or b) just want the Ariely, we understand, we've been there, we know you can do better... but we made these short Ariely-centric YouTube clips for you anyway:

The Audio:

The Transcript:

Jeff Kreisler: What I think is great about this particular panel is that today, many times many speakers have mentioned this idea of how do we translate between academics, between the principles and the practice. Academia to industry. And in many ways, that’s what we have right here on stage: Dan, representing academia, and Charlotte, representing practice in industry. Of course, they’ve crossed over some, but I think their unique perspective will be informative for everyone here that wants to go forward and influence change using these principles in their own practice and their own business.

One thing that I think has come across this entire day is it seems like most of the interventions we’ve talked about, and whether it’s been case studies or perspective ideas, have been outward facing. How do we impact clients and consumers and people who want to have better health, financial health and physical health? A question for me has been, especially since I’ve begun working with Maritz, what about organization? Instead of looking outward, looking inward. Looking to their employees and their workforce and their own organizations, and can behavioral science have an impact there on motivation, incentives, engagement, all these other areas?

Most of the interventions we’ve talked about, whether it’s been case studies or perspectives or ideas, have been outward facing …

So, that’s what we’re going to talk about today, the principles that impact motivation, the successes and the challenges that it faces in practice, and the opportunities going forward, and what really are the tools to implement those things. And I think you’ll find it enlightening.

I’d like to begin with you, Charlotte, if you could provide for us a little context in the field of employee motivation. I know that Maritz does a lot of work in that field, and has for decades before behavioral science was really a thing. And if you could provide some foundational information for us.

Charlotte Blank: Sure. Yes. Centuries actually. Maritz is actually 124 years old. So, the gold watch for retirement, that concept was invented by Edward Maritz. That was a thing that was like commercialized.

So, the story for us, Maritz kind of does everything for everyone. We work with Fortune 100s in every industry. But the flagship really was in the sales incentive business, when back, way, way, way back we pivoted from a jewelry company to this sort of B2B concept where we were selling jewelry to companies to use as incentives and rewards to unleash the potential of your employee base or your sales channel partners. So that’s kind of the history of Maritz. And now we do a lot of other things. But really, at the core of it is a psychological understanding of enabling and motivating people to sort of do their best or bring their most to the company.

So, my sort of passion and mission is to help business leaders start to think like scientists. And I think we have a lot to learn from marketers. They’re sort of leading the way. It’s in the title of this event. For lots of reasons I think it’s sort of common practice in advertising and marketing to run experiments and to think from psychological insight. But for some reason, a lot less so in the design of incentive programs, though we spend five times as much on those than we do on advertising. Actually, as an industry, we spend $800 billion a year on incentives. So, a lot of opportunity there.

(We do a lot less experimenting) in the design of incentive programs, though we spend five times as much on those than we do on advertising.

Dan Ariely: And that’s just incentives. It doesn’t include salaries.

Charlotte Blank: Correct.

Jeff Kreisler: So, Dan, you have done a lot of work in a lot of fields. Your book “Payoff” – has anyone heard of the book “Payoff” or seen the – but it’s upstairs in the People Science Lounge. Check it out.

Dan Ariely: It’s a little bit depressing. Like the first chapter – if you don’t read the rest, keep the first chapter.

Jeff Kreisler: Why is it depressing?

Dan Ariely: Just sad.

Jeff Kreisler: You do a fantastic job of managing expectations for your own intellectual work. Let’s not discuss sadness just yet.

Could you tell us a little bit about some of the principles that you think have the greatest potential to apply in this field that maybe people haven’t yet done, or maybe you’ve experimented with?

Dan Ariely: So, the first observation I want to make is I want us to think for a second about the gap or the range between the minimum amount that we have to do to keep our jobs so nobody fires us and the max we could do if we really care. And let’s call that goodwill.

