When we encounter new information, we should force ourselves to do something with it. Write yourself a note explaining what you just learned, or figure out a small way to test an idea, or graph a series of data points onto a piece of paper, or force yourself to explain an idea to a friend. Every choice we make in life is an experiment—the trick is getting ourselves to see the data embedded in those decisions, and then to use it somehow so we learn from it.
TO MAKE BETTER DECISIONS:
• Envision multiple futures. By pushing yourself to imagine various possibilities—some of which might be contradictory—you’re better equipped to make wise choices.
• We can hone our Bayesian instincts by seeking out different experiences, perspectives, and other people’s ideas. By finding information and then letting ourselves sit with it, options become clearer.
[...] so one night, after putting the kids to bed, I sat at my laptop and hit the reply button, creating a series of responses. Then, as fast as I could, I typed a sentence within each email—any sentence at all—to get me going. For instance, a co-worker sent a note asking if I could join him at a meeting. I had put off replying because I didn’t want to attend. I knew the meeting would be long and boring. But I couldn’t completely ignore him. So I wrote one sentence in my response:
I can attend, but I’ll need to leave after twenty minutes.
I went through two dozen replies just like that, writing a short sentence in each one, hardly thinking about it. And then, I went back and filled in the rest of each email:
Sure, I can attend, but I’ll need to leave after twenty minutes.
I hope that’s okay.
I noticed two things: First, it was much easier to reply to an email once I had at least one sentence on the screen. Second, and more important, it was easier to get motivated when that first sentence was something that made me feel in control. When I told Jim that I could only stay for twenty minutes, it reminded me that I didn’t have to commit to his project if I didn’t want to. When I drafted a reply to someone asking me to come speak at a conference, I began by typing:
I would like to leave on Tuesday and be back in New York by Thursday night.
Which reinforced that I was in control of whether I attended or not.
Motivation becomes easier when we transform a chore into a choice. Doing so gives us a sense of control.
“Our brain wants to find a simple frame and stick with it, the same way it wants to make a binary decision,” Eric Johnson, the Columbia psychologist, told me. “That’s why teenagers get stuck thinking about breaking up with a boyfriend as, ‘Do I love him or not?’ rather than ‘Do I want to be in a relationship, or do I want to be able to leave for college?’ Or why, when you’re buying a car, you start thinking, ‘Do I want the power windows or the GPS?’ rather than ‘Am I sure I can afford this car?’
“But when we teach people a process for reframing choices, when we give them a series of steps that causes a decision to seem a little bit different than before,” said Johnson, “it helps them take more control of what’s going on inside their heads.”
One of the best ways to help people cast experiences in a new light is to provide a formal decision-making system—such as a flowchart, a prescribed series of questions, or the engineering design process—that denies our brains the easy options we crave. “Systems teach us how to force ourselves to make questions look unfamiliar,” said Johnson. “It’s a way to see alternatives.”
One important study of the power of such decision-making frames was published in 1984, after a researcher from Northwestern University asked a group of participants to list reasons why they should buy a VCR based on their own experiences. Volunteers generated dozens of justifications for such a purchase. Some said they felt a VCR would provide entertainment. Others saw it as an investment in their education or a way for their families to spend time together. Then those same volunteers were asked to generate reasons not to buy a VCR. They struggled to come up with arguments against the expenditure. The vast majority said they were likely to buy one sometime soon.
Next, the researcher asked a new group of volunteers to come up with a list of reasons against purchasing a VCR. No problem, they replied. Some said watching television distracted them from their families. Others said that movies were mindless, and they didn’t need the temptation. When those same people were then asked to list reasons for buying a VCR, they had trouble coming up with convincing reasons to make the purchase and said they were unlikely to ever buy one.
What interested the researcher was how much each group struggled to adopt an opposing viewpoint once they had an initial frame for making a decision. The two groups were demographically similar. They should have been equally interested in buying a VCR. At the very least, they should have generated equal numbers of reasons to buy or spurn the machines. But once a participant grabbed on to a decision-making frame—This is an investment in my education versus This is a distraction from my family—they found it hard to envision the choice in a different way. A VCR was either a tool for learning or a time-wasting distraction, based on how the question was framed. Similar results have been found in dozens of other experiments in which people were presented with decisions ranging from the vital, such as end-of-life choices, to the costly, such as buying a car. Once a frame is established, that context is hard to dislodge.
“The important step seems to be performing some kind of operation,” said Adam Alter, a professor at NYU who has studied disfluency. “If you make people use a new word in a sentence, they’ll remember it longer. If you make them write down a sentence with the word, they’ll start using it in conversations.” When Alter conducts experiments, he sometimes gives people instructions in a hard-to-read font because, as they struggle to make out the words, they read the text more carefully. “The initial difficulty in processing the text leads you to think more deeply about what you’re reading, so you spend more time and energy making sense of it,” he said. When you ask yourself a few questions about wine, or compare the fees on various 401(k) plans, the data becomes less monolithic and more like a series of decisions. When information is made disfluent, we learn more.
Mental scaffolds are like file cabinets filled with folders that help us store and access information when the need arises. If someone is handed a huge wine list at a restaurant, for instance, they’ll typically have no problem making a selection because their brain will automatically place what they know about wine into a scaffold of categories they can use to make binary decisions (Do I want a white or a red? White!), and then finer subcategories (Expensive or cheap? Cheap!) until they confront a final comparison (The six-dollar Chardonnay or the seven-dollar Sauvignon Blanc?) that draws upon what they have already learned about themselves (I like Chardonnay!). We do this so quickly that, most of the time, we’re hardly aware it’s occurring.
