Specialists are eating the world. Tiger parents push their kids to get an early start and develop enough expertise to distinguish themselves for admissions committees from preschool through college. Academic departments push exquisite depth, seeking scholars to drill down and become world authorities in ever more narrow subjects. Corporate hiring managers seek candidates for roles with sharply defined skill sets.
“We are often taught that the more competitive and complicated the world gets, the more specialized we all must become (and the earlier we must start) to navigate it,” writes journalist David Epstein in Range, perhaps the most important business — and parenting — book of the year.
Epstein has nothing against specialization, but believes our obsession with it has gotten out of hand, in the process obscuring an important counter-narrative that values breadth and lateral thinking, tolerates ambiguity and inefficiency, embraces meandering career paths and extols personal exploration.
I should acknowledge at the outset the intense personal resonance of Epstein’s themes. Fifteen years ago, Denny Ausiello and I worried about “our failure to nourish and sustain inquisitive physicians-scientists,” and noted “efficiency isn’t everything, and unless we learn to cultivate creativity as avidly as we pursue consistency, future generations of patients may find themselves stuck with the same basic treatments they’re receiving today. It will be the same medicine, just served quickly.” A defining feature of the Harvard translational research training program Denny and I founded in 1999 (more here) was that our monthly speakers – brilliant medical innovators like Robert Langer, Denise Faustman, Judah Folkman, Jeff Flier – had to begin their talks by telling students about their real career journeys, which invariably were far more meandering and uncertain than the linear narratives generally deployed to introduce distinguished speakers, where one’s life path can seem like a series of deliberate steps leading up to the present moment. The truth tends to be far less obvious – and appreciably more interesting. The Tech Tonics podcast Lisa Suennen and I have been hosting since 2015 similarly focuses on the complex and uncertain journey of inspiring innovators in technology, health, and medicine.
Kind Vs Wicked Domains
The gist of Epstein’s argument is that much of the work celebrating specialization comes from what psychologist Robin Hogarth calls “kind” domains, areas where “patterns repeat over and over, and feedback is extremely accurate and usually very rapid,” where there are “rules and within defined boundaries, a consequence is quickly apparent, and similar challenges occur repeatedly.” Golf and chess, for example.
But this may represent what Taleb has called the “ludic fallacy,” and simple games constitute a relative poor model for the real world and it’s pervasive “wicked” domains where rules “are often unclear or incomplete, there may or may not be repetitive patterns and they may not be obvious, and feedback is often delayed, inaccurate, or both.” The problem, Epstein explains, is that without realizing it, we instinctively – and at our peril – apply the heuristics that work so effectively in kind domains into areas that are wicked.
“When narrow specialization is combined with an unkind domain, the human tendency to rely on experience of familiar patterns can backfire horribly,” Epstein writes. In kind environments, early specialization and “massive amounts of narrow practice” makes sense; you want you gallbladder removed by a surgeon who has extensive experience with the exact procedure. “But when the rules are altered just slightly,” Epstein observes, “it makes experts appear to have traded flexibility for narrow skill.”
Epstein takes aim at the hyperspecialization mythology by puncturing some widely-held assumptions. He cites studies that find most elite athletes initially spent less time than near-elite athletes practicing the sport on which they eventually excel. Rather, elite athletes often try out a number of sports, which Epstein explains is useful both because it provides them an opportunity to optimize “match fit” and also to cross-train, which seems to be especially helpful. The same seems to be true for musicians, where many the best and most creative tend not to be the ones who picked one instrument as a toddler and stuck with it relentlessly. It’s not just that one can always find distinguished exceptions, Epstein repeatedly emphasizes; based on the data, these “exceptions” seem to be the rule.
Cross-training – gaining experience in a range of activities, domains, sports, instruments – may be valuable, especially in wicked environments, because “breadth of training predicts breadth of transfer. The more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example. Learners become better at applying their knowledge to a situation they’ve never seen before, which is essence of creativity.”
The essence of “match fit” is the idea that it’s important to align who you are – your “abilities and proclivities” – with what you do. The catch – and the opportunity – Epstein explains, is that “we learn who we are only by living and not before. Epstein cites Herminia Ibarra, a professor at London Business School, who explains that we are each made of numerous possibilities, and “discover the possibilities by doing, by trying new activities, building new networks, find new role models.” In other words, Epstein summarizes, “We learn who we are in practice, not in theory.”
