Range: Why Generalists Triumph in a Specialized World

by David Epstein

I never expected that my path from science into writing would go through work as the overnight crime reporter at a New York City tabloid, nor that I would shortly thereafter be a senior writer at Sports Illustrated, a job that, to my own surprise, I would soon leave. I began worrying that I was a job-commitment-phobic drifter who must be doing this whole career thing wrong. Learning about the advantages of breadth and delayed specialization has changed the way I see myself and the world.

rather than relying on our own direct experiences, we make sense of reality through classification schemes, using layers of abstract concepts to understand how pieces of information relate to one another. We have grown up in a world of classification schemes totally foreign to the remote villagers;

They were trying to turn a conceptual problem they didn’t understand into a procedural one they could just execute.

Repetition, it turned out, was less important than struggle.

it is difficult to accept that the best learning road is slow, and that doing poorly now is essential for better performance later. It is so deeply counterintuitive that it fools the learners themselves, both about their own progress and their teachers’ skill.

A reason for this, the researchers concluded, is that early childhood education programs teach “closed” skills that can be acquired quickly with repetition of procedures, but that everyone will pick up at some point anyway. The fadeout was not a disappearance of skill so much as the rest of the world catching up. The motor-skill equivalent would be teaching a kid to walk a little early. Everyone is going to learn it anyway, and while it might be temporarily impressive, there is no evidence that rushing it matters.

College football coaches rated the same player’s potential very differently depending on what former player he was likened to in an introductory description, even with all other information kept exactly the same.

Netflix came to a similar conclusion for improving its recommendation algorithm. Decoding movies’ traits to figure out what you like was very complex and less accurate than simply analogizing you to many other customers with similar viewing histories. Instead of predicting what you might like, they examine who you are like, and the complexity is captured therein.

there is often no entrenched interest fighting on the side of range, or of knowledge that must be slowly acquired. All forces align to incentivize a head start and early, narrow specialization, even if that is a poor long-term strategy. That is a problem, because another kind of knowledge, perhaps the most important of all, is necessarily slowly acquired—the kind that helps you match yourself to the right challenge in the first place.

The more skilled the Army thought a prospective officer could become, the more likely it was to offer a scholarship. And as those hardworking and talented scholarship recipients blossomed into young professionals, they tended to realize that they had a lot of career options outside the military. Eventually, they decided to go try something else. In other words, they learned things about themselves in their twenties and responded by making match quality decisions.

When they were high school graduates, with few skills and little exposure to a world of career options, West Point cadets might easily have answered “Not like me at all” to the Grit Scale statement “I often set a goal but later choose to pursue a different one.” A few years later, with more knowledge of their skills and preferences, choosing to pursue a different goal was no longer the gritless route; it was the smart one.

In the wider world of work, finding a goal with high match quality in the first place is the greater challenge, and persistence for the sake of persistence can get in the way.

Diversity was great, Hesselbein was told, but it was too much too soon. Fix the organizational problems, and then worry about diversity. But she had decided that diversity was the primary organizational problem, so she took it further.

Darwin began perhaps the most impactful post-college gap year in history. His father’s wishes eventually “died a natural death.” Decades later, Darwin reflected on the process of self-discovery.

Over the course of her work, she watched midcareer professionals move from a flicker of desire for change, to an unsettling period of transition, to the actual jump to a new career. Occasionally she saw the entire process occur twice for the same individual.

Swanson felt that if this big bang of public knowledge continued apace, subspecialties would be like galaxies, flying away from one another until each is invisible to every other.

The polymaths had depth in a core area—so they had numerous patents in that area—but they were not as deep as the specialists. They also had breadth, even more than the generalists, having worked across dozens of technology classes. Repeatedly, they took expertise accrued in one domain and applied it in a completely new one, which meant they were constantly learning new technologies. Over the course of their careers, the polymaths’ breadth increased markedly as they learned about “the adjacent stuff,” while they actually lost a modicum of depth.

Griffin’s research team noticed that serial innovators repeatedly claimed that they themselves would be screened out under their company’s current hiring practices. “A mechanistic approach to hiring, while yielding highly reproducible results, in fact reduces the numbers of high-potential [for innovation] candidates,” they wrote.

Incredibly, the hedgehogs performed especially poorly on long-term predictions within their domain of expertise. They actually got worse as they accumulated credentials and experience in their field. The more information they had to work with, the more they could fit any story to their worldview.

A hallmark of interactions on the best teams is what psychologist Jonathan Baron termed “active open-mindedness.” The best forecasters view their own ideas as hypotheses in need of testing. Their aim is not to convince their teammates of their own expertise, but to encourage their teammates to help them falsify their own notions.

Like Van Gogh or Frances Hesselbein or hordes of young athletes, Novoselov probably looked from the outside like he was behind, until all of a sudden he very much wasn’t. He was lucky. He arrived in a workspace that treated mental meandering as a competitive advantage, not a pest to be exterminated in the name of efficiency.

“When you push the boundaries, a lot of it is just probing. It has to be inefficient,” Casadevall told me. “What’s gone totally is that time to talk and synthesize. People grab lunch and bring it into their offices. They feel lunch is inefficient, but often that’s the best time to bounce ideas and make connections.”