Information blindness occurs because of the way our brain’s capacity for learning has evolved. Humans are exceptionally good at absorbing information—as long as we can break data into a series of smaller and smaller pieces. This process is known as “winnowing” or “scaffolding.”
“The quality of people’s decisions generally gets better as they receive more relevant information. But then their brain reaches a breaking point when the data becomes too much. They start ignoring options or making bad choices or stop interacting with the information completely.”
In theory, the ongoing explosion in information should make the right answers more obvious. In practice, though, being surrounded by data often makes it harder to decide.
This inability to take advantage of data as it becomes more plentiful is called “information blindness.” Just as snow blindness refers to people losing the capacity to distinguish trees from hills under a blanket of powder, so information blindness refers to our mind’s tendency to stop absorbing data when there’s too much to take in.
Finally, remember that the relief accompanying a creative breakthrough, while sweet, can also blind us to seeing alternatives. It is critical to maintain some distance from what we create. Without self-criticism, without tension, one idea can quickly crowd out competitors. But we can regain that critical distance by forcing ourselves to critique what we’ve already done, by making ourselves look at it from a completely different perspective, by changing the power dynamics in the room or giving new authority to someone who didn’t have it before. Disturbances are essential, and we retain clear eyes by embracing destruction and upheaval, as long as we’re sensitive to making the disturbance the right size.
Second, recognize that the panic and stress you feel as you try to create isn’t a sign that everything is falling apart. Rather, it’s the condition that helps make us flexible enough to seize something new. Creative desperation can be critical; anxiety is what often pushes us to see old ideas in new ways. The path out of that turmoil is to look at what you know, to reinspect conventions you’ve seen work and try to apply them to fresh problems. The creative pain should be embraced.
If you want to become a broker and increase the productivity of your own creative process, there are three things that can help: First, be sensitive to your own experiences. Pay attention to how things make you think and feel. That’s how we distinguish clichés from true insights.
Creativity can’t be reduced to a formula. At its core, it needs novelty, surprise, and other elements that cannot be planned in advance to seem fresh and new. There is no checklist that, if followed, delivers innovation on demand.
But the creative process is different. We can create the conditions that help creativity to flourish. We know, for example, that innovation becomes more likely when old ideas are mixed in new ways. We know the odds of success go up when brokers—people with fresh, different perspectives, who have seen ideas in a variety of settings—draw on the diversity within their heads. We know that, sometimes, a little disturbance can help jolt us out of the ruts that even the most creative thinkers fall into, as long as those shake-ups are the right size.
Human creativity, of course, is different from biological diversity. It’s an imprecise analogy to compare a falling tree in the Australian rain forest to a change in management at Disney. Let’s play with the comparison for a moment, though, because it offers a valuable lesson: When strong ideas take root, they can sometimes crowd out competitors so thoroughly that alternatives can’t prosper. So sometimes the best way to spark creativity is by disturbing things just enough to let some light through.
It seemed as if nature’s creative capacities depended on some kind of periodic disturbance—like a tree fall or an occasional storm—that temporarily upset the natural environment. But the disturbance couldn’t be too small or too big. It had to be just the right size. “Intermediate disturbances are critical,” Connell told me.
Within biology, this has become known as the intermediate disturbance hypothesis, which holds that “local species diversity is maximized when ecological disturbance is neither too rare nor too frequent.”
“Creativity is just connecting things,” Apple cofounder Steve Jobs said in 1996. “When you ask creative people how they did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had and synthesize new things. And the reason they were able to do that was that they’ve had more experiences or they have thought more about their experiences than other people.” People become creative brokers, in other words, when they learn to pay attention to how things make them react and feel.
“A lot of the people we think of as exceptionally creative are essentially intellectual middlemen,” said Uzzi. “They’ve learned how to transfer knowledge between different industries or groups. They’ve seen a lot of different people attack the same problems in different settings, and so they know which kinds of ideas are more likely to work.”
Annie knows a lot about Bayesian thinking from graduate school, and she uses it in poker games. “When I play against someone I’ve never met before, the first thing I do is start thinking about base rates,” she told me. “To someone who has never studied Bayes’ rule, the way I play might seem like I’m prejudiced, because if I’m sitting across from, say, a forty-year-old businessman, I’m going to assume all he cares about is telling his friends he played against pros and he doesn’t really care about winning, so he’ll take lots of risks. Or, if I’m sitting across from a twenty-two-year-old in a poker T-shirt, I’m going to assume he learned to play online so he’s got a tight, limited game.
“But the difference between prejudice and Bayesian thinking is that I try to improve my assumptions as we go along.
So the next time a friend misses out on a promotion, ask him why. The next time a deal falls through, call up the other side to find out what you did wrong. The next time you have a bad day or you snap at your spouse, don’t simply tell yourself that things will go better next time. Instead, force yourself to really figure out what happened.
Then use those insights to forecast more potential futures, to dream up more possibilities of what might occur. You’ll never know with 100 percent certainty how things will turn out. But the more you force yourself to envision potential futures, the more you learn about which assumptions are certain or flimsy, the better your odds of making a great decision next time.
This, ultimately, is one of the most important secrets to learning how to make better decisions. Making good choices relies on forecasting the future. Accurate forecasting requires exposing ourselves to as many successes and disappointments as possible. We need to sit in crowded and empty theaters to know how movies will perform; we need to spend time around both babies and old people to accurately gauge life spans; and we need to talk to thriving and failing colleagues to develop good business instincts.
This is hard, because success is easier to stare at. People tend to avoid asking friends who were just fired rude questions; we’re hesitant to interrogate divorced colleagues about what precisely went wrong. But calibrating your base rate requires learning from both the accomplished and the humbled.
