Range: How Generalists Triumph in a Specialized World

by David Epstein

she told me, in a clever inversion of a hallowed axiom, “First act and then think.” Ibarra marshaled social psychology to argue persuasively that we are each made up of numerous possibilities. As she put it, “We discover the possibilities by doing, by trying new activities, building new networks, finding new role models.” We learn who we are in practice, not in theory.

Themes emerged in the transitions. The protagonists had begun to feel unfulfilled by their work, and then a chance encounter with some world previously invisible to them led to a series of short-term explorations. At first, all career changers fell prey to the cult of the head start and figured it couldn’t possibly make sense to dispense with their long-term plans in favor of rapidly evolving short-term experiments. Sometimes they tried to talk themselves out of it. Their confidants advised them not to do anything rash; don’t change now, they said, just keep the new interest or talent as a hobby. But the more they dabbled, the more certain they were that it was time for a change. A new work identity did not manifest overnight, but began with trying something temporary, Hesselbein style, or finding a new role model, then reflecting on the experience and moving to the next short-term plan. Some career changers got richer, others poorer; all felt temporarily behind, but as in the Freakonomics coin-flip study, they were happier with a change.

Rather than expecting an ironclad a priori answer to “Who do I really want to become?,” their work indicated that it is better to be a scientist of yourself, asking smaller questions that can actually be tested—“Which among my various possible selves should I start to explore now? How can I do that?” Be a flirt with your possible selves.* Rather than a grand plan, find experiments that can be undertaken quickly. “ Test-and-learn,” Ibarra told me, “not plan-and-implement.”

It might seem that nothing would be easier than deciding what you like, but it turns out to be hard, partly because it’s hard to get an accurate picture of most jobs. . . . Most of the work I’ve done in the last ten years didn’t exist when I was in high school. . . . In such a world it’s not a good idea to have fixed plans.

And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don’t give up on your dreams. I know what they mean, but this is a bad way to put it, because it implies you’re supposed to be bound by some plan you made early on. The computer world has a name for this: premature optimization. . .

Instead of working back from a goal, work forward from promising situations. This is what most success...

In the graduation-speech approach, you decide where you want to be in twenty years, and then ask: what should I do now to get there? I propose instead that you don’t commit to anything in the future, but just look at the options available now, and choose th...

A person don’t know what he can do unless he tryes. Trying things is the answer to find your talent.”

efficacious,

“Knowledge is a double-edged sword. It allows you to do some things, but it also makes you blind to other things that you could do.”

conundrum.

Facing uncertain environments and wicked problems, breadth of experience is invaluable. Facing kind problems, narrow specialization can be remarkably efficient. The problem is that we often expect the hyperspecialist, because of their expertise in a narrow area, to magically be able to extend their skill to wicked problems. The results can be disastrous.

The average expert was a horrific forecaster. Their areas of specialty, years of experience, academic degrees, and even (for some) access to classified information made no difference. They were bad at short-term forecasting, bad at long-term forecasting, and bad at forecasting in every domain. When experts declared that some future event was impossible or nearly impossible, it nonetheless occurred 15 percent of the time.

Dropping familiar tools is particularly difficult for experienced professionals who rely on what Weick called overlearned behavior. That is, they have done the same thing in response to the same challenges over and over until the behavior has become so automatic that they no longer even recognize it as a situation-specific tool. Research on aviation accidents, for example, found that “a common pattern was the crew’s decision to continue with their original plan” even when conditions changed dramatically.

Decades later, an astronaut who flew on the space shuttle, both before and after Challenger, and then became NASA’s chief of safety and mission assurance, recounted what the “In God We Trust, All Others Bring Data” plaque had meant to him: “Between the lines it suggested that, ‘We’re not interested in your opinion on things. If you have data, we’ll listen, but your opinion is not requested here.’” Physicist and Nobel laureate Richard Feynman was one of the members of the commission that investigated the Challenger, and in one hearing he admonished a NASA manager for repeating that Boisjoly’s data did not prove his point. “When you don’t have any data,” Feynman said, “you have to use reason.”

“no tool is omnicompetent. There is no such thing as a master-key that will unlock all doors.” Rather than wielding a single tool, they have managed to collect and protect an entire toolshed, and they show the power of range in a hyperspecialized world.

“Take your skills to a place that’s not doing the same sort of thing. Take your skills and apply them to a new problem, or take your problem and try completely new skills.”

“Do we really need to go through courses with very specialized knowledge that often provides a huge amount of stuff that is very detailed, very specialized, very arcane, and will be totally forgotten in a couple of weeks? Especially now, when all the information is on your phone. You have people walking around with all the knowledge of humanity on their phone, but they have no idea how to integrate it. We don’t train people in thinking or reasoning.”

Don’t feel behind.

Compare yourself to yourself yesterday, not to younger people who aren’t you. Everyone progresses at a different rate, so don’t let anyone else make you feel behind. You probably don’t even know where exactly you’re going, so feeling behind doesn’t help. Instead, as Herminia Ibarra suggested for the proactive pursuit of match quality, start planning experiments. Your personal version of Friday night or Saturday morning experiments, perhaps.

Approach your own personal voyage and projects like Michelangelo approached a block of marble, willing to learn and adjust as you go, and even to abandon a previous goal and change directions entirely should the need arise.

Research on creators in domains from technological innovation to comic books shows that a diverse group of specialists cannot fully replace the contributions of broad individuals. Even when you move on from an area o...

“It is an experiment, as all life is an experiment.”

we learn who we are in practice, not in theory.

“Here’s who I am at the moment, here are my motivations, here’s what I’ve found I like to do, here’s what I’d like to learn, and here are the opportunities. Which of these is the best match right now? And maybe a year from now I’ll switch because I’ll find something better.”

“Research has established pretty firmly that diverse groups of people are better at innovation and problem solving, but more recent research is finding that diverse career histories within a single person can also benefit performance.”

Specialization has benefits, she added, “but before specialization comes sampling, the exploration of possibilities that, really, you cannot know anything about until you try them . . . Don’t confuse the healthy development of a work ethic with the premature commitment to a singular passion.”

The early specializers often won in the short term, and lost in the long run. Workers who received general education, the economists concluded, were better positioned to adapt to change in a wicked world where work next year might not look like work last year.