One implication of this perspective: reconceptualizing grit. Recognizing something represents a bad fit and moving on to something else may not represent a lack of grit, he argues, but rather a savvy decision. He cites West Point graduates who at some point decide to step away from military careers; this shouldn’t be understood as lack of grit, because it means they found something they liked better, reflecting their strong drive for personal development. As he observes,
“No one in their right mind would argue that passion and perseverance are unimportant, or that a bad day is a cue to quit. But the idea that a change in interest, or a recalibration of focus, is an imperfection and competitive disadvantage leads to a simple, one size fits all Tiger story: pick and stick, and soon as possible. Responding to lived experience with a change of direction, like Van Gogh did habitually, like West Point graduates have been doing since the dawn of the knowledge economy, is less tidy but no less important.”
Another implication: instead of asking “what do I really want to become,” Epstein advises, research suggests you would be you might be better off asking, “which among my various possible selves should I start to explore now. How can I do that?… Rather than grand plan, find experiments that can be undertaken quickly.” This approach can help you avoid what Y Combinator Paul Graham calls the “premature optimization” trap, Epstein explains. “Instead of working back from a goal,” Graham suggests, “work forward from promising situations.” In other words, exchange a “plan and implement” mindset, as Ibarra puts it, for a “test and learn” approach.
Epstein recognizes this framework can lead to a path, and potentially a career, that’s meandering, and squandering time that could be used to advance in a single, focused direction. He delights in pointing out both compelling examples and a slew of scientific studies that highlight the value (economic as well as psychological) of delayed specialization, and of exposure to multiple disciplines. Success often involves a very long road; van Gogh serially explored a range of roles (“a student, an art dealer, a teacher, a book-seller, a prospective pastor, and an itinerant catechist”), each time, after “promising starts, he had failed spectacularly in every path he tried.” He after he identified a prospect match – painting – he embarked on another extensive discovery process as he “pinballed from one artistic passion to another.” Epstein discovers fascinating research on comic book creators, studies that revealed the best predictor of success (which required creative talent, obviously, but was defined by commercial value – the investigators were business school professors after all) was “how many of twenty-two different genres a creator had worked in….. Length of experience did not differentiate creators, breadth of experiences did. Broad genre experience made creators better on average and more likely to innovate.” Observes Epstein, “Mental meandering and personal experimentation are sources of power, and head starts are overrated.”
One of Epstein’s most perceptive observations is that “at its core, hyperspecialization is a well-meaning drive for efficiency.” Epstein takes particular pleasure in providing a succession of examples that our addiction to immediate gratification may be sending us down the wrong paths. He cites several compelling examples from education, noting that teaching math, for example, involves using procedures and making connection – but making connections is hard, and understandably, many students want to turn a conceptual problem they don’t understand into a procedural one they can just execute. Not only do teachers tend to give to the students, but parents do as well, preferring to teach their kids shortcuts versus watching them struggle through a frustrating homework problem intended to push students to make connections. “Well-meaning parents,” writes Epstein, “aren’t comfortable with bewildered kids, and they want understanding to come quickly and easily. But for learning that is both durable (it sticks) and flexible (it can be applied broadly), fast and easy is precisely the problem.
Considerable research, apparently shows that a degree of struggle – “desirable difficulties” is the term of art is critical for learning, and “obstacles that make learning more challenging, slower, and more frustrating in the short term” can make it “better in the long-term,” while excessive hinting “bolsters immediate performance but undermines progress in the long run.” In part this relates to the “generation effect” – “struggling to generate an answer on your own, even a wrong one, enhances subsequent learning.” Epstein describes a captivating study of Air Force Academy cadets demonstrating that the highest-scoring students on a Calculus I final (the only exam in the course) tended to taught by professors rated highly by students, yet these students were not the ones who retained the information best . They felt like they were learning, they credited their teachers for teaching them, but the teaching didn’t stick. In contrast, it was students whose immediate performance was worse, and who didn’t feel as good about the effectiveness of their teachers, who actually emerged as the best educated, as evaluated by performance in subsequent classes that requires Calculus I as a prerequisite. “Professors who excel at promoting contemporaneous student achievement,” the researchers observed (per Epstein) “on average, harm the subsequent performance of their students in more advanced classes.” The researchers suggested (but hardly proved) that the professors with the less-happy but better educated students may have focused on making connections.