“The best entrepreneurs are acutely conscious of the risks that come from only talking to people who have succeeded,” said Don Moore, the Berkeley professor who participated in the GJP and who also studies the psychology of entrepreneurship. “They are obsessed with spending time around people who complain about their failures, the kinds of people the rest of us usually try to avoid.”
Many successful people, in contrast, spend an enormous amount of time seeking out information on failures. They read inside the newspaper’s business pages for articles on companies that have gone broke. They schedule lunches with colleagues who haven’t gotten promoted, and then ask them what went wrong. They request criticisms alongside praise at annual reviews. They scrutinize their credit card statements to figure out why, precisely, they haven’t saved as much as they hoped. They pick over their daily missteps when they get home, rather than allowing themselves to forget all the small errors. They ask themselves why a particular call didn’t go as well as they had hoped, or if they could have spoken more succinctly at a meeting. We all have a natural proclivity to be optimistic, to ignore our mistakes and forget others’ tiny errors. But making good predictions relies on realistic assumptions, and those are based on our experiences. If we pay attention only to good news, we’re handicapping ourselves.
So how do we get the right assumptions? By making sure we are exposed to a full spectrum of experiences. Our assumptions are based on what we’ve encountered in life, but our experiences often draw on biased samples. In particular, we are much more likely to pay attention to or remember successes and forget about failures. Many of us learn about the business world, for instance, by reading newspapers and magazines. We most frequently go to busy restaurants and see the most popular movies. The problem is that such experiences disproportionately expose us to success. Newspapers and magazines tend to devote more coverage to start-ups that were acquired for $1 billion, and less to the hundreds of similar companies that went bankrupt. We hardly notice the empty restaurants we pass on the way to our favorite, crowded pizza place. We become trained, in other words, to notice success and then, as a result, we predict successful outcomes too often because we’re relying on experiences and assumptions that are biased toward all the successes we’ve seen—rather than the failures we’ve overlooked.
“Probabilities are the closest thing to fortune-telling,” Howard said. “But you have to be strong enough to live with what they tell you might occur.”
When Annie started playing poker seriously, it was her brother who sat her down and explained what separated the winners from everyone else. Losers, Howard said, are always looking for certainty at the table. Winners are comfortable admitting to themselves what they don’t know. In fact, knowing what you don’t know is a huge advantage—something that can be used against other players.
It’s great to be 100 percent certain you love your girlfriend right now, but if you’re thinking of proposing to her, wouldn’t you rather know the odds of staying married over the next three decades?” said Don Moore, a professor at UC-Berkeley’s Haas School of Business who helped run the GJP. “I can’t tell you precisely whether you’ll be attracted to each other in thirty years. But I can generate some probabilities about the odds of staying attracted to each other, and probabilities about how your goals will coincide, and statistics on how having children might change the relationship, and then you can adjust those likelihoods based on your experiences and what you think is more or less likely to occur, and that’s going to help you predict the future a little bit better.
“In the long run, that’s pretty valuable, because even though you know with 100 percent certainty that you love her right now, thinking probabilistically about the future can force you to think through things that might be fuzzy today, but are really important over time. It forces you to be honest with yourself, even if part of that honesty is admitting there are things you aren’t sure about.”
Learning to think probabilistically requires us to question our assumptions and live with uncertainty. To become better at predicting the future—at making good decisions—we need to know the difference between what we hope will happen and what is more and less likely to occur.
Simply exposing participants to probabilistic training was associated with as much as a 50 percent increase in the accuracy of their predictions, the GJP researchers wrote.
The GJP’s training modules instructed people in various methods for combining odds and comparing futures. Throughout, a central idea was repeated again and again. The future isn’t one thing. Rather, it is a multitude of possibilities that often contradict one another until one of them comes true. And those futures can be combined in order for someone to predict which one is more likely to occur.
The lessons on probabilistic thinking offered by the GJP had instructed participants to think of the future not as what’s going to happen, but rather as a series of possibilities that might occur. It taught them to envision tomorrow as an array of potential outcomes, all of which had different odds of coming true. “Most people are sloppy when they think about the future,” said Lyle Ungar, a professor of computer science at the University of Pennsylvania who helped oversee the GJP. “They say things like, ‘It’s likely we’ll go to Hawaii for vacation this year.’ Well, does that mean that it’s 51 percent certain? Or 90 percent? Because that’s a big difference if you’re buying nonrefundable tickets.” The goal of the GJP’s probabilistic training was to show people how to turn their intuitions into statistical estimates.
A culture of commitment and trust isn’t a magic bullet. It doesn’t guarantee that a product will sell or an idea will bear fruit. But it’s the best bet for making sure the right conditions are in place when a great idea comes along.
That said, there are good reasons companies don’t decentralize authority. There is a powerful logic behind investing power in only a few hands. At NUMMI, a small group of disgruntled workers could have bankrupted the firm by pulling andon cords needlessly. Inside the FBI, a misguided programmer could have built the wrong computer system. An agent might have followed the wrong hunch. But, in the end, the rewards of autonomy and commitment cultures outweigh the costs. The bigger misstep is when there is never an opportunity for an employee to make a mistake.
Employees work smarter and better when they believe they have more decisionmaking authority and when they believe their colleagues are committed to their success. A sense of control can fuel motivation, but for that drive to produce insights and innovations, people need to know their suggestions won’t be ignored, that their mistakes won’t be held against them. And they need to know that everyone else has their back.
Among filmmakers, the “Pixar method” was modeled specifically on Toyota’s management techniques and became famous for empowering low-level animators to make critical choices. When Pixar’s leadership was asked to take over Disney Animation in 2008, executives introduced themselves with what became known as “the Toyota Speech,” “in which I described the car company’s commitment to empowering its employees and letting people on the assembly line make decisions when they encountered problems,” Pixar cofounder Ed Catmull later wrote. “I stressed that no one at Disney needed to wait for permission to come up with solutions. What is the point of hiring smart people, we asked, if you don’t empower them to fix what’s broken?”
