Drive: The Surprising Truth About What Motivates Us

by Daniel H. Pink

  Neither open-source production nor previously unimagined “not only for profit” businesses are yet the norm, of course. And they won’t consign the public corporation to the trash heap. But their emergence tells us something important about where we’re heading. “There’s a big movement out there that is not yet recognized as a movement,” a lawyer who specializes in for-benefit organizations told The New York Times.6 One reason could be that traditional businesses are profit maximizers, which square perfectly with Motivation 2.0. These new entities are purpose maximizers—which are unsuited to this older operating system because they flout its very principles.

  How We Think About What We Do

  When I took my first economics course back in the early 1980s, our professor—a brilliant lecturer with a Patton-like stage presence—offered an important clarification before she’d chalked her first indifference curve on the blackboard. Economics, she explained, wasn’t the study of money. It was the study of behavior. In the course of a day, each of us was constantly figuring the cost and benefits of our actions and then deciding how to act. Economists studied what people did, rather than what we said, because we did what was best for us. We were rational calculators of our economic self-interest.

  When I studied law a few years later, a similar idea reappeared. The newly ascendant field of “law and economics” held that precisely because we were such awesome self-interest calculators, laws and regulations often impeded, rather than permitted, sensible and just outcomes. I survived law school in no small part because I discovered the talismanic phrase and offered it on exams: “In a world of perfect information and low transaction costs, the parties will bargain to a wealth-maximizing result.”

  Then, about a decade later, came a curious turn of events that made me question much of what I’d worked hard, and taken on enormous debt, to learn. In 2002, the Nobel Foundation awarded its prize in economics to a guy who wasn’t even an economist. And they gave him the field’s highest honor largely for revealing that we weren’t always rational calculators of our economic self-interest and that the parties often didn’t bargain to a wealth-maximizing result. Daniel Kahneman, an American psychologist who won the Nobel Prize in economics that year for work he’d done with Israeli Amos Tversky, helped force a change in how we think about what we do. And one of the implications of this new way of thinking is that it calls into question many of the assumptions of Motivation 2.0.

  Kahneman and others in the field of behavioral economics agreed with my professor that economics was the study of human economic behavior. They just believed that we’d placed too much emphasis on the economic and not enough on the human. That hyperrational calculator-brained person wasn’t real. He was a convenient fiction.

  Play a game with me and I’ll try to illustrate the point. Suppose somebody gives me ten dollars and tells me to share it—some, all, or none—with you. If you accept my offer, we both get to keep the money. If you reject it, neither of us gets anything. If I offered you six dollars (keeping four for myself ), would you take it? Almost certainly. If I offered you five, you’d probably take that, too. But what if I offered you two dollars? Would you take it? In an experiment replicated around the world, most people rejected offers of two dollars and below.7 That makes no sense in terms of wealth maximization. If you take my offer of two dollars, you’re two dollars richer. If you reject it, you get nothing. Your cognitive calculator knows two is greater than zero—but because you’re a human being, your notions of fair play or your desire for revenge or your simple irritation overrides it.

  In real life our behavior is far more complex than the textbook allows and often confounds the idea that we’re purely rational. We don’t save enough for retirement even though it’s to our clear economic advantage to do so. We hang on to bad investments longer than we should, because we feel far sharper pain from losing money than we do from gaining the exact same amount. Give us a choice of two television sets, we’ll pick one; toss in an irrelevant third choice, and we’ll pick the other. In short, we are irrational—and predictably so, says economist Dan Ariely, author of Predictably Irrational, a book that offers an entertaining and engaging overview of behavioral economics.

  The trouble for our purposes is that Motivation 2.0 assumes we’re the same robotic wealth-maximizers I was taught we were a couple of decades ago. Indeed, the very premise of extrinsic incentives is that we’ll always respond rationally to them. But even most economists don’t believe that anymore. Sometimes these motivators work. Often they don’t. And many times, they inflict collateral damage. In short, the new way economists think about what we do is hard to reconcile with Motivation 2.0.

  What’s more, if people do things for lunk-headed, backward-looking reasons, why wouldn’t we also do things for significance-seeking, self-actualizing reasons? If we’re predictably irrational—and we clearly are—why couldn’t we also be predictably transcendent?

  If that seems far-fetched, consider some of our other bizarre behaviors. We leave lucrative jobs to take low-paying ones that provide a clearer sense of purpose. We work to master the clarinet on weekends although we have little hope of making a dime (Motivation 2.0) or acquiring a mate (Motivation 1.0) from doing so. We play with puzzles even when we don’t get a few raisins or dollars for solving them.