I think it’s quite clear that goodwill is increasing. If we worked in a manual labor job and we had to rearrange the chairs here or take them out, what’s the range between the minimum we have to do and the max we could do? As we move to the information age and we can sit at our desk and play with Twitter or we could be at home and work and we can represent ourselves to other people by thinking about our job, this gap is incredible. This range is incredible. It’s only growing. It’s only growing. And we’re really lucky and fortunate. Not everybody in the world has it. But a lot of the things we think about, this range is large, incredible and increasing, and it’s all up to us to either not shrink it or hopefully increase it. So, that’s the first thing.

Think about the gap between the minimum amount that we have to do to keep our jobs so nobody fires us and the max we could do if we really care.

The second thing I want us to think about is this phrase that we have the right to pursue happiness. I actually think it’s a shame that we wrote it in – that it’s written in. I think happiness is the wrong goal for humanity. I’m not against happiness, but if you think about momentary happiness and you say life is about sitting on a beach drinking mojitos, that’s kind of nice for a few days a year, but you don’t want the life of that. And if you think about the things that actually make us fulfilled, most of them don’t have happiness in them. I’m trying to be sad again. Anybody here ever run a marathon? A few? OK. I never did, but I watched some people who run marathons.

Jeff Kreisler: While drinking margaritas on a beach.

Dan Ariely: And they don’t seem happy. They don’t seem happy. If you came from outer space and you saw people who are running marathons, you would say, these people did something terrible. They did something terrible and now society is punishing them in this really cruel way, they’re experiencing lots of pain, lots of misery. Hopefully, they’ll forgive them and they’ll never behave badly again. Because it is more painful.

There’s no question that being in jail – like if you took people and you say which one is more painful. I cannot – it’s just terrible. Now, of course, it’s not the whole picture. Because even though it’s physically terrible, it gives people lots of other things. Like, nobody smiles, but it gives people a sense of purpose and meaning and competition and camaraderie and history to 2,000 years back of when people started running this particular distance. It’s really an amazingly meaningful experience, just not about happiness.

And I think that a lot of the things that we are trying to optimize in our lives, also the life of companies, are misguided to happiness rather than to meaning. And I think that a lot of times we’re actually sacrificing meaning for cheap happiness rather than doing something. And as we move more into the information age, we could do more of that.

A lot of the things that we are trying to optimize in our lives, also the life of companies, are misguided to happiness rather than to meaning.

I’ll tell you about maybe the most recent data exercise we had with this. What I do is I usually go to one company and I change something. I change bonuses or structure or something, and we see some improvement. What is really hard is to see whether the stock performance of that company is influenced by that. If you go to one company at a time, you know, lots of things happen. How can you find out? So, for the last few years I’ve been really interested in trying to get data about the productivity of companies.

So, I finally got the dataset, took a long time, and the dataset describes hundreds of companies going back to 2006. And basically, twice a year I have a snapshot of almost 100 dimensions of human capital. And you can think about whether the company gives free coffee or not, and whether the salaries are equal between men and women, and what is the vacation policy and do people feel that they have a sense of meaning and do people have autonomy and lots of things. Almost 101 of those.

And I took each of them separately. I said, imagine we took just one. Does the company give free coffee? Not that one, but just imagine. And I said, imagine I got the first data about the quality of coffee that the company has. I got the first dataset in 2006, and I sorted the companies from the company who buys the worst coffee to the company who buys the nicest coffee. And I bought in the stock market the stocks of the companies in the top 20 percent. And I kept those stocks, invested. And then at some point I got new data and some companies popped to the top 20 and some companies drop. And if they did, I replaced the stocks. And I kept on doing this until the end of 2017. From all these hundred dimensions, all but one beats the S&P 500. Some of them by a little bit; some of them by a lot. And even the one that is a little bit behind, it’s just a tiny bit behind.