In 2001, a group of computer programmers had gathered at a ski lodge in Utah to write a set of principles, called the “Manifesto for Agile Software Development,” that adapted Toyota’s methods and lean manufacturing to how software was created. The Agile methodology, as it came to be known, emphasized collaboration, frequent testing, rapid iteration, and pushing decision making to whoever was closest to a problem.
[...] four years after NUMMI opened, the recession hit the auto industry. The stock market crashed. Unemployment was rising. Car sales plummeted. NUMMI’s managers estimated they needed to reduce production by 40 percent. “Everyone was saying there were going to be layoffs,” said Smith, the UAW rep. Instead, the plant’s top sixty-five executives all took pay cuts. Assembly line workers were reassigned to janitorial duties or landscaping, or sent into the paint room to scrape air vents instead of let go. The company proved it was committed.
“After that, workers were willing to do anything for the company,” Smith said. “Four separate sales slumps over thirty years, and NUMMI never did layoffs once. And each time, when the business finally came back, everyone worked harder than before.”
“If people started pulling andons for no good reason, the plant would have fallen apart,” said Smith. Everyone knew it still cost thousands of dollars each minute a line was stopped, “and that anyone could stop the line, at any time, without penalty. So employees could bankrupt the place if they wanted to.
“Once you’re entrusted with that kind of authority, you can’t help feel a sense of responsibility,” said Smith. “The most junior workers didn’t want NUMMI to go bankrupt, and the management didn’t want that, and so, suddenly, everyone was on the same side of the table.” And as workers were empowered to make more choices, their motivation skyrocketed.
Toyoda faced Joe and bowed. He began speaking in Japanese.
“Joe, please forgive me,” a lieutenant translated. “I have done a poor job of instructing your managers of the importance of helping you pull the cord when there is a problem. You are the most important part of this plant. Only you can make every car great. I promise I will do everything in my power to never fail you again.”
One of the reasons commitment cultures were successful, it seemed, was because a sense of trust emerged among workers, managers, and customers that enticed everyone to work harder and stick together through the setbacks that are inevitable in any industry. Most commitment companies avoided layoffs unless there was no other alternative. They invested heavily in training. There were higher levels of teamwork and psychological safety. Commitment companies might not have had lavish cafeterias, but they offered generous maternity leaves, daycare programs, and work-from-home options. These initiatives were not immediately cost-effective, but commitment firms valued making employees happy over quick profits—and as a result, workers tended to turn down higher-paying jobs at rival firms. And customers stayed loyal because they had relationships that stretched over years. Commitment firms dodged one of the business world’s biggest hidden costs: the profits that are lost when an employee takes clients or insights to a competitor.
“Good employees are always the hardest asset to find,” said Baron. “When everyone wants to stick around, you’ve got a pretty strong advantage.”
“Venture capitalists love star firms because when you’re investing in a portfolio of companies, all you need are a few huge successes,” Baron told me. “But if you’re an entrepreneur and you’re betting on just one company, then the data says you’re much better off with a commitment-focused culture.”
[...] when Baron and Hannan looked at their data, they found the only culture that was a consistent winner were the commitment firms. Hands down, a commitment culture outperformed every other type of management style in almost every meaningful way. “Not one of the commitment firms we studied failed,” said Baron. “None of them, which is amazing in its own right. But they were also the fastest companies to go public, had the highest profitability ratios, and tended to be leaner, with fewer middle managers, because when you choose employees slowly, you have time to find people who excel at self-direction.” Employees in commitment firms wasted less time on internal rivalries because everyone was committed to the company, rather than to personal agendas. Commitment companies tended to know their customers better than other kinds of firms, and as a result could detect shifts in the market faster.
[...] the star model produced some of the study’s biggest winners. As it turned out, putting all the smartest people in the same room could yield vast influence and wealth. But, unexpectedly, star firms also failed in record numbers. As a group, they were less likely to make it to an IPO than any other category, and they were often beset by internal rivalries. As anyone who has ever worked in such a company knows, infighting is often more vicious inside a star-focused firm, because everyone wants to be the star.
The final category was known as the “commitment” model, and it was a throwback to an age when people happily worked for one company their entire life. “Commitment CEOs say things like, ‘I want to build the kind of company where people only leave when they retire or die,’ ” said Baron. “That doesn’t necessarily mean the company is stodgy, but it does imply a set of values that might prioritize slow and steady growth.”
Engineering-focused cultures are powerful because they allow firms to grow quickly. “Think of how fast Facebook expanded,” said Baron. “When everyone comes from a similar background and mindset, you can rely on common social norms to keep everyone on the same path.”
“Our basic philosophy was that no one goes to work wanting to suck. If you put people in a position to succeed, they will.”
“Every person in an organization has the right to be the company’s top expert at something,” John Shook, who trained Madrid as one of Toyota’s first Western employees, told me. “If I’m attaching mufflers or I’m a receptionist or a janitor, I know more about exhaust systems or receiving people or cleaning offices than anyone else, and it’s incredibly wasteful if a company can’t take advantage of that knowledge. Toyota hates waste. The system was built to exploit everyone’s expertise.”
[...] the Toyota Production System—which in the United States would become known as “lean manufacturing”—relied on pushing decision making to the lowest possible level. Workers on the assembly line were the ones who saw problems first. They were closest to the glitches that were inevitable in any manufacturing process. So it only made sense to give them the greatest authority in finding solutions.
