Posts Tagged ‘Choice Architecture’

Easy Undoes It

Bob Nease, PhD — Chief Scientist; Express Scripts — is a leader in the convergence of behavioral economics and healthcare; at Express Scripts, he is responsible for advancing the understanding of consumer behavior. To this end, he closely follows emerging science around human behavior and decision making, then works to develop tools and communications that help plan sponsors enable better health and value.

I had the pleasure of speaking with Prof. Brian Wansink the other day.  He’s the food genius who’s done all those funky experiments that remind me of something out of Willy Wonka (e.g., bottomless soup bowls).  Three interlocking insights came to light as we spoke.

First, Wansink’s numero uno big idea is that we eat mindlessly.  That is to say, a surprisingly large degree of our eating behaviors are driven by things of which we are flat out unaware.  (This is exactly the sort of claim that is not ripe for assessment by self reflection, because it’s pretty hard to recall things of we are unaware.)  He’s done the science, and the evidence is in his corner.

Second, Wansink has come to an interesting conclusion about our bellies when it comes to eating:

After conducting hundreds of food studies, I’m increasingly convinced that our stomach has only three settings: 1) We either feel like we’re starving, 2) we feel like we’re stuffed, or 3) we feel like we can eat more. Most of the time we’re in the middle, we’re neither hungry nor full, but if something’s put in front of us, we’ll eat it.

Stop with me for a second or two on this one.  Prof. W is telling us that when it comes to eating, we naturally have three speeds, and none of them is neutral.  Put another way, given the opportunity, we’ll eat to the point of regretting it.

The third idea relates to the first two: little things of which we’re unaware made us fat, and so little things of which we’re unaware can make us slim down as well.  Move the bread and potatoes to the kitchen counter out of reach.  Use smaller plates.  Take that jar of candy off your desk and put it on your bookshelf.  Put treats into a container that takes two hands to open.

There’s a more general design idea at work here: it’s the little foxes that spoil the grapes, but those little foxes take time to do their damage.  And it’s those same little foxes - given time - that can make us healthier and happier.  What are a few little things you can do to make the good behaviors easier and the bad ones just a bit more difficult?

Taxi Interrupted

Bob Nease, PhD — Chief Scientist; Express Scripts — is a leader in the convergence of behavioral economics and healthcare; at Express Scripts, he is responsible for advancing the understanding of consumer behavior. To this end, he closely follows emerging science around human behavior and decision making, then works to develop tools and communications that help plan sponsors enable better health and value.

The New York Times reports on the effect of choice architecture on tips for taxi drivers:

The increase in tips, however, may have less to do with New Yorkers’ generosity than with the preset amounts suggested to passengers on the taxi’s software systems. In many of the city’s cabs, riders are offered options for their tip depending on the length of the ride. For fares under $15, a screen prompts tips of $2, $3 or $4; the numbers can range from 15 percent to 30 percent for higher fares. The presets are used about 70 percent of the time, according to industry estimates.

For the full story, click here.

Dan Ariely vs. Tim Harford… vs. Me

Bob Nease, PhD — Chief Scientist; Express Scripts — is a leader in the convergence of behavioral economics and healthcare; at Express Scripts, he is responsible for advancing the understanding of consumer behavior. To this end, he closely follows emerging science around human behavior and decision making, then works to develop tools and communications that help plan sponsors enable better health and value.

The single most important insight for me about human behavior is that the brain — as with every other organ in the human body — is the result of evolution over a very long period of time.  Although not every behavior is driven by how we’re wired, the implications of the brain as an evolved organ are frequently overlooked.

One of these implications is that our brains are laggy.  That is, our environment and our wiring have been changing at different speeds, with the former charging ahead much more quickly than the latter.  Part of this is due to the inherently slow tempo of evolution: sex and survival advantages accrue across generations.  But perhaps the greater contributor to our brains’ lagginess is the profound change in our environment over an extremely short period of time.

According to Gregory Clark in A Farewell to Alms, our standard of living remained stuck in a rut until about 1800, and life expectancy was about 30 to 35 years for our hunter-gatherer ancestors… and remained unchanged until about 1800.  Nutritional challenges stunted growth as well; the average height of men from AD 1 to about AD 1800 was stuck at roughly 5′8″.  But after the Industrial Revolution, the average male got about three inches taller.