Now, just to be clear, that means that every way I could come to measure employees’ well-being is as good or better than the S&P 500. And this index, by the way, doesn’t use any financial data. I don’t look at anything about quarterly earnings. I only look at companies who treat their employees well on coffee, quality of salaries, sense of meaning and so on. And, of course, now the next exercise. This is just to tell you that all the building blocks I have are better than the S&P. And now I said, OK, let’s build a really good index.

I don’t look at quarterly earnings. I only look at companies who treat their employees well on coffee, quality of salaries, sense of meaning and so on.

So, we played for a while, and we tried to build a good index. Our good index that we came up with does 12 percent better than the S&P per year. Now, if you’re not in the stock market, 12 percent is a lot. It’s really tough to beat those indexes, and 12 percent per year is a lot. And, by the way, it’s just not on the top side, it’s also on the bottom side.

So, everything I told you now is just about the companies that treat their employees well. What are companies that treat their employees badly? That’s a really good reason to short the stock. If you short those companies, you’re really doing well as well. So, it’s not just on the upside, it’s on the downside as well.

Now you can ask the question, OK, so what things enter these dimensions, and what doesn’t? So, it turns out that quality of coffee doesn’t matter. Actually, it turns out that benefits in general don’t matter as much. And the things that matter are the things you would think matter from the beginning of the discussion. It’s a sense of purpose and autonomy. And a lot of it is about alignment.

So, for example, if you have a company and you have the management and you have the employees, and you try to make the average happy by making the management happier, that’s actually a good reason to short the stock. Because it’s not just about the average happiness, it’s about the agreement between employees and management. As these gaps become larger, it becomes a worse and worse signal. And this, of course, is because our happiness is about relativity, not about absolute. So, if you look at the people around you and some people are treated much better, then you think really miserable. It’s not about the absolute.

There’s all kinds of things like it. I’ll tell you just one last thing about this. There’s a lot of movement now to take women and put them at the top of the organization. There’s even a she index that does – that invest in companies that do that. It turns out by itself it’s a terrible strategy. If you basically – we call it window dressing. If you basically have a culture that is very unequal to women and you take and you put a couple of people on the board and maybe somebody at the C-Suite, performance of the company actually goes down. Now, if you change the culture of the company, now you’re doing well. So, it’s not putting women at the top is not a good idea, but it’s a really bad idea if it doesn’t come together with a real cultural change.

So, I think for me, the question about how do we – the thing is, if you just put – arrange tables or chairs, there’s not so much of yourself that you can bring to work. The amazing thing about the modern workplace is we can bring lots of motivations in. We can bring identity. We can bring a sense of accomplishment, and we can bring pride. There’s all kinds of things because people can take – can do it.

I think the companies who do it well are going to flourish dramatically. And the companies who don’t and have this mechanical view of flavor are the ones we should short.

The companies who do it well are going to flourish dramatically. And the companies who don’t are the ones we should short.

Jeff Kreisler: What I find fascinating about this index is that it’s a piece of data that I think a lot of people here would love to have is the ability to convince the decision-makers to try these interventions and these behavioral changes to essentially start experimentation. And a common theme that I’ve heard here –

Dan Ariely: But wait. It’s really tough. You know, we complain or you complain about companies don’t do much. It’s really tough to experiment within a company. Imagine you said, let’s put half of our employees on, you know, giving them meaningful work and not give meaningful work to the other ones. It’s very tricky. And then companies just ending up doing the same thing over and over and over. And then you hire consulting companies, and they just tell you what other people are doing. And people just equate to whatever the lowest common denominator is.

It’s really tough to experiment within a company.

Jeff Kreisler: That’s what I think one of the biggest challenges is, is how do you experiment? When you’re outward facing, you’ve got a website with a million customers, it’s easy to rearrange your buttons. But when it’s your own people, and you face these challenges like that fairness – and Charlotte, I know that you’ve been involved in a lot of different experiments. What have you seen that’s successful? How have you overcome these challenges? What has been your experience?