One day he shadowed a worker who, midway through a shift, told a manager he had an idea for a new tool that would help him install struts. The manager walked to the machine shop and returned fifteen minutes later with a prototype. The worker and manager refined the design throughout the day. The next morning, everyone had their own versions of the tool waiting at their stations.
When the screw gun squealed inside the Japanese plant, though, something unexpected happened. The worker who made the mistake reached above his head and pulled a hanging cable that turned on a spinning yellow light. He then reversed the direction of his screw gun and pulled the bolt out of the doorframe, grabbed another tool, and used it to smooth the hole’s threads. At this point, a manager walked over, stood behind the worker, and began asking questions. The worker ignored his boss except to bark out a few orders, and then grabbed another tool to rethread the hole. The conveyor belt was still moving, but the worker hadn’t finished his repair. When the door got to the end of the worker’s station, the entire assembly line stopped. Madrid had no idea what was going on.
Another man, clearly a senior manager, came over. Instead of yelling, he laid out a new bolt and equipment on a tray, like a nurse in an operating room. The worker kept issuing orders to his superiors. In Fremont, that would have gotten him slugged. Here, though, there were no angry shouts or anxious whispers. The other men on the line were calmly standing in place or double-checking parts they had just installed. No one seemed surprised at what was happening. Then the worker completed his rethreading, put a new bolt in the door, and pulled the cord above his head again. The assembly line started moving at normal speed. Everyone went back to work.
In addition to having audacious ambitions and plans that are thorough, we still need, occasionally, to step outside the day-to-day and consider if we’re moving toward goals that make sense. We still need to think.
[...] one solution is writing to-do lists that pair stretch goals and SMART goals. Come up with a menu of your biggest ambitions. Dream big and stretch. Describe the goals that, at first glance, seem impossible, such as starting a company or running a marathon.
Then choose one aim and start breaking it into short-term, concrete steps. Ask yourself: What realistic progress can you make in the next day, week, month? How many miles can you realistically run tomorrow and over the next three weeks? What are the specific, short-term steps along the path to bigger success? What timeline makes sense? Will you open your store in six months or a year? How will you measure your progress? Within psychology, these smaller ambitions are known as “proximal goals,” and repeated studies have shown that breaking a big ambition into proximal goals makes the large objective more likely to occur.
“To-do lists are great if you use them correctly,” Timothy Pychyl, a psychologist at Carleton University, told me. “But when people say things like ‘I sometimes write down easy items I can cross off right away, because it makes me feel good,’ that’s exactly the wrong way to create a to-do list. That signals you’re using it for mood repair, rather than to become productive.”
The problem with many to-do lists is that when we write down a series of short-term objectives, we are, in effect, allowing our brains to seize on the sense of satisfaction that each task will deliver. We are encouraging our need for closure and our tendency to freeze on a goal without asking if it’s the right aim. The result is that we spend hours answering unimportant emails instead of writing a big, thoughtful memo—because it feels so satisfying to clean out our in-box.
In one experiment conducted at Duke University, for instance, varsity athletes were asked to run around a track and, when signaled, get as close as possible to a finish line 200 meters away within ten seconds. The runners in the study all knew, simply by looking at the distance they were being asked to cover, that the goal was absurd. No person has ever run anything close to 200 meters in ten seconds. The athletes made it 59.6 meters, on average, during their sprint.
A few days later, those same participants were presented with the same task, but this time the finish line was only 100 meters away. The goal was still audacious—but it was within the realm of possibility. (Usain Bolt ran 100 meters in 9.58 seconds in 2009.) During this trial, the runners made it, on average, 63.1 meters in ten seconds—“a large difference by track and field standards,” the researchers noted.
This difference in performance was explained by the fact that the shorter distance, while still challenging, lent itself to the kind of methodical planning and mental models that experienced runners are accustomed to using. The shorter distance, in other words, allowed the runners to participate in the athletic equivalent of breaking a stretch goal into SMART components. “All runners in our sample engaged in regular workouts,” the researchers wrote, and so when confronted with running 100 meters in ten seconds, they knew how to wrestle with the task. They broke it into pieces and treated it like they would other sprints. They started strong, and paced off other runners, and then pushed themselves as hard as possible in the final seconds. But when they were confronted with running 200 meters in ten seconds, there was no practical approach. There was no way to break the problem into manageable parts. There were no SMART criteria they could apply. It was simply impossible.
There is an important caveat to the power of stretch goals, however. Studies show that if a stretch goal is audacious, it can spark innovation. It can also cause panic and convince people that success is impossible because the goal is too big. There is a fine line between an ambition that helps people achieve something amazing and one that crushes morale. For a stretch goal to inspire, it often needs to be paired with something like the SMART system.
The reason why we need both stretch goals and SMART goals is that audaciousness, on its own, can be terrifying. It’s often not clear how to start on a stretch goal. And so, for a stretch goal to become more than just an aspiration, we need a disciplined mindset to show us how to turn a far-off objective into a series of realistic short-term aims. People who know how to build SMART goals have often been habituated into cultures where big objectives can be broken into manageable parts, and so when they encounter seemingly outsized ambitions, they know what to do. Stretch goals, paired with SMART thinking, can help put the impossible within reach.
Stretch goals “serve as jolting events that disrupt complacency and promote new ways of thinking,” a group of researchers wrote in Academy of Management Review business journal in 2011. “By forcing a substantial elevation in collective aspirations, stretch goals can shift attention to possible new futures and perhaps spark increased energy in the organization. They thus can prompt exploratory learning through experimentation, innovation, broad search, or playfulness.”
By 1994, every GE employee within GE had participated in at least one Work-Out. As profits and productivity rose, executives at other companies began imitating the Work-Out system inside their own firms. By 1995, there were hundreds of companies conducting Work-Outs. Kerr joined GE full-time in 1994 and eventually became the company’s “chief learning officer.”