  Some scholars are already widening the reach of behavioral economics to encompass these ideas. The most prominent is Bruno Frey, an economist at the University of Zurich. Like the behavioral economists, he has argued that we need to move beyond the idea of Homo Oeconomicus (Economic Man, that fictional wealth-maximizing robot). But his extension goes in a slightly different direction—to what he calls Homo Oeconomicus Maturus (or Mature Economic Man). This figure, he says, “is more ‘mature’ in the sense that he is endowed with a more refined motivational structure.” In other words, to fully understand human economic behavior, we have to come to terms with an idea at odds with Motivation 2.0. As Frey writes, “Intrinsic motivation is of great importance for all economic activities. It is inconceivable that people are motivated solely or even mainly by external incentives.”8

  How We Do What We Do

  If you manage other people, take a quick glance over your shoulder. There’s a ghost hovering there. His name is Frederick Winslow Taylor—remember him from earlier in the chapter?—and he’s whispering in your ear. “Work,” Taylor is murmuring, “consists mainly of simple, not particularly interesting, tasks. The only way to get people to do them is to incentivize them properly and monitor them carefully.” In the early 1900s, Taylor had a point. Today, in much of the world, that’s less true. Yes, for some people work remains routine, unchallenging, and directed by others. But for a surprisingly large number of people, jobs have become more complex, more interesting, and more self-directed. And that type of work presents a direct challenge to the assumptions of Motivation 2.0.

  Begin with complexity. Behavioral scientists often divide what we do on the job or learn in school into two categories: “algorithmic” and “heuristic.” An algorithmic task is one in which you follow a set of established instructions down a single pathway to one conclusion. That is, there’s an algorithm for solving it. A heuristic task is the opposite. Precisely because no algorithm exists for it, you have to experiment with possibilities and devise a novel solution. Working as a grocery checkout clerk is mostly algorithmic. You do pretty much the same thing over and over in a certain way. Creating an ad campaign is mostly heuristic. You have to come up with something new.

  During the twentieth century, most work was algorithmic—and not just jobs where you turned the same screw the same way all day long. Even when we traded blue collars for white, the tasks we carried out were often routine. That is, we could reduce much of what we did—in accounting, law, computer programming, and other fields—to a script, a spec sheet, a formula, or a series of steps that produced a right answer. But today, in much of North America, Western Europe, Japan, South Korea, and Australia, routine white-collar work is dis
appearing. It’s racing offshore to wherever it can be done the cheapest. In India, Bulgaria, the Philippines, and other countries, lower-paid workers essentially run the algorithm, figure out the correct answer, and deliver it instantaneously from their computer to someone six thousand miles away.

  But offshoring is just one pressure on rule-based, left-brain work. Just as oxen and then forklifts replaced simple physical labor, computers are replacing simple intellectual labor. So while outsourcing is just beginning to pick up speed, software can already perform many rule-based, professional functions better, more quickly, and more cheaply than we can. That means that your cousin the CPA, if he’s doing mostly routine work, faces competition not just from five-hundred-dollar-a-month accountants in Manila, but from tax preparation programs anyone can download for thirty dollars. The consulting firm McKinsey & Co. estimates that in the United States, only 30 percent of job growth now comes from algorithmic work, while 70 percent comes from heuristic work.9 A key reason: Routine work can be outsourced or automated; artistic, empathic, nonroutine work generally cannot.10

  The implications for motivation are vast. Researchers such as Harvard Business School’s Teresa Amabile have found that external rewards and punishments—both carrots and sticks—can work nicely for algorithmic tasks. But they can be devastating for heuristic ones. Those sorts of challenges—solving novel problems or creating something the world didn’t know it was missing—depend heavily on Harlow’s third drive. Amabile calls it the intrinsic motivation principle of creativity, which holds, in part: “Intrinsic motivation is conducive to creativity; controlling extrinsic motivation is detrimental to creativity.”11 In other words, the central tenets of Motivation 2.0 may actually impair performance of the heuristic, right-brain work on which modern economies depend.

  Partly because work has become more creative and less routine, it has also become more enjoyable. That, too, scrambles Motivation 2.0’s assumptions. This operating system rests on the belief that work is not inherently enjoyable—which is precisely why we must coax people with external rewards and threaten them with outside punishment. One unexpected finding of the psychologist Mihaly Csikszentmihalyi, whom we’ll encounter in Chapter 5, is that people are much more likely to report having “optimal experiences” on the job than during leisure. But if work is inherently enjoyable for more and more people, then the external inducements at the heart of Motivation 2.0 become less necessary. Worse, as Deci began discovering forty years ago, adding certain kinds of extrinsic rewards on top of inherently interesting tasks can often dampen motivation and diminish performance.

  Once again, certain bedrock notions suddenly seem less sturdy. Take the curious example of Vocation Vacations. This is a business in which people pay their hard-earned money . . . to work at another job. They use their vacation time to test-drive being a chef, running a bike shop, or operating an animal shelter. The emergence of this and similar ventures suggests that work, which economists have always considered a “disutility” (something we’d avoid unless we received a payment in return), is becoming a “utility” (something we’d pursue even in the absence of a tangible return).

  Finally, because work is supposed to be dreary, Motivation 2.0 holds that people need to be carefully monitored so they don’t shirk. This idea, too, is becoming less relevant and, in many ways, less possible. Consider, for instance, that America alone now has more than 18 million of what the U.S. Census Bureau calls “non-employer businesses”—businesses without any paid employees. Since people in these businesses don’t have any underlings, they don’t have anybody to manage or motivate. But since they don’t have bosses themselves, there’s nobody to manage or motivate them. They have to be self-directed.