Charlotte Blank: I was just thinking maybe to kind of bridge the gap between the difficulty of trying something, an experiment of something so foundational and core to the culture of the company, like bifurcating your company into an A and B group, where one is like this beautiful intrinsically motivated place with the best culture in the world, and one is like a car dealership and you’re measured on your hourly sales. That’s probably unrealistic.

But when you bring in what could be consultants or this kind of world that we live in, this incentive and recognition third-party world where we’re designing these programs which are, by design, extrinsic, but there are interventions within those that you could test. That might start to complement and pull out these deeper elements of our nature. So, an example, kind of a theoretical setup, is – actually came out of this conference last year.

So, a different client – partner that we brought here is in the financial services industry and was inspired by a different talk that someone gave about prosocial behavior, and our natural, innate tendencies to be giving to others. And there’s even some, very limited, but some, evidence that in an incentive context people will perform better when given a cash bonus to spend on a teammate than a cash bonus to spend on themselves. That was shown in a randomized controlled trial at a pharmaceutical company. Now, that was a bonus. That was not what we call an incentive, which is do this, get that sort of contingent. This was after the fact I saw what you did, thanks. More like a gift.

(There is) some evidence that in an incentive context people will perform better when given a cash bonus to spend on a teammate than a cash bonus to spend on themselves.

So, now we’re curious about taking that a step further and testing whether someone would actually exert more effort and work harder to sell for the prospect of a charitable donation in their name versus a separate group of FAs who are working for the chance to win a cash to keep incentive. So that one’s in field now, don’t have results yet. But that’s the kind of thing that you could do that’s kind of a blend of the two worlds.

Dan Ariely: Yeah. And it’s a little easier to do in sales. It also is more measurable. But I think – OK. So, one way to think about experiments is experiments are really entrapment. What happens? Usually, people just behave in the world. Let’s say I’ve done lots of experiments on dishonesty. When I tried to figure out how much money people would steal with me and what condition and so on. And I could wait for people to steal money from me, but that would take a long time, so what do I do? I bring people to the lab and I organize an opportunity to steal with me at the same time.

That’s what experiments are. They’re basically trying to take the timeline of things will happen naturally and say, let’s condense it and have it happen immediately. And there’s all kinds of things we could do this way. So, for example, if you say goodwill. Let’s think about doing an intervention and then, let’s ask employees to shop on the weekend to help us paint the barn. Or we did something a while ago that we send people some energy information and then we send some undergrads to their doorsteps to sell energy efficient lightbulbs. We didn’t want to wait for them to actually do something. We wanted to tempt them to see if it happens here.

That’s what experiments are. They’re basically trying to take the timeline of things will happen naturally and say, “let’s condense it and have it happen immediately.”

So, I think there are opportunities, but you need to think what you want to measure and can you accelerate. Another thing is Zappos, a really lovely, lovely company, they give people gift certificates to give to other people on the team routinely, and they force people to do it. So, you have to do it I think once a month, to give a $25 certificate. Right? Those are easy things to measure to say, let’s create a culture where people say a little bit more thank you quicker, and then let’s create a measurement environment for something quicker, like do people care more about the company and so on.

I think you just need to be willing to do it. I will tell you that we tried an experiment with a very large company, and our dependent measure was going to see whether they would steal from the supply cabinet. So, the goal was to do something that creates goodwill, and then to put some really nice pens in the supply cabinet and people see how quickly they would disappear. We couldn’t get that going. It’s still on my list.

Charlotte Blank: That’s one of the barriers that comes up. There are a few kinds of big ones, and a big one is just kind of head in the sand. I don’t want to know that about my employees.

Jeff Kreisler: That actually was my next question. Broadly speaking, both of you in your different capacities, what have you seen to be the big barriers to getting companies to experiment, whether it’s a large or a small intervention? Is there some –

Dan Ariely: Lawyers.

Jeff Kreisler: That’s very reasonable. So, how do you overcome lawyers? How do you overcome the issue of fairness, if you have one condition where people live on the beach, and the other, they live in a cave? What are the different things that you see commonly?