“The Work-Outs were successful because they balanced the psychological influence of immediate goals with the freedom to think about bigger things,” said Kerr. “That’s critical. People respond to the conditions around them. If you’re being constantly told to focus on achievable results, you’re only going to think of achievable goals. You’re not going to dream big.”
Aims such as SMART goals “can cause [a] person to have tunnel vision, to focus more on expanding effort to get immediate results,” Locke and Latham wrote in 1990. Experiments have shown that people with SMART goals are more likely to seize on the easiest tasks, to become obsessed with finishing projects, and to freeze on priorities once a goal has been set. “You get into this mindset where crossing things off your to-do list becomes more important than asking yourself if you’re doing the right things,” said Latham.
[...] an instinct for decisiveness is great—until it’s not. When people rush toward decisions simply because it makes them feel like they are getting something done, missteps are more likely to occur.
The “need for closure introduces a bias into the judgmental process,” a team of researchers wrote in Political Psychology in 2003. A high need for closure has been shown to trigger close-mindedness, authoritarian impulses, and a preference for conflict over cooperation. Individuals with a high need for closure “may display considerable cognitive impatience or impulsivity: They may ‘leap’ to judgment on the basis of inconclusive evidence and exhibit rigidity of thought and reluctance to entertain views different from their own,” the authors of the need for closure scale, Arie Kruglanski and Donna Webster, wrote in 1996.
The need for cognitive closure, in many settings, can be a great strength. People who have a strong urge for closure are more likely to be self-disciplined and seen as leaders by their peers. An instinct to make a judgment and then stick with it forestalls needless second-guessing and prolonged debate.
“You can’t delegate thinking,” de Crespigny told me. “Computers fail, checklists fail, everything can fail. But people can’t. We have to make decisions, and that includes deciding what deserves our attention. The key is forcing yourself to think. As long as you’re thinking, you’re halfway home.”
To become genuinely productive, we must take control of our attention; we must build mental models that put us firmly in charge. When you’re driving to work, force yourself to envision your day. While you’re sitting in a meeting or at lunch, describe to yourself what you’re seeing and what it means. Find other people to hear your theories and challenge them. Get in a pattern of forcing yourself to anticipate what’s next. If you are a parent, anticipate what your children will say at the dinner table. Then you’ll notice what goes unmentioned or if there’s a stray comment that you should see as a warning sign.
If you want to do a better job of paying attention to what really matters, of not getting overwhelmed and distracted by the constant flow of emails and conversations and interruptions that are part of every day, of knowing where to focus and what to ignore, get into the habit of telling yourself stories. Narrate your life as it’s occurring, and then when your boss suddenly asks a question or an urgent note arrives and you have only minutes to reply, the spotlight inside your head will be ready to shine the right way.
The Qantas plane flying that day had the same auto-flight systems as the Air France airplane that had crashed into the sea. But the pilots were very different. Even before Captain Richard Champion de Crespigny stepped on board Qantas Flight 32, he was drilling his crew in the mental models he expected them to use.
“I want us to envision the first thing we’ll do if there’s a problem,” he told his copilots as they rode in a van from the Fairmont hotel to Singapore Changi Airport. “Imagine there’s an engine failure. Where’s the first place you’ll look?” The pilots took turns describing where they would turn their eyes. De Crespigny conducted this same conversation prior to every flight. His copilots knew to expect it. He quizzed them on what screens they would stare at during an emergency, where their hands would go if an alarm sounded, whether they would turn their heads to the left or stare straight ahead. “The reality of a modern aircraft is that it’s a quarter million sensors and computers that sometimes can’t tell the difference between garbage and good sense,” de Crespigny later told me. He’s a brusque Australian, a cross between Crocodile Dundee and General Patton. “That’s why we have human pilots. It’s our job to think about what might happen, instead of what is.”
The economists figured the superstars were pickier because they were seeking out assignments that were similar to previous work they had done. Conventional wisdom holds that productivity rises when people do the same kind of tasks over and over. Repetition makes us faster and more efficient because we don’t have to learn fresh skills with each new assignment. But as the economists looked more closely, they found the opposite: The superstars weren’t choosing tasks that leveraged existing skills. Instead, they were signing up for projects that required them to seek out new colleagues and demanded new abilities. That’s why the superstars worked on only five projects at a time: Meeting new people and learning new skills takes a lot of additional hours.
“You can think about your brain’s attention span like a spotlight that can go wide and diffused, or tight and focused,” said David Strayer, a cognitive psychologist at the University of Utah. Our attention span is guided by our intentions. We choose, in most situations, whether to focus the spotlight or let it be relaxed. But when we allow automated systems, such as computers or autopilots, to pay attention for us, our brains dim that spotlight and allow it to swing wherever it wants. This is, in part, an effort by our brains to conserve energy. The ability to relax in this manner gives us huge advantages: It helps us subconsciously control stress levels and makes it easier to brainstorm, it means we don’t have to constantly monitor our environment, and it helps us get ready for big cognitive tasks. Our brains automatically seek out opportunities to disconnect and unwind.
Project Oxygen found that a good manager (1) is a good coach; (2) empowers and does not micromanage; (3) expresses interest and concern in subordinates’ success and well-being; (4) is results oriented; (5) listens and shares information; (6) helps with career development; (7) has a clear vision and strategy; (8) has key technical skills.
“A couple of months ago, we were in a meeting where I made a mistake,” Julia Rozovsky told me. “Not a huge mistake, but an embarrassing one, and afterward, I sent out a note explaining what had gone wrong, why it had happened, and what we were doing to resolve it. Right afterward, I got an email back from a team member that just said, ‘Ouch.’
