Elon Musk, who unveiled Tesla’s Cybertruck on Nov. 21, says he does ‘zero market research,’ an audacious—and maybe reckless—strategy.


Elon Musk and the Dying Art of the Big Bet

par Featured articles licensed from The Wall Street Journal | le 4 December 2019

In the age of Big Data, Tesla’s stated approach to market research—ignoring it altogether—seems especially reckless


Sam Walker – The Wall Street Journal

The show began Nov. 21 in Los Angeles with smoke, lasers and leaping plumes of fire. Then a futuristic new electric truck rolled onstage; a fever dream of sharp angles, flat steel panels and supervillain aesthetics.

“Doesn’t look like anything else,” said Tesla Chief Executive Elon Musk, who dressed in black for the occasion.

The highlight of the whole nutty spectacle came a few minutes later when the company’s design chief hurled a steel ball at the truck’s windows to show how sturdy they were. They promptly shattered. “Oh my f—ing God,” Mr. Musk said.

Shares in Tesla fell 6.1% the following day.

It’s possible that none of this will matter when the Cybertruck goes on sale to the public, assuming it does. Mr. Musk has posted tweets suggesting that orders are pouring in, and that critics of the truck’s design are just suffering from a lack of imagination. “Nobody *expects* the Cybertruck,” he wrote.

Here’s what we do know: the most audacious thing about this vehicle isn’t the styling—it’s the way it was conceived, designed and launched. This isn’t the kind of calculated strategic move you’d expect from a $60 billion public company. It’s basically a gut hunch—a wild bet.

On Nov. 5, two weeks before the Cybertruck’s debut, Mr. Musk discussed the project in a little-noticed interview at a U.S. Air Force tech event in San Francisco. He also described Tesla’s approach to market research.

“I do zero market research whatsoever,” he said.

Let that sink in for a moment. Before introducing a completely new product aimed at cracking the truck market, the most hotly competitive and historically profitable segment of the U.S. auto industry, Tesla’s CEO said he did not deem it necessary to consult potential customers.

Ignoring market research would be a tough strategy to defend in any industrial era, but it seems especially reckless in the age of Big Data. Amazon, Apple, Google and Facebook, among others, have become behemoths by harvesting and analyzing mountains of customer data. They don’t make bets. Before making operational changes, they run experiments to determine the outcome.


In a forthcoming book, “The Power of Experiments: Decision-Making in a Data-Driven World,” Harvard professors Michael Luca and Max Bazerman show how such experiments have helped organizations from eBay to the U.K. tax authority make better decisions. By testing different strategies on a limited pool of unwitting customers before implementing them, they say, companies can eliminate guesswork and intuition and build products and processes “that better account for the many quirks of human behavior.”

Companies that manufacture things don’t always have the same luxury, of course. Tesla can’t be expected to mass-produce 10 different trucks to see which one the public prefers. But here’s the thing: Most Earthlings now carry devices in their pockets that record everything they think and do. And if that data can’t help you determine what kind of truck customers want, you can always just reach out and ask them. Companies get scores of ideas from social media, crowdsourcing platforms and online suggestion boxes.

Elon Musk’s resistance to customer research is unusual for a technology CEO, but his attitude toward management is not. Many Silicon Valley “superheroes” who’ve led companies they founded have become devoted believers in their own brilliant instincts.

“A lot of times people try to make products that they think others would love but they don’t love them themselves,” Mr. Musk said at the Nov. 5 tech event. Tesla’s approach is to start by imagining the “platonic ideal” of a car. “I find that if you do that, people will want to buy it,” he said. “If it’s compelling to you it will be compelling to others.”

As a newcomer to the truck market, where customers are often fiercely brand loyal, Tesla has every incentive to create a distinctive product that appeals to new buyers. And if the impressive specifications Mr. Musk quoted for the Cybertruck’s ground clearance, towing capacity, acceleration and entry-level price ($39,900) survive to production, styling may be less of a concern.

At the Nov. 5 event, Mr. Musk said Tesla’s new rig was designed to turn heads on the street. He described it as “an armored personnel carrier from the future.” The risk, of course, is that some people will decline to buy it for precisely the same reason. Wouldn’t it make sense to ask them?

If there’s one broad leadership lesson in this, it involves how, in the future, successful executives should allocate their time.

There’s an old saying, often attributed to Albert Einstein, that if you had an hour to solve a problem and your life depended on the outcome, you ought to spend 55 minutes thinking about the problem and five minutes implementing the solution.

In the past, most CEOs did the opposite. They cycled through product ideas to find one they were comfortable betting the farm on, then spent the majority of their time getting it built. But as data experiments become more accessible, the Einstein strategy makes more sense. If the market’s response to any solution is knowable, a leader’s emphasis needs to shift to identifying the right problem.

Some of the world’s largest companies have been animated by one compelling problem looking for an answer. If you think about it, Amazon’s entire business model was formed around a question: Shouldn’t people be able to buy anything, at any time, without leaving the house?

In his recent book “Loonshots,” Safi Bachcall tells the story of Edwin Land, the founder and former CEO of Polaroid, who is best known as the father of the instant camera. The idea came to him in 1943 as a simple question from his young daughter. After Mr. Land snapped few photos of her one day, she asked him: “Why can’t I see them now?”

Tesla was also formed around an excellent problem: Shouldn’t somebody build zero-emissions vehicles that everybody wants to drive?

If the company had stuck to that goal, it would almost certainly have conducted mountains of customer research. But somewhere along the way, I suspect, Mr. Musk and his team got sidetracked. They shifted their focus to a problem that might not be a problem outside their conference rooms. “Trucks have been the same for a very long time, like 100 years,” Mr. Musk said at the unveiling. “We wanted to try something different.”

I can’t blame Mr. Musk for wanting to be a unicorn, or thinking he is one, or even for preferring to build things that reflect his own tastes, rather than some crowdsourced consensus. History has, at times, produced genuine business visionaries whose all-in bets have changed the world. Apple’s Steve Jobs probably comes to mind.

In less than a decade, however, circumstances have changed. The volume of incoming customer data, combined with advancements in artificial intelligence and machine learning are helping businesses decode human behavior at a level that humans could never see.

Put simply, today’s geniuses study problems. Only suckers make bets.