Charlotte Blank: I would have said the fairness one. Like, we’ve done experiments where this – we did a big one with an auto dealership network that I’ve actually told Dan about where we tested the concept of endowment effect in paying some of the dealers up front at the beginning of the month and clawing it back versus the status quo control group of getting paid at the end of the month. Understandably, there was concern about well, these dealers pay to participate in this incentive program, we can’t just change – actually, legally we can’t just change the rules on them and give them different treatment.

So, we were able to design around that by splitting into groups A and B, running that for four months, and then reversing the condition, so now B and A. Really, we’re only analyzing the first four months, because that second four is not really a true control group because half of them are like recovering from this weird thing that just happened. But we still did it to satisfy this requirement of fairness.

Dan Ariely: So, a couple of other things. One thing is calling something an experiment, usually like it’s frightening. Pilot, much nicer. But I’ll tell you a funny version. So, one of my colleagues went to the Durham schools and wanted to do a study on the public schools, wanted to do a study of the effect of giving kids free lunch. And, of course, we wanted randomized control trials. We wanted to give half the kids, randomly assigned, half the kids to get a free lunch, half the kids not. How do you think the principal reacted? Terribly. Terribly. Just hated it. It was just offensive.

Calling something “an experiment,” usually it’s frightening. “Pilot,” much nicer.

So, we went back three months later. We showed up and he said, look, I really want to give all the kids free lunch, I just don’t have money for everybody, I only have money for half. How do you recommend that we choose? I said, let’s do random assignment. You know, it’s kind of interesting that random assignment can either look really cruel, or really just in terms of fairness.

Charlotte Blank: I know I should have taken my [indiscernible].

Dan Ariely: But I think that’s important. The other thing I would say is that we really want people to think about doing experiments for the long term, not just the short term. So, you know, if you’re going to do one experiment and that’s it and you’ll never do another experiment, maybe don’t carry it out that well and don’t have all the control condition and so on. But, if this is experiment one, and you’re going to run experiments all the time and you want to do cumulative learning, that’s a very different story. And that’s one of the things I try to get people to do is to say, how are the lessons from this going to inform the next experiment.

Because one of the things that happens in companies is, they try often to do the experiment to study 17 things together. And they say, OK, if this was the last experiment in the world, that’s perfectly fine. But if we’re going to do another one, which one are we going to do after that? And then they say, oh, it’s not going to help us at all. Say, OK, let’s scale back, let’s do something else. So, I think the long-term perspective and cumulative learning are really important.

We really want people to think about doing experiments for the long term, not just the short term.

Jeff Kreisler: Charlotte, have you found working with companies, large and small, that if you do an experiment that maybe doesn’t get the results that were anticipated, that they then shut off that valve of experimentation, or are they encouraged to try something more like Dan said, to learn from that?

Charlotte Blank: Good question. I think it can go either way, because sometimes if someone’s excited to participate in an experiment, they might have already sort of pre-committed to their expected outcome. So, it can be disappointing to have the opposite effect. But again, this same auto experiment with the loss version. That actually backfired on us. In this group – in this experiment, the loss framing condition, the sales went down for one of the key brands, and that was not what any of us expected, client included. But it was actually a really nice learning experiment for us because it was this like money slide of why you need a control group. If we didn’t have this randomized control trial, you would have missed the effect, because over this period of time overall sales are trending up. But we had carved out this special random group to test this, and in that group, sales are just kind of flat. So, not only were we able to contain the loss to this pilot test, but also, we were able to identify the effect and not have it still running where you’re still kind of losing money on the table.

Jeff Kreisler: It sounds like a lot of the challenge is finding companies that are willing to do this, for whatever reason. Because, you know, we’re in the Bay Area, there’s a lot of start-ups. I think if you’re starting from the ground up as a culture of experimentation, like an Airbnb, an Uber, Amazon, all these companies, it’s great. Where if you’re starting a product like Shapa, it’s baked in. But then, how do you get these more legacy companies, the larger industrial efforts to shift. It sounds like progress is being made, but there’s still many challenges to face.