“It was like a punch to the gut. I was already upset about making this mistake, and this note totally played on my insecurities. But because of all the work we’ve done, I pinged the person back and said, ‘Nothing like a good Ouch to destroy psychological safety in the morning!’ And he wrote back and said, ‘I’m just testing your resilience.’ That could have been the wrong thing to say to someone else, but he knew it was exactly what I needed to hear. With one thirty-second interaction, we diffused the tension.
“It’s funny to do a project on team effectiveness while working on a team, because we get to test everything we’re learning as we go along. What I’ve realized is that as long as everyone feels like they can talk and we’re really demonstrating that we want to hear each other, you feel like everyone’s got your back.”
“I come from a quantitative background. If I’m going to believe something, you need to give me data to back it up,” said Sagnik Nandy, who as chief of Google Analytics Engineering heads one of the company’s biggest teams. “So seeing this data has been a game changer for me. Engineers love debugging software because we know we can get 10 percent more efficiency by just making a few tweaks. But we never focus on debugging human interactions. We put great people together and hope it will work, and sometimes it does and sometimes it doesn’t, and most of the time we don’t know why. Aristotle let us debug our people. It’s totally changed how I run meetings. I’m so much more conscious of how I model listening now, or whether I interrupt, or how I encourage everyone to speak.”
One of the easiest ways to gauge social sensitivity is to show someone photos of people’s eyes and ask them to describe what that person is thinking or feeling—the empathy test described previously. This is a “test of how well the participant can put themselves into the mind of the other person, and ‘tune in’ to their mental state,” wrote the creator of the “Reading the Mind in the Eyes” test, Simon Baron-Cohen of the University of Cambridge. While men, on average, correctly guess the emotion of the person in the photo only 52 percent of the time, women typically guess right 61 percent.
There were, however, two behaviors that all the good teams shared.
First, all the members of the good teams spoke in roughly the same proportion, a phenomenon the researchers referred to as “equality in distribution of conversational turn-taking.” In some teams, for instance, everyone spoke during each task. In other groups, conversation ebbed from assignment to assignment—but by the end of the day, everyone had spoken roughly the same amount.
“As long as everyone got a chance to talk, the team did well,” said Woolley. “But if only one person or a small group spoke all the time, the collective intelligence declined. The conversations didn’t need to be equal every minute, but in aggregate, they had to balance out.”
Second, the good teams tested as having “high average social sensitivity”—a fancy way of saying that the groups were skilled at intuiting how members felt based on their tone of voice, how people held themselves, and the expressions on their faces.
The researchers eventually concluded that the good teams had succeeded not because of innate qualities of team members, but because of how they treated one another. Put differently, the most successful teams had norms that caused everyone to mesh particularly well.
The group that created Saturday Night Live came together so successfully, this theory goes, because a communal culture replaced individual needs. There were shared experiences (“We were all the kids who didn’t get to sit at the popular table in high school,” Beatts told me); common social networks (“Lorne was a cult leader,” said writer Bruce McCall. “As long as you had a Moonie-like devotion to the group, you were fine.”); and group needs trumped individual egos (“I don’t mean this in a bad way, but we were Guyana on the seventeenth floor,” said Zweibel. “It was a stalag.”).”
“The units with the strongest sense of teamwork would have the lowest error rates.” Except, when she tabulated her data, Edmondson found exactly the opposite. The wards with the strongest team cohesion had far more errors. She checked the data again. It didn’t make any sense. Why would strong teams make more mistakes?
Confused, Edmondson decided to look at these nurses’ responses, question by question, alongside the error rates to see if any explanations emerged. Edmondson had included one survey question that inquired specifically about the personal risks associated with making errors. She asked people to agree or disagree with the statement: “If you make a mistake in this unit, it is held against you.” Once she compared the data from that question with error incidence, she realized what was going on. It wasn’t that wards with strong teams were making more mistakes. Rather, it was that nurses who belonged to strong teams felt more comfortable reporting their mistakes. The data indicated that one particular norm—whether people were punished for missteps—influenced if they were honest after they screwed up.
Group norms, the researchers on Project Aristotle concluded, were the answer to improving Google’s teams. “The data finally started making sense,” said Dubey. “We had to manage the how of teams, not the who.”
There is strong evidence that group norms play a critical role in shaping the emotional experience of participating in a team. Research by psychologists from Yale, Harvard, Berkeley, the University of Oregon, and elsewhere indicate that norms determine whether we feel safe or threatened, enervated or excited, and motivated or discouraged by our teammates. Julia’s study group at Yale, for instance, felt draining because the norms—the tussles over leadership, the pressure to constantly demonstrate expertise, the tendency to critique—had put her on guard. In contrast, the norms of her case competition team—enthusiasm for one another’s ideas, withholding criticisms, encouraging people to take a leadership role or hang back as they wanted—allowed everyone to be friendly and unconstrained. Coordination was easy.
The Project Aristotle researchers went back to their data and analyzed it again, this time looking for norms. They found that some teams consistently allowed people to interrupt one another. Others enforced taking conversational turns. Some teams celebrated birthdays and began each meeting with a few minutes of informal chitchat. Others got right to business. There were teams that contained extroverts who hewed to the group’s sedate norms whenever they assembled, and others where introverts came out of their shells as soon as meetings began.
Google had devoted enormous resources to studying workers’ happiness and productivity. The People Analytics group, part of Google’s human resources division, helped examine if employees were satisfied with their bosses and coworkers, whether they felt overworked, intellectually challenged, and fairly paid, whether their work-life balance was actually balancing out, as well as hundreds of other variables. The division helped with hiring and firing decisions, and its analysts provided insights into who should be promoted and who, perhaps, had risen too fast. In the years before Julia joined the group, People Analytics had determined that Google needed to interview a job applicant only four times to predict, with 86 percent confidence, if they would be a good hire. The division had successfully pushed to increase paid maternity leave from twelve to eighteen weeks because computer models indicated that would reduce the frequency of new mothers quitting by 50 percent. At the most basic level, the division’s goal was to make life at Google a little bit better and a lot more productive.