In another example that may reflect the same underlying phenomenon, Epstein highlights a study showing that work with new knowledge combinations in science, and papers that bring different or unusual approaches to a particular field – are “less likely to be funded, less likely to appear in famous journals, more likely to be ignored upon publication.” But “after three years, the papers with new knowledge combos surpassed conventional papers, and began accumulating more citations from other scientists. Fifteen years after publication, studies that made multiple new knowledge combinations were way more likely to be in the top one percent of most cited papers.”
The ability to make connections is arguably becoming ever-more important, Epstein argues. He observes that the hallmark of modernity is abstract thinking – and presents a fascinating “natural experiment” study performed by Russian psychologist Alexander Luria in 1930s Russia, essentially comparing the thinking of residents of remote villages that had just been restructured by the socialist revolution into collective farms with the thinking of residents of similar villages that the revolution hadn’t quite got to yet, and which were still “premodern.” The researchers discovered that residents of the untouched villages could only think in concrete terms, while the others were able to abstract. “The more they had moved towards modernity,” Epstein writes, “the more powerful their abstract thinking, and the less they had to rely on their concrete experience of the world as a reference point.”
Regrettably, Epstein complains, contemporary education, including (and perhaps in particular) higher education, seems increasingly focused on specialization. The GPA of college students, a study conducted by New Zealand researcher James Flynn found, didn’t correlate at all with performance on a test of broad conceptual thinking. Laments Flynn, “There is no sign any [university] department attempts to develop [anything] other than narrow critical competence.” Epstein is a big fan of interdisciplinary efforts, like Northwestern’s Integrated Science Program, and the R3 Initiative at Johns Hopkins. (The counterargument is that you can’t really understand how a discipline thinks without understanding it in real depth.) Epstein emphasizes the value of analogies, and the importance of framing (and re-framing) problems. He cites Jeannette Wing, a Columbia Professor and former Microsoft Research Executive, who has advanced the idea “computational thinking” as a “mental Swiss Army Knife” that uses “abstraction and decomposition when attacking a large complex task. It is choosing appropriate representation for a problem.”
Generalists As Heroes
Range is the sort of book that makes you want to stand up and cheer. Epstein celebrates creative tinkerers, like Nintendo developer Gunpei Yokoi who excelled in “lateral thinking with withered technologies”; outsiders, like the solver participating in the crowdsourcing innovation platform InnoCentive who figured out how to approach a vexing problem of oil sludge cleanup by applying a lesson he learned one day while helping a friend pour concrete steps; proud generalists, like the creative 3M scientists Jayshree Seth and Andy Ouderkirk; and champions of interdisciplinary thinking, like Hopkins professor Arturo Casadevall, a physician-scientist who’s trying to coax colleagues out of their silos. “The system maintains you in a trench,” Casadevall says. “You basically have all these parallel trenches, and it s vary rare that anybody stands up and actually looks at the next trench to see what they are doing, and often it’s related….We don’t train people in thinking or in reasoning….Everyone acknowledges that great progress is made at the interface, but who is there to defend the interface?”
Scientists will also enjoy the story about the invention of gel electrophoresis by Oliver Smithies, a relentlessly imaginative researcher who remembered cleaning up goopy starch from home-washed shirts, and learning that Edwin Southern developed the DNA transfer technique that bears his name based on a childhood memory of cyclostyling (“an old document-copying device that used glazed paper and a stencil system,” in case you were wondering). Meanwhile executives are sure to chuckle knowingly as they read Epstein’s description of a Yale study of “high powered consultants” who “did really well on business school problems that were well-defined and quickly assessed. But they employed single-loop learning, the kind that favors the first familiar solution that comes to mind. Whenever those solutions went wrong, the consultant usually got defensive, which the professor found particularly surprising since the ‘essence of their job’ is to teach others how to do things differently.”
Insightfully, Epstein recognizes how the best leaders, like wilderness firefighter Paul Gleason and Air Force pararescue jumper (PJ) Tony Lesmes, favor what behavior expert Karl Weick calls “hunches held lightly,” balancing the need for the direction with the willingness to change should the situation call for it; he appreciates the deft management skills of NASA legend Gene Kranz (Flight Director during the time of the Apollo 11 mission), who simultaneously valorized process but also had a habit of seeking out opinions from technicians and engineers at every level of the hierarchy, simultaneously maintaining the established chain of command while also introducing an additional, informal chain of communication – in marked contrast to the more formalized and less nuanced approaches, built around “allegiance to hierarchy and procedure,” that may have contributed to the Challenger and Columbia disasters.