In other words, until about 1800, life was short and so were we. 

But since then — in fewer than eight generations — per capita incomes haverisen tenfold.  Better nutrition means better health.  We live longer.  We’ve grown taller.  (I’d personally like to think I’ve become more distinguished looking.)

And yet our brains are in way “stuck” in a place very long ago and very far away.  We’re still wired to throw and catch — skills that were life-sustaining back there and then — with amazing accuracy, and without having to solve nasty and complex differential equations (which is what a computer would have to do to solve a similar problem).  We harbor a natural aversion to snakes and spiders, but not to electrical outlets, fast-moving traffic, or divorce lawyers.

Which leads me to comment on the most recent books by two authors I very much enjoy: Dan Ariely and Tim Harford.  In Predictably Irrational, Dan focuses on reliable ways in which our behavior is not logical; in The Logic of Life, Tim suggests that much of what appears to be irrational can be explained by looking for the right incentive.

Although Ariely and Harford are not at full-on loggerheads, they come to very different conclusions using a shared framework: rationality.  But this framework obscures a crucial point: it isn’t whether our behavior is irrational (Ariely) or rational (Harford).  It’s whether our behavior is adaptive or maladaptive.  What Dan sees as irrational behavior can also be seen as valuable behavior that’s simply out of place — a rule of thumb that worked very well in a very different environment.  And what Tim sees as rational behavior can just as easily be seen as something that works today as well as it worked when and where our brains “grew up.”

For example, bias toward the present (or hyperbolic discounting) suggests that people very steeply discount the future.  Because many desirable behaviors involve upfront costs for downstream benefits, we plan to engage in the activities when costs and benefits are both in the future and therefore equally discounted. We then have a difficult time executing on those plans because the costs loom large relative to steeply discounted future benefits.  This is, perhaps, the fundamental challenge of wellness: In the long run, we’re better off eating less, drinking less, and exercising more.  In the short run, that’s nothing but a buzzkill.

But if you step back and think about the environment of our ancestors (and I don’t mean Uncle Al), a little light begins to dawn on Marble Head.  Back then, times were tough.  What life lacked in comfort and calories, it made up for in brevity.  Back then, chances of the long run were slim to none.  So all those behaviors that seem so virtuous today — moderation, exercise, temperance — would have been worse than useless; they’d have been a waste.

The prescription to “eat, drink and be merry” might not be sound medical advice today, but it was undoubtedly good investment advice not all that long ago.  And that’s exactly the kind of environment in which our brains were shaped.

It’s not about rationality or irrationality.  It’s about what was adaptive back then and whether it’s still adaptive today.

The lesson for practicing behavioral economists is to strive for a better understanding of the heuristics and sentiments that drive our behavior in light of the environment in which our brains were most powerfully shaped, and to determine whether those remain adaptive in today’s environment.  For those that don’t, we must work hard to retool our environments — using techniques such as choice architecture — so that yesterday’s brain succeeds today.

The Password Is: “Default”

As an editor for the Corporate Database team, Eric Ferguson is responsible for writing and editing strategic language for Express Scripts' Sales & Marketing department.

Each day for the past two weeks, my work computer has greeted me with the following message:

“Your password will expire in X days. Would you like to reset it now?”

My choices are “Yes” and “No.” Needless to say, my morning routine now includes clicking “No.” I will continue to do so until I absolutely must change my password. Who has the time –- literally dozens of seconds –- required to change a password? In case you haven’t heard, I’m very busy and important.

It seems to me that it would be in the best interests of corporate security if better choice architecture were employed. How about something like:

“Unless you correctly name each Teenage Mutant Ninja Turtle in alphabetical order and then list the first five R.E.M. albums in the next 10 seconds, we will require that you change your password.”

Maybe not exactly that. Maybe Primus instead of R.E.M.

Behavioral Economics and the Health Insurance Mandate

Julie Adelsberger — Senior Manager; Express Scripts — As senior manager of knowledge management, Julie Adelsberger is responsible for translating scientific research into accessible communications for plan sponsors and other healthcare stakeholders.