A lot of the challenge is finding companies that are willing to experiment.

Dan Ariely: It’s very tough. So, think about like basic questions that we just don’t know. Working from home, good or bad? What kind of dosage? Is it right for – it has to have some kind of return function, but what’s good for? And people spend an unbelievable amount of time commuting in this particular area of the world, and they still think it’s worthwhile to live in San Francisco. But, you know, it’s an amazing thing, right? What will happen if you allow people to show up two hours later to work, and you save them an hour of standing on the 101? Isn’t that – and we’re not exploring any of those. It’s kind of shocking.

Jeff Kreisler: Is there then – close to our final thoughts here. Is there one area that you would love to see tested, a principle, an industry disrupted, to use a term, that you would love to see sort of explored farther that hasn’t been?

Dan Ariely: I think that – I’ll give you two answers. The first one is this whole question about work-life balance. I decided I’m not going to worry about this. Personally, a few years ago I decided it’s like work-life balance, you’re just miserable all the time. You’re at work, you think you should be home; you’re home, you think you should be at work. I’ll just work. I’m not going to worry about this, and I’m not going to feel guilty about it. It’s really amazing. It’s an amazing thing to stop worrying about work-life balance. I highly recommend it.

But I think it is a really interesting thing because it’s not that you’re forcing people to work. It’s a really interesting thing about how we’re integrating standard work in the rest of our lives and what is our hobbys and how do we do it. So, I think basically trying to figure out a model in which people are micro entrepreneurs within a company. That’s what we are, right? We’re each running our own little business and we have autonomy. The people who basically have to assemble gadgets don’t stay late and come on the weekend. They don’t have that issue. It’s the people that something has captured their imagination and so on. So, how do we figure out that part I think is important.

I think university is one interesting model. If you think about the university model, we’re professors, the people who are here at this. And the university gives us tenure. And the interesting thing about the university promotion system is that my promotion never depended on people in my university. So, the way it works is that every few years they write letters to other people in the field and they say, what do you think about Dan. And if those people think I’m good, I’m getting promoted. I don’t have to worry about local politics because I’m kind of independent. Once you get tenure, you’re really independent. So, it’s an interesting – I think it’s an extreme version of really being able to do whatever you want under the umbrella of the university.

The last story I’ll tell you is that we’re getting toward the end of the year, and every year I think about what do I give the people who work with me at the research center.

Jeff Kreisler: Money.

Dan Ariely: So, three years ago I think, I had the following gift. I asked everybody in the center, about 30 people at the time, asked everybody in the center to think about something they want to learn, not professional, but as an individual. To tell me what they want to learn, where in the world they want to learn it, up to two weeks, and I said I’ll send you there to learn that thing for two weeks on our account.

It was a really interesting gift, because it showed people that they care about them as individuals. It transitioned caring about people from saying thank you backward to saying thank you forward. And also, because everybody picked what they wanted, there was a whole year in which people were about to go on a trip, they told people, they went on the trip, they came back, they learned something. They were quite energized with this idea.

It was a really interesting gift, because it showed people that they care about them as individuals.

And it’s slightly connected to this idea of investing in people holistically and not just as – learning how to use our peers in a better way. But it’s slightly about let’s figure out what people are not doing enough for themselves and be a little bit paternalistic in terms of incentives, allow people to do things themselves that they would not feel comfortable to spend that money on something like this.

Jeff Kreisler: It also touches on the cash versus noncash incentives, which is an area that’s fascinating.

We are out of time. Charlotte, I would love to hear from you. What would you tell your fellow practitioners or hopeful practitioners who want to apply behavioral science as their key perspective?

Charlotte Blank: I’ll just leave with, don’t just do it, test it. Work with us, run experiments.

Jeff Kreisler: Thank you all very much.