  So do people who aren’t technically working for themselves. In the United States, 33.7 million people telecommute at least one day a month, and 14.7 million do so every day—placing a substantial portion of the workforce beyond the gaze of a manager, forcing them to direct their own work.12 And even if many organizations haven’t opted for measures like these, they’re generally becoming leaner and less hierarchical. In an effort to reduce costs, they trim the fatty middle. That means managers oversee larger numbers of people and therefore scrutinize each one less closely.

  As organizations flatten, companies need people who are self-motivated. That forces many organizations to become more like, er, Wikipedia. Nobody “manages” the Wikipedians. Nobody sits around trying to figure out how to “motivate” them. That’s why Wikipedia works. Routine, not-so-interesting jobs require direction; nonroutine, more interesting work depends on self-direction. One business leader, who didn’t want to be identified, said it plainly. When he conducts job interviews, he tells prospective employees: “If you need me to motivate you, I probably don’t want to hire you.”

  TO RECAP, Motivation 2.0 suffers from three compatibility problems. It doesn’t mesh with the way many new business models are organizing what we do—because we’re intrinsically motivated purpose maximizers, not only extrinsically motivated profit maximizers. It doesn’t comport with the way that twenty-first-century economics thinks about what we do—because economists are finally realizing that we’re full-fledged human beings, not single-minded economic robots. And perhaps most important, it’s hard to reconcile with much of what we actually do at work—because for growing numbers of people, work is often creative, interesting, and self-directed rather than unrelentingly routine, boring, and other-directed. Taken together, these compatibility problems warn us that something’s gone awry in our motivational operating system.

  But in order to figure out exactly what, and as an essential step in fashioning a new one, we need to take a look at the bugs themselves.

  CHAPTER 2

  Seven Reasons Carrots and Sticks (Often) Don’t Work . . .

  An object in motion will stay in motion, and an object at rest will stay at rest, unless acted on by an outside force.

  That’s Newton’s first law of motion. Like Newton’s other laws, this one is elegant and simple—which is part of its power. Even people like me, who bumbled though high school physics, can understand it and can use it to interpret the world.

  Motivation 2.0 is similar. At its heart are two elegant and simple ideas:Rewarding an activity will get you more of it. Punishing an activity will get you less of it.

  And just as Newton’s principles can help us explain our physical environment or chart the path of a thrown ball, Motivation 2.0’s principles can help us comprehend our social surroundings and predict the trajectory of human behavior.

  But Newtonian physics runs into problems at the subatomic level. Down there—in the land of hadrons, quarks, and Schrödinger’s cat—things get freaky. The cool rationality of Isaac Newton gives way to the bizarre unpredictability of Lewis Carroll. Motivation 2.0 is similar in this regard, too. When rewards and punishments encounter our third drive, something akin to behavioral quantum mechanics seems to take over and strange things begin to happen.

  Of course, the starting point for any discussion of motivation in the workplace is a simple fact of life: People have to earn a living. Salary, contract payments, some benefits, a few perks are what I call “baseline rewards.” If someone’s baseline rewards aren’t adequate or equitable, her focus will be on the unfairness of her situation and the anxiety of her circumstance. You’ll get neither the predictability of extrinsic motivation nor the weirdness of intrinsic motivation. You’ll get very little motivation at all.

  But once we’re past that threshold, carrots and sticks can achieve precisely the opposite of their intended aims. Mechanisms designed to increase motivation can dampen it. Tactics aimed at boosting creativity can reduce it. Programs to promote good deeds can make them disappear. Meanwhile, instead of restraining negative behavior, rewards and punishments can often set it loose—and give rise to cheating, addiction, and dangerously myopic thinking.

  This is weird. And it doesn’t hold in all circumstances (about which more after this ch
apter). But as Edward Deci’s Soma puzzle experiment demonstrates, many practices whose effectiveness we take for granted produce counterintuitive results: They can give us less of what we want—and more of what we don’t want. These are the bugs in Motivation 2.0. And they rise to the surface whether we’re promising rupees in India, charging shekels in Israel, drawing blood in Sweden, or painting portraits in Chicago.

  LESS OF WHAT WE WANT

  One of the most enduring scenes in American literature offers an important lesson in human motivation. In Chapter 2 of Mark Twain’s The Adventures of Tom Sawyer, Tom faces the dreary task of whitewashing Aunt Polly’s 810-square-foot fence. He’s not exactly thrilled with the assignment. “Life to him seemed hollow, and existence but a burden,” Twain writes.

  But just when Tom has nearly lost hope, “nothing less than a great, magnificent inspiration” bursts upon him. When his friend Ben ambles by and mocks Tom for his sorry lot, Tom acts confused. Slapping paint on a fence isn’t a grim chore, he says. It’s a fantastic privilege—a source of, ahem, intrinsic motivation. The job is so captivating that when Ben asks to try a few brushstrokes himself, Tom refuses. He doesn’t relent until Ben gives up his apple in exchange for the opportunity.