SEATTLE – Even though author Michael Lewis’ books are often about complex subjects that involve a lot of data, it is never his goal to make data the main character. For Lewis, it’s always about a good story.
“I’m an art history major from Princeton,” Lewis told an overflow crowd at Tableau’s 2014 user conference in Seattle last week. “I’m attracted to characters for whom data plays a central role. One of the easy ways to get action on the page is to have a character who is disrupting their environment, and we live in an environment now where the tools that character is using to disrupt big environments are data.”
Data scientists need to see the story that the data is telling. If they cannot describe the story to their mothers, said Lewis, then they need a better understanding of what the data is telling them. This is Lewis’s litmus test: If his mother doesn’t understand what he is writing about, then he goes back to the drawing board.
“I’m explaining this so someone who has no prior knowledge can understand it,” he said. “If you take the risk of seeming stupid, you give your audience the feeling of being smart, and that’s gold.”
To illustrate this point, Lewis offered the example of a Wall Street floor trader compared with a Wall Street hedge fund manager. If you talk to the floor trader, he or she is likely to try to wow you with all the lingo that goes along with the intricacies of the profession. If you feel stupid at the end of the conversation, that was probably the intention.
By comparison, if you ask a billionaire hedge fund manager about how Wall Street works, you will walk away with a much deeper understanding because he or she is not afraid to put things in plain language that anyone can understand. They are not afraid of appearing stupid.
“The kind of people who do that are often very secure in their jobs,” said Lewis.
When interviewer Kelly Wright, vice president of Sales for Tableau, asked Lewis how he does this, Lewis said he thinks in pictures. And if he can’t explain that picture to someone who doesn’t understand the material, then he knows he doesn’t understand well enough yet either.
Lewis said he is not afraid to eliminate detail. If some piece of information is not central to the story and does not enlighten or move the story forward, then it gets cut. This can be very painful for an author, and also for a data scientist who has spent many months working on a project and has a vested interest in showing just how hard she has worked and what she has learned. But it has to be done. Without clarity, data can obfuscate instead of enlighten.
“The big challenge of storytelling – of all storytelling – is … figuring out what you can eliminate from the story,” says Lewis. “Eliminate complexity. If it’s not central to what you do, kick it out.”
So when it comes to his books, he looks for characters like Billy Beane, the general manager of Major League Baseball’s Oakland Athletics. Beane’s story is particularly interesting because baseball loves data. But what it doesn’t love is letting go of tradition. In Beane’s case, he was drafted out of high school by the New York Mets in the first round of the 1980 draft. But he never lived up to the expectations of major-league scouts, and his career in the majors was short and undistinguished.
“Billy Beane had his life screwed up because the market mis-valued him, because he looked like something he wasn’t,” said Lewis. “And what he wasn’t was an all-star baseball player. Billy Beane would have never drafted Billy Beane, but the New York Mets told him he was the best player in the world. So that makes him highly sensitive to the irrationality of the market he is in and gives him a motive to destroy it.”
Fast forward to today, and what Beane has accomplished with the Oakland A’s. Beane’s realization that he had been mischaracterized and misplaced by a system that did not understand its own numbers helped him to adopt a new way of approaching the game based on nothing but data. His data-based approach to talent evaluation has changed the game of baseball, and all of professional sports, forever.
This is an opportunity that exists in every business vertical. Dig deep into the data to find the story. And use the data to tell it. If you can do that, your work will have influence and impact, and might revolutionize an entire industry.
Now a freelance writer, in a former, not-too-distant life, Allen Bernard was the managing editor of CIOUpdate.com and numerous other technology websites. Since 2000, Allen has written, assigned, and edited thousands of articles that focus on intersection of technology and business. As well as content marketing and PR, he now writes for Data Informed and other high-quality publications. Originally from the Boston area, Allen now calls Columbus, Ohio, home. He can be reached at 614-937-2316 or email@example.com. Please follow him on Twitter at @allen_bernard1, on Google+ or on Linked In.
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