Today’s Washington Post explores whether a health insurance mandate is likely to succeed:

[T]he question of whether people will follow a government order that they carry health insurance — an issue that will help determine whether universal healthcare is a success or costly failure — will depend on more than the penalty they would pay for refusing, many economists say. This, they say, is the lesson of behavioral economics, a school of thought that holds that people do not necessarily make decisions out of well-reasoned self-interest. It is an approach that has gained a powerful foothold in the Obama White House.

Many factors will come into play, the experts in the article say: complexity of the law, hassles associated with compliance, the program’s choice architecture, the success of social norming campaigns, and timing and severity of consequences for noncompliance.

For the full article, click here.

Now, An Organ Donor App for the iPhone

Julie Adelsberger — Senior Manager; Express Scripts — As senior manager of knowledge management, Julie Adelsberger is responsible for translating scientific research into accessible communications for plan sponsors and other healthcare stakeholders.

Bob wrote last month about Richard Thaler’s opinion piece on organ donation in The New York Times.  In that article, Thaler called on Steve Jobs, CEO of Apple, who received a lifesaving liver transplant this year:

 

The private sector could help create other simple methods [for donation registry]. Here is a challenge to Mr. Jobs: Why not create a Web site — and a free app for the iPhone — that lets people sign up as organ donors in their home states?

 

Now the Nudge blog reports that this application exists:

 

Steve Jobs didn’t meet Thaler’s challenge, but Raymond Cheung of Serenity Integration did. “Basically, I was inspired after reading Dr. Thaler’s column,” he tells the Nudge blog. So he directed his team of developers to create an iPhone app called Donate Lives that lets users identify where they live, and then takes them directly to the state web site where they can sign-up to become an organ donor.

Designing Organ Donation Programs

Bob Nease, PhD — Chief Scientist; Express Scripts — is a leader in the convergence of behavioral economics and healthcare; at Express Scripts, he is responsible for advancing the understanding of consumer behavior. To this end, he closely follows emerging science around human behavior and decision making, then works to develop tools and communications that help plan sponsors enable better health and value.

Richard Thaler, co-author of Nudge, writes an interesting piece about the behavioral economics of organ donation for The New York Times. Research has long shown that opt-in donor registration programs result in low rates of sign-up, while opt-out programs result in high rates of sign-up. But many object to the opt-out programs, believing organ donation should require explicit consent.

Fortunately, there is another possibility, called “mandated choice,” under which people must indicate their preference. In Illinois, where I live, this system has been in use since 2006 and doesn’t seem to have ruffled many feathers.

Here is how it works: When you go to renew your driver’s license and update your photograph, you are required to answer this question: “Do you wish to be an organ donor?” The state now has a 60 percent donor signup rate, according to Donate Life Illinois, a coalition of agencies. That is much higher than the national rate of 38 percent reported by Donate Life America.

What does this mean? It indicates a large degree of latent support for organ donation. That is, these results are consistent with the idea that many people want to register for organ donation but don’t because of the hassle required to do so. And this is exactly what we saw with Select Home Delivery: roughly half of people getting their maintenance medication in retail moved to Home Delivery when required to make an explicit choice (and offered assistance with the move).

Using a Stick to Save Paper

Julie Adelsberger — Senior Manager; Express Scripts — As senior manager of knowledge management, Julie Adelsberger is responsible for translating scientific research into accessible communications for plan sponsors and other healthcare stakeholders.

The New York Times reports on T-Mobile’s stick approach to converting customers to paperless billing.  The wireless company had previously taken a carrot approach, persuading customers to ditch paper via a green campaign that included a promise to plant a tree on behalf of each person who made the change.  Last month the company took a more aggressive tack, implementing a $1.50 fee for those who continue to receive paper bills.

When the $1.50 fee was added to the bills that went out in August, the number jumped to 33,000 a day, according to a spokesman. This was even before the charge really bit: for August, T-Mobile also added a matching $1.50 credit to every bill for the initial month, to give customers more time to decide whether to opt for paperless.

