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Case studies in freakish behavior at MDRT’s 2015 annual meeting

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Consider this scenario: You ask 100 of your clients to rank themselves in a survey according to their perceived tolerance for taking investment risk. Following a bear market, you revisit the survey and find out the responses don’t correlate with reality: Many of those who rated themselves as a high tolerant pulled out of stocks when the market turned stock; others who rated themselves low stayed course.

This disconnect between predicted and actual behavior — between “declared preferences” and “actual preferences” — is precisely what transpired during the economic and stock market downtown of 2007-2009. The disconnect is also a professional focus of Stephen Dubner, an award-winning author, journalist and radio and television personality. Best known for books he’s coauthored — “Freakonomics,” “SuperFreakonomics” and “Think Like a Freak” — Dubner was the featured speaker during an exclusive presentation of elite Court of the Table and Top of the Table members attending the 2015 annual meeting of the Million Dollar Round Table, in New Orleans June 14-17.

“We live in a world full of predictions by people who don’t have skin in the game,” said Dubner. “But when their predictions aren’t accurate, then we have to do two things: first, find the data that reflects what’s really going on in the world; and second, understand the incentives — financial, moral, social, among others — that people respond to.”

“If you can find data that reflects the real world, and the incentives that people really respond to, and not just what they say they’ll respond to, then you’ll do better in predicting the future,” he added.

To illustrate his point, Dubner outlined several examples highlighting the difference between perceived and actual incentives. Two focused on basic task of hygiene: hand-washing.

On average, he noted, 70 percent of men who use public restrooms wash their hands. The other 30 percent, depending on how the question is posed, will likely not admit to not washing their hands. Hence a key point of the presentation: The circumstances under which one asks a question (and, more broadly, gathers data) will determine the reliability of survey results.

The lack of hand-washing is, oddly, far more pronounced among people for whom the task is a critical part of their jobs: doctors. In U.S. hospitals, said Dubner, many of the more than 100,000 preventable deaths that take place annually could be avoided if doctors only washed their hands.

And why don’t they? A key reason, Dubner suggested, is the time and effort involved. Because they’re in close contact with patients in hospital wards throughout much of the day, they would repeatedly have to wash and dry their hands for more than 90 minutes a day to keep them sanitized. The effort involved, Dubner suggested, could represent for the doctors “an opportunity cost” — time perceived as better spent on other tasks.

For hospital administrators, however, the problem can’t be ignored. And so some institutions have endeavored to quantify the scale of the problem and find solutions.

It’s a big problem. At one hospital based on Australia, said Dubner, 73 percent of surveyed doctors reported washing their hands. The actual rate — as determined by nurses deputized to spy on the doctors — was just 9 percent.

The percentage difference brought into stark relief the importance of gathering accurate data.

“Think about your own business,” said Dubner. “If in your business three out of four people say they do something but only one 1/10 actually do it, then you are solving a different problem. “Not only is the scale of the problem different but also the nature of the problem,” he added. “That’s what real data can do. It can help you determine what problem you’re actually trying to solve.”

At Cedar-Sinai Medical Center in Los Angeles — a world class institution where good hygiene is a high priority — hand-washing among doctors was just 60 percent a few years ago. To try to boost it to 100 percent, a 20-person committee composed of the hospital’s top administrators decided to offer $10 Starbucks gift cards to doctors who were observed (again using nurses deputized to spy on them) to actually wash their hands in patients’ wardrooms.

The solution worked — for a time — this despite the fact that the financial reward was minimal compared to the hundreds of thousands of dollars the doctors earn annually in salary.

“Never underestimate the power of free,” said Dubner. “The doctors loved the free gift card so much that they never turned it down. Moreover, they started to game the system so as to acquire additional gift cards.”

The gift card program did not, however, improve the hand-washing rate over the long-term. So, after further trial-and-error and deliberation, the committee hit upon a winning formula: to display as a screen-saver on every doctor’s PC an imprint of an unwashed hand pressed into a Petri dish used to culture cells — the imprint brimming with bacteria.

The screen-saver proved remarkably successful, boosting the hand-washing rate to 100 percent. When other medical facilities in the U.S. and internationally caught wind of the initiative, said Dubner, they contacted Cedar-Sanai to learn more.

All well and good. But the program, said Dubner, could not be considered an unqualified success because of the length of time needed to arrive at a lasting solution, and because of the harm caused to patients due to bacterial contamination.

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In the absence of real data, said Dubner, the optimal way to arrive at solutions to problems or challenge is to experiment. Just as scientists conduct randomized trials of drugs — giving patients different doses or placebos under different conditions to isolate the effect of the drug — so, too, can companies benefit by testing various potential solutions to a problem.

Brian Mullaney, a successful marketing executive, did just that for one non-profit: Smile Train. The organization provides free surgery in developing countries to poor children who suffer from facial disfigurements, including cleft lips and cleft palates.

When Mullaney joined the organization, said Dubner, Smile Train was using donated funds to periodically fly U.S.-based doctors to points worldwide to perform the needed surgeries. The program was costly and inefficient: Because of their short stays in the countries affected, the doctors — most of whom traveled on their own personal time — couldn’t get to all of the children who needed the operations.

Mullaney thereafter revamped the program, using the American doctors to train physicians based in the developing countries to perform the surgeries. Upshot: Smile Train reduced surgical costs by 75 percent, enabling the non-profit to do three additional surgeries — and cut through a backlog of children on waiting lists — for every dollar raised from charitable contributions.

To boost those contributions, Mullaney instituted a second “brilliant idea:” to offer prospective donors the opportunity to contribute once to the charity, and thereafter never be bothered again by the non-profit’s direct mail solicitations.

This “once-and-done” contribution was offered as one of several options in a direct mail letter to donors; the others included options to (2) contribute and received subsequent correspondence on a limited basis; and (3) receive correspondence on an unlimited basis.

Result? The people who received the once-and-done solicitation gave more money than did recipients of any of the other direct mail piece: about $56 on average versus $50 on average. The response rate was double that of other direct mail letters sent by Smile Train.

“Here’s the remarkable thing: Most of the people who received the once-and-done direct mail piece gave more money and they wanted to be contacted again,” said Dubner. “Smile Train raised more money from more people, who ended up giving more money longer — all by being told that they didn’t have to hear from Smile Train again.

“This outcome was the exactly the opposite of what everyone would have predicted,” he added.

Dubner attributed the achievement of the direct mail campaign to several factors, including the letter’s candor, novelty and, most importantly, its success in altering the relationship between the charity and its donors.

“What Brian Mullaney did that was so brilliant and subtle was that he changed the framework of the relationship between the charity and the potential donors from an essentially financial framework — buying a good feeling by having given money to repair the faces of disfigured children — to a collaborative one,” he said. “In a collaborative framework, both parties in the relationship — the charity and the potential donors — could avoid the hassle of 18 solicitations per year by availing donors of, and the charity agreeing to, a once-and-done option.”

Dubner added that all professionals, whatever their field, could do better by finding the data that reflects how people respond to incentives and by discovering incentives that really make people behave in desired ways. “It’s great to feel that you are doing good and well for yourself and your family,” he said in closing. “It’s better to know that you really are doing good and well.

“And that really is the magic formula,” he added. “If you try to apply a little bit of this in your profession, you might make some real progress.”

Check out all of our coverage of MDRT 2015 here.

See also:

3 peeks inside your health prospects’ brains

Three ways to leverage predictive insights to reach millennials