The Undoing Project Shows How Bias Can Best Even Data-Driven Marketers

Michael Krauss
Marketing News
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Key Takeaways

​What? Our natural decision-making processes can bias our choices.

So what? Marketers must be wary of their bias when presented with data that contradicts it.

Now what? Make sure you are not ignoring the facts in your data just because your inclinations or instincts may contradict them.

​Feb. 2, 2017
 

The author of Moneyball presents marketers with a challenge to check their bias in decision-making

 

What makes a great data-driven marketing leader?

Some say you need knowledge and expertise of cutting-edge computer hardware, state-of-the-art software and facility with the most advanced statistical techniques.

After reading Michael Lewis’ newest book, The Undoing Project, a Friendship That Changed Our Minds, I’m convinced the most important thing we marketers must understand is how the mental rules of thumb—or heuristics—we use when making decisions can bias our decision-making.

We may think we are highly rational, left brain-leaning and deeply knowledgeable in statistical methods. Yet, as The Undoing Project explains, we consistently and systematically make errors in judgment and decision-making.

If you’ve not heard of the “representativeness heuristic” or the “availability heuristic” or the idea of “anchoring” and how they influence us, even the best data-mining algorithms may not advance your marketing aims.

What Lewis has written is an entertaining and educational book that describes the lives and academic work of two Israeli psychologists, Daniel Kahneman and Amos Tversky. 

Lewis’ storytelling is remarkable in bringing to life and making relevant a series of highly complex concepts that govern our decision-making.

He simultaneously provides the reader with a powerful biography of the psychologists and case illustrations from the worlds of sport and medicine that manifest the impact of their groundbreaking research. 

The Undoing Project is a fun-to-read book that even the marketer with only a casual interest in data analytics will find hard to put down. For those interested in delving deeper, Lewis has provided a series of references and citations sufficient to power the motivated reader to become an expert in the mind’s influence on decision-making. 

 

NEW YORK, NY - NOVEMBER 23: (L-R) Director Adam McKay, author Michael Lewis and actor Brad Pitt attend 'The Big Short' New York premiere at Ziegfeld Theater on November 23, 2015 in New York City. (Photo by Astrid Stawiarz/Getty Images)


How it Begins: Professional Sports and Analytics

The book begins where Lewis’ 2003 best-seller, Moneyball, left off.

In Moneyball, Lewis explored how Oakland A’s general manager Billy Beane revolutionized baseball by applying data and analytics to the game.

In The Undoing Project, Lewis shows how Kahneman and Tversky’s ideas are transforming the practice of medicine, modern finance, economics, professional sports and, of course, marketing.

Lewis begins by describing the journey of a committed data and analytics pioneer: Daryl Morey. The general manager of the Houston Rockets, Morey is a self-proclaimed geek who sought, with some success, to build an analytics engine to improve player screening and recruiting for his NBA team.

“Morey’s job was to replace one form of decision-making, which relied upon the intuition of basketball experts, with another, which relied mainly on the analysis of data,” Lewis writes. “One of the first things Morey did after he arrived in Houston (in 2006) was to install his statistical model for predicting the future performance of basketball players.”

Morey’s analytics model improved the Rockets’ performance. “The players he’d drafted performed better than the players drafted by three quarters of the other NBA teams. His approach had been sufficiently effective that other NBA teams were adopting it,” writes Lewis. And the Rockets’ performance was consistently strong.

Yet, there were consistent and systematic errors. Poor decisions made because of the ways that our minds work. For example, in the 2007 draft, Morey’s model favored Marc Gasol, a 22-year-old, seven-foot-one-inch center playing in Europe. “The scouts had found a photograph of him playing shirtless. He was pudgy and baby-faced and had these jiggly pecs. The Rockets’ staff had given Marc Gasol a nickname: ‘Man Boobs,’ ” Lewis writes.




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Morey chose not to draft Gasol, who went on to become a two-time NBA All-Star. Morey said, “I made a new rule right then. I banned nicknames.”

The problem, we learn from Lewis, is a tendency that Tversky and Kahneman called “representativeness” in thir article, “Judgment under Uncertainty: Heuristics and Biases,” published in Science in 1974 and one of the most often-cited academic papers of all time. 

The same phenomenon that caused the Rockets to pass on Gasol was true of Harvard basketball player, Jeremy Lin. “He lit up our model,” said Morey.

The problem was, “The objective measurement of Jeremy Lin didn’t square with what the experts saw when they watched him play: a not terribly athletic Asian kid,” reports Lewis.

“At the bottom of the transformation in decision-making in professional sports—but not only in professional sports—were ideas about the human mind and how it functioned when faced with uncertain situations,” writes Lewis.

Despite the fact that the Houston Rockets and Morey were writing the book on applied analytics in basketball they were making systematic errors. And they are not alone.

Lewis describes the impact Tversky and Kahneman’s article had on a young high school student named Don Redelmeier. Redelmeier, Lewis explains, went on to became a physician and to co-author academic papers with Tversky, including, “Discrepancy between Medical Decisions for Individual Patients and Group,” published in The New England Journal of Medicine in 1990.

“ ‘Watch any NBA game,’ Tversky explained to Redelmeier, and you saw that the announcers, the fans and maybe even the coaches seemed to believe that basketball shooters had the ‘hot hand.’ Simply because some player had made his last few shots, he was thought to be more likely to make his next shot.” Lewis writes. Tversky collected data on NBA shooting streaks to see if the “hot hand” was statistically significant and found it was not.

“Tversky had the clear idea of how people misperceived randomness. […] People had incredible ability to see meaning in these patterns where none existed,” Lewis writes.

Transition: Medical Accidents and Heuristics

Today, Redelmeier is a physician at one of Toronto’s most important trauma centers, Sunnybrook Hospital. In part, his job is to check the understanding of the specialists for mental errors. Lewis shares a frightening and powerful story of how an accident victim with multiple injuries nearly died due to this decision-making phenomenon.

Lewis explains that ER doctors observed the accident victim with a wildly irregular heartbeat. Before passing out, the victim told the ER physicians she had an overactive thyroid. The treating physicians were about to administer drugs for hyperthyroidism to the patient until Redelmeier arrived in the ER.

Lewis reports that Redelmeier, “Asked everyone to slow down. To wait. Just a moment. Just to check their thinking and to make sure they were not trying to force the facts into an easy, coherent and ultimately false story.”

It turned out the patient had a collapsed lung which, if left untreated, would have killed her.

“It was a classic case of the representativeness heuristic,” said Redelmeier. “You need to be so careful when there is one simple diagnosis that instantly pops into your mind that beautifully explains everything at once. That’s when you need to stop and check your thinking.”

If that story moves you as a marketer, you should read Lewis’ The Undoing Project.

You might follow that with a reading of Daniel Kahneman’s 2011 best-seller, Thinking, Fast and Slow. Then you might want to proceed to the other academic journal articles described by Lewis in his book.

Reading The Undoing Project, you’ll realize the biggest challenge we have as decision-making marketers is our own human fallibility, not our capacity to process and analyze the data. 


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Author Bio:

 
Michael Krauss
Krauss is president of Market Strategy Group based in Chicago.
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