The company sends out 16.5 million invoices each month, but the accelerated rate of signups in August made it possible to imagine converting the entire customer base to paperless in only 15 months – and fully realize the potential annual savings of 10.8 million pounds of paper, equivalent to 13,500 trees (T-Mobile will talk only of trees to be saved, not dollars). …

T-Mobile had concluded that the “voluntary approach” was “not something that would get the majority of our customers to paperless,” said Glenn A. Zaccara, a T-Mobile spokesman. I spoke with Mr. Zaccara and David Beigie, the company’s vice president for corporate communications, on Sept. 1, when enough time had elapsed for the company to see that the paper bill fee was having the desired effect of “putting a spotlight on the costs of preparing paper bills.”

Although T-Mobile enjoyed the fee’s short-term success in converting customers to paperless billing, this mandatory approach rubbed many customers the wrong way.  Complaints mounted, and a class-action lawsuit was filed in a Missouri district court.  As a result, T-Mobile dropped the fee in mid-September and returned to the significantly less effective voluntary approach. 

This experience shows again the challenge companies face choosing between mandatory programs that achieve results and voluntary programs that don’t disrupt customers.  One of the benefits of behavioral economics is achieving those mandatory-like results without disruption.  For example, wireless companies could consider an opt-out or active choice model for paperless billing to increase its use without disrupting customers who prefer to keep traditional paper bills.

Designing for Irrational Choice

Julie Adelsberger — Senior Manager; Express Scripts — As senior manager of knowledge management, Julie Adelsberger is responsible for translating scientific research into accessible communications for plan sponsors and other healthcare stakeholders.

In a Harvard Business blog posting, John Sviokla explores the growing popularity of behavioral economics and discusses how choice architecture enables companies to drive desired behavior.  He is particularly interested in how design can counter information overload.  He writes:

Every manager should remember that in a world of excess choice, an easy place to differentiate is in the careful design of the decision process itself. It is especially powerful in the ever-increasing realm of e-commerce. Few companies have optimized their customer choice process to make the most of the web. Fewer still do regular experiments to find out how their customers really act instead of how they are supposed to act, and they are leaving money on the table because of it. So ask yourself: is your company’s choice process optimal – and do you have data to prove it?

For the full post, click here.

More Behavioral Economics at NEJM

Bob Nease, PhD — Chief Scientist; Express Scripts — is a leader in the convergence of behavioral economics and healthcare; at Express Scripts, he is responsible for advancing the understanding of consumer behavior. To this end, he closely follows emerging science around human behavior and decision making, then works to develop tools and communications that help plan sponsors enable better health and value.

One potential element of healthcare reform is the provision of insurance exchanges, an arrangement designed to allow small businesses and individuals access to more affordable health insurance.  A question arises, however, as to exactly how such an exchange should be run.  For example, should it ensure a certain level of quality and features but place no limit on the number of plans offered?  Or should it play the role most employers take, selecting a much smaller number of options from which members can choose?

In a posting at the New England Journal of Medicine’s healthcare reform section, Richard Frank and Richard Zeckhauser argue that we ought to approach this question carefully because actual human behavior falls short of the ideal in predictable ways.

As people face an increasingly large number of similar health plan choices, their tendency to switch plans to reduce their premiums is unlikely to increase and may actually decline – a consumer may be more likely to switch from 1 plan among 6 than from 1 plan among 23. A recent analysis of the Swiss health insurance experience revealed the phenomenon of “inertia due to numbers. Depending on the canton in which they lived, Swiss consumers faced the choice of 30 to 75 health plans, all meeting mandated coverage standards. Information on plans, including premium amounts, was made widely available. Under these circumstances, one might expect frequent switching and robust price competition. Instead, people who were offered more alternatives were less likely to switch plans. The result was greater price variation in markets offering more choices. The implication is that when choice sets become very large, people “leave more money on the table” – possibly because the abundance of alternatives overwhelms them or prevents them from getting enough information on an alternative plan to induce them to switch.

These sorts of data are really challenging in terms of choice architecture.  What is the optimal number of plans to offer?  Should everyone see the same N options, or should there be a mechanism to winnow down the superset of options to a more manageable number?  This sort of reminds me of real estate agents: in theory, purchasers can choose between a large number of very different houses.  But in practice, realtors do a lot of filtering – in a sense, you’re paying not to see a bunch of irrelevant options.