Great business decisions often require imagination more than data

The business world has an unhealthy obsession with data.

In both the way it’s practiced and studied, there’s an underlying belief that business decisions should be based on a rigorous analysis of data.

The explosion of big data has reinforced this idea. In a recent EY survey, 81 percent of executives said they believed that “data should be at the heart of all decision-making,” leading EY to enthusiastically proclaim that “big data can eliminate reliance on ‘gut feel’ decision-making.”

But can management decisions really be reduced to an exercise in data analysis? I do not believe that they can. Creating great choices requires imagination more than data. To understand what this means and why it is true, we need to travel back to the origins of science.

Is business a science?

What we think of as science began with Aristotle, who as a student of Plato was the first to write about cause and effect and the methodology for demonstrating it. This made “demonstration,” or proof, the goal of science and the final criterion for “truth.” As such, Aristotle developed a first approach to scientific exploration, which Galileo, Bacon, Descartes, and Newton would then formalize as “the scientific method” 2,000 years later.

It’s hard to overestimate science’s impact on society. The discoveries of the Enlightenment—deeply rooted in the Aristotelian methodology—led to the Industrial Revolution and the global economic progress that followed. Science has solved many problems and made the world a better place. Small wonder that we came to regard great scientists like Einstein as latter-day saints. And even smaller wonder that we came to view the scientific method as a template for other forms of inquiry and to speak of “social sciences” rather than “social studies.”

But Aristotle might question whether we’ve allowed our application of the scientific method to go too far. In defining his approach, he set clear boundaries around what it should be used for, which was understanding natural phenomena that “cannot be other than they are.” Why does the sun rise every day, why do lunar eclipses happen when they do, why do objects always fall to the ground? These things are beyond the control of any human, and science is the study of what makes them occur.

However, Aristotle never claimed that all events were inevitable. To the contrary, he believed in free will and the power to make choices that can radically change the future. In other words, people choose a great many things in the world that can be other than they are.

“Most of the things about which we make decisions, and into which we therefore inquire, present us with alternative possibilities,” he wrote. “All our actions have a contingent character; hardly any of them are determined by necessity.”

Aristotle believed that this realm of possibilities was driven not by scientific analysis but by human invention and persuasion.

This is particularly true when it comes to decisions about business strategy and innovation. You can’t chart a course for the future or bring about change merely by analyzing history. Customer behavior will never be transformed by a product whose design is based on an analysis of past behavior. Yet transforming customer habits and experiences is what great business innovations do.

Steve Jobs, Steve Wozniak, and other computing pioneers created a brand-new device, the personal computer, that revolutionized how people interacted and did business. The railroad, the motor car, and the telephone all introduced enormous behavioral and social shifts that prior data could not have predicted. To be sure, innovators often incorporate scientific discoveries in their creations, but their real genius is in their ability to imagine products or processes that never existed before.

The world we live in is not just the inevitable result of the laws of science at work; to act as if that’s the case would deny the potential for genuine innovation. A purely scientific approach to business decision-making has serious limitations, and managers need to understand those limits.

Can or cannot?

Most situations involve elements you can change and those you cannot. Spotting the difference is a critical skill for anyone in business. The question you need to ask is this: Is the situation dominated by possibility (that is, things we can alter for the better) or by necessity (elements we cannot change)?

Executives need to deconstruct every decision-making situation into “cannot” and “can” parts and then test their logic. If the initial hypothesis is that an element can’t be changed, the executive needs to ask what laws of nature suggest this. If the rationale for “cannot” is compelling, then the best approach is to apply a methodology that will optimize the status quo. In that case, let science be the master and use its tool kits of data and analytics to drive choices.

In a similar way, executives need to test the logic behind classifying elements as “cans.” What suggests that behaviors or outcomes can be different from what they have been? If the supporting rationale is strong enough, let design and imagination be the master and use analytics in their service.

It’s important to realize that the presence of data is not sufficient proof that a certain outcome is inevitable. Data is not logic. In fact, many of the most lucrative business moves come from bucking the evidence. Lego Brand Group chair Jørgen Vig Knudstorp offers a case in point. Back in 2008, when he was the company’s CEO, its data suggested that girls were much less interested in its toy bricks than boys were: 85 percent of Lego players were boys, and every attempt to attract more girls had failed. Many of the firm’s managers, therefore, believed that girls were inherently less likely to play with the bricks— they saw it as a “cannot” situation. But Knudstorp did not. The problem, he thought, was that Lego had not yet figured out how to inspire girls to play with construction toys. His hunch was borne out with the launch of the successful Lego Friends line in 2012.

The Lego case illustrates that data is no more than evidence, and it’s not always obvious what it is evidence of. Moreover, the absence of data does not preclude possibility. If you are talking about new outcomes and behaviors, then naturally there is no prior evidence.

A truly rigorous thinker considers not only what the data suggests but also what, within the bounds of possibility, could happen. And that requires imagination—a very different process from analysis.

The division between “can” and “cannot” is also more fluid than most people think. And innovators will push that boundary more than most.

Reprinted by permission of Harvard Business Review Press. Adapted from A New Way To Think: Your Guide To Superior Management Effectiveness by Roger L. Martin. Copyright 2022 Roger L. Martin. All rights reserved.