Epstein excels at demystifying expertise – or at least encouraging us to avoid the temptation to overgeneralize from it. Consider chess grandmasters, who have legendary ability to remember chess positions they’ve seen for fleeting seconds, or some savants, who can perfectly reproduce a pop tune they’ve heard just once. It turns out that grandmasters don’t do especially well on memory tasks if presented with random chess positions, or positions that couldn’t actually occur in a game, just as music savants struggle to recapture atonal melodies Epstein reveals. What seems like photographic memory, or acting like a human tape recorder, is really just the ability to recognize familiar, repetitive patterns, like chess positions or conventional music arrangements. Impressive feats, to be sure; but also surprisingly fragile – tweak the situation, and the edge is lost.
Epstein also invokes the work ofUniversity of Pennsylvania researcher Philip Tetlock, who persuasively demonstrated that “the average expert is a horrific forecaster,” and found “a ‘perverse inverse relationship’ between fame and accuracy.” Interestingly, the narrow experts, which Tetlock called hedgehogs (in contrast to the integrators, known as foxes), performed especially poorly on long-term predictions within their domain of expertise – worse with time and credentials and experience. It was as if a wicked environment had hacked their feedback loop, perhaps by reifying existing biases and beliefs that hedgehogs tend to hold especially firmly. To this very point, Karim Lakhani, a Harvard innovation researcher studying InnoCentive and approaches like it, found that “the further a problem was from the solver’s expertise, the more likely they were to solve it.” Lahani adds, according to Epstein, that “a key to creative problem solving is tapping outsiders who use different approaches ‘so that the “home field” for the problem does not end up constraining the solution.’” (To be fair, the problems presented the InnoCentive solver community were generally those that internal experts struggled with, and may only represent a small fraction of total problem space.)
Thus, while “our intuition might be that only hyperspecialized experts can drive modern innovation,” Epstein writes, “but increasing specialization actually creates new opportunities for outsiders.” Epstein acknowledges that most organizations reflexively tend towards local search for difficult challenges, Lakhani might encourage them to think differently, noting that Big innovation most often happens when an outsider who may be far away from the surface of a problem reframes the problem in a way that unlocks the solution.” This is a problem Epstein sees not only in the corporate world but also in the academy, where university departments “elevate narrowness as an ideal.”
As any parent can tell you, it’s really hard to escape the draw of expertise, and the cult of immediate feedback. It’s reassuring to feel you’re seeing concrete progress, continuous learning, the evolution of expertise. It’s all well and good for Epstein to praise personal experimentation and the search for match fit, but I suspect if you’re the parent of a young adult who seems to flit from major to major, interest to interest, or career to career, it would be increasingly difficult to persuade yourself that your child will emerge as the next Van Gogh as you worry they’ll never get it together – which of course was exactly what Van Gogh’s parents apparently thought as well, “insisting the he needed to ‘stop following [his] own desires’ and return to a stable life course.” Inspiring as the meandering into success stories are, you wonder if they’re representative, and it’s hard not to at least contemplate the denominator even as we celebrate the numerator.
Optimizing For A Complex World
But to dwell on that point would miss what I suspect is the larger and far more important point of the book: we live in a staggeringly complex world, an incredible mix of kind and wicked environments. This was highlighted in a piece by Klein and Kahneman that Epstein references in Range (and I discuss here), examining the intuition quality of different experts, which turned out to depend on whether they functioned in a kind environment (where experts had great intuition) or a wicked environment (where the intuition of experts was consistently poor). Interestingly, a few occupations – including physician — turned up on both lists, meaning that they operate in a realm that’s sometimes kind (so intuition and experience matters) and other times wicked; Kahneman and Klein called this “fractionated expertise,” and I suspect it’s remarkably common.
Many individuals and most organizations are required to operate in similarly mixed environments, where success unquestionably requires exquisite specialization to go deep where required, but it also needs broad, integrative operators, lateral thinkers, who can imaginatively reframe complex problems and catalyze original solutions. Integrative talent, by its very nature, can be especially challenging to evaluate, cultivate, or even to identify, but offers such critical value that we must pursue it nonetheless. “If you’re working on well-defined and well-understood problems,” the prolific 3M innovator Ouderkirk tells Epstein, “specialists work very, very well. As ambiguity and uncertainty increases, which is the norm with system problems, breadth becomes increasingly important.”
Similarly, studies of patents led by Spanish business professors Eduardo Melero and Neus Palomeras found that in “low uncertainty domains” characterized by “linear progression with more obvious next steps… teams of specialists were more likely to author useful patents. In high-uncertainty domains—where the fruitful questions themselves were less obvious –teams that include individuals who had worked on a wide variety of technologies were more likely to make a splash. The higher the domain uncertainty, the more important it was to have a high-breadth team member.”
Another study of patents – led by Ouderkirk and colleagues – found that specialist and generalists “both made contributions. One was not uniformly superior to the other.” (Those lacking breadth and depth, by contrast, “rarely made an impact.”) Specialists, the researchers reported, “were at working for a long time on difficult technical problems, and for anticipating development obstacles.” Generalists, in contrast, “added value by integrating domains, taking technology from one area and applying it in others.”
Yokoi, the Nintento innovator and a generalist, recognized the need for specialists, but worried (very appropriately, I’d add) about the fate of generalists in a maturing company. “His concern,” Epstein writes, “was that as companies grew and technology progressed, vertical-thinking hyperspecialists would continue to be valued but lateral-thinking generalists would not…. Lateral and vertical thinkers were best together, even in high technical fields.”
The worry, however, is that – as the coauthors of Serial Innovators write, per Epstein, “’HR policies at mature companies have such a well-defined specialized slots for employees that potential serial innovators will look like round pegs to square holes’ and get screened out. Their breadth of interests do not neatly fit a rubric.” Epstein describes incredible positive impact of a receptive professional environment on Konstantin Novoselov, the researcher who shared the 2010 Nobel Prize with his mentor Andre Geim, for the production of the material graphene. Novoselov joined Geim’s lab after starting his graduate school career in a different research group. In Geim’s lab, Novoselov “found equipment that was similar to his previous lab, but ‘this flexibility and the opportunity to try yourself in different areas which was interesting.’” As Epstein nicely distills it, “Novoselov probably looked from the outside like he was behind, until all of a sudden he very much wasn’t. He was lucky. He arrive in a workspace that treated mental meandering as a competitive advantage, not a pest to be exterminated in the name of efficiency…. That kind of protection from the cult of the head start is increasingly rare.”
Rather than cultivate lateral thinking, some organizations seem to be doubling down on depth, which can be reflected in their approach to technology. Yokoi, for example, specifically worried that “the ‘shortcut [for a lack of ideas] is competition in the realm of computing powers’” – the idea that one can compensate for creative, lateral thinking with computer-driven vertical approaches.
The Power Of Collaboration
Happily, Epstein offers an encouraging counterexample, a more hopeful way the future could evolve, arising from a form of chess called freestyle, which features human-computer teams. After first demonstrating how computers can now beat even the very best grandmasters, and showing that the key skill of grandmasters – pattern recognition – can be assumed by computer, Epstein reveals that human-computer teams can do much better than either computer or grandmasters, even if the human is not especially adept at chess. He writes,
“A duo of amateur players with three normal computers not only destroyed Hydra, the best chess super computer, they also crushed teams of grandmasters using computers. [Chess Grandmaster Gary] Kasparov concluded that the humans on the winning team were the best at ‘coaching’ multiple computers on what to examine, and then synthesizing that information for an overall strategy. Human/computer combo teams – known as ‘centaurs’ – were playing the highest level of chess ever seen.”
Another freestyle chess tournament was won by a team consisting of four people and several computers, Epstein tells us:
“The captain and primary decision maker was Anson Williams, a British engineer with no official chess rating. His teammate, Nelson Hernandez, [said] ‘…freestyle involves an integrated set of skills that in some cases have nothing to do with playing chess.’ In traditional chess, Williams was probably at the level of a decent amateur. But he was well versed in computers and adept at integrating streaming information for strategy decisions. As a teenager, he had been outstanding at the video game Command & Conquer, known as a “real time strategy” game….”
This example seems to highlight that ability to integrate information may well be among the most value skill sets of the future (and perhaps was the very skill your kid was honing when you told her to stop messing around with the video games and go back to her math homework). More generally, as both this example and Epstein’s book as a whole suggest, the future may belong exclusively to neither the hyperspecialists or the integrators, but rather to organizations, and perhaps the rare individuals, able to value, cultivate, facilitate and authentically embrace the full range – breadth as well as depth — of expertise.