“We met every night for a week. I thought we should fill the shop with nap pods, and someone else said it should become a game room, and there was also some kind of clothing swap idea. We had lots of crazy ideas.” No one ever shot down a suggestion, not even the nap pods. Julia’s study group, as part of their class assignments, had also engaged in a fair amount of brainstorming, “but if I had ever mentioned something like a nap pod, somebody would have rolled their eyes and come up with fifteen reasons why it was a dumb idea. And it was a dumb idea. But my case team loved it. We always loved each other’s dumb ideas. We spent an hour figuring out how nap pods could make money by selling accessories like earplugs.”
In 2010, twenty-two years after her South American vacation with Robert, Viola was diagnosed with ovarian cancer. It took two years for the disease to consume her. At every step, Robert was there, helping her out of bed in the morning and reminding her to take her medications at night. He asked her questions to distract her from the pain and fed her when she became feeble. When Viola finally passed, Robert sat by her empty bed for days. His children, worried he was slipping back into apathy, suggested another visit with the neurologist in New Orleans. Perhaps the doctor would recommend something to forestall his listlessness from returning.
No, Robert replied. It wasn’t apathy keeping him indoors. He just needed some time to reflect on sixty-two years of marriage. Viola had helped Robert build a life—and then, when everything had slipped from his grasp, she helped him rebuild it again. He just wanted to honor that by pausing for a few days, he told his kids. A week later, he left the house and came over for brunch. Afterward, he babysat his grandchildren. Robert passed away twenty-four months later, in 2014. He was active, his obituary noted, until the end.
[...] we need to prove to ourselves that our choices are meaningful. When we start a new task, or confront an unpleasant chore, we should take a moment to ask ourselves “why.” Why are we forcing ourselves to climb up this hill? Why are we pushing ourselves to walk away from the television? Why is it so important to return that email or deal with a coworker whose requests seem so unimportant?
Once we start asking why, those small tasks become pieces of a larger constellation of meaningful projects, goals, and values. We start to recognize how small chores can have outsized emotional rewards, because they prove to ourselves that we are making meaningful choices, that we are genuinely in control of our own lives. That’s when self-motivation flourishes: when we realize that replying to an email or helping a coworker, on its own, might be relatively unimportant. But it is part of a bigger project that we believe in, that we want to achieve, that we have chosen to do. Self-motivation, in other words, is a choice we make because it is part of something bigger and more emotionally rewarding than the immediate task that needs doing.
28 December 2018
This theory suggests how we can help ourselves and others strengthen our internal locus of control. We should reward initiative, congratulate people for self-motivation, celebrate when an infant wants to feed herself. We should applaud a child who shows defiant, self-righteous stubbornness and reward a student who finds a way to get things done by working around the rules.
Viola Philippe, the wife of the onetime auto parts tycoon of Louisiana, was something of an expert on motivation herself before she and Robert flew to South America. She had been born with albinism—her body did not produce the enzyme tyrosinase, critical in the production of melanin—and as a result, her skin, hair, and eyes contained no pigment, and her eyesight was poor. She was legally blind, and could read only by putting her face very close to a page and using a magnifying glass. “You have never met a more determined person, though,” her daughter, Roxann, told me. “She could do anything.”
When Viola was a girl, the school district had tried to put her into remedial classes despite the fact that it was her eyes, not her brain, that had problems. But she refused to leave the classroom where her friends sat. She stayed in that room until administrators relented. After she graduated, she went to Louisiana State University and told the school she expected them to provide someone to read textbooks to her aloud. The school complied. During her sophomore year, she met Robert, who soon dropped out to start washing and greasing cars for a local Ford dealer. He encouraged her to quit school, as well. She politely declined and got her degree. They were married in December 1950, four months after she graduated.
He got another job, but the lack of camaraderie among his colleagues was disappointing. No one seemed motivated to excel. So in 2015, he reenlisted. “I missed that constant reminder that I can do anything,” he told me. “I missed people pushing me to choose a better me.”
A group of residents at a nursing home in Little Rock violated the institution’s rules by moving furniture around to personalize their bedrooms. Because wardrobes were attached to the walls, they used a crowbar—appropriated from a tool closet—to wrench their dressers free. In response, an administrator called a meeting and said there was no need to undertake independent redecorations; if the residents needed help, the staff would provide it. The residents informed the administrator that they didn’t want any assistance, didn’t need permission, and intended to continue doing whatever they damn well pleased.
These small acts of defiance were, in the grand scheme of things, relatively minor. But they were psychologically powerful because the subversives saw the rebellions as evidence that they were still in control of their own lives. The subversives walked, on average, about twice as much as other nursing home residents. They ate about a third more. They were better at complying with doctors’ orders, taking their medications, visiting the gym, and maintaining relationships with family and friends. These residents had arrived at the nursing homes with just as many health problems as their peers, but once inside, they lived longer, reported higher levels of happiness, and were far more active and intellectually engaged.
If you can link something hard to a choice you care about, it makes the task easier, Quintanilla’s drill instructors had told him. That’s why they asked each other questions starting with “why.” Make a chore into a meaningful decision, and self-motivation will emerge.
“We never tell anyone they’re a natural-born leader. ‘Natural born’ means it’s outside your control,” Krulak said. “Instead, we teach them that leadership is learned, it’s the product of effort. We push recruits to experience that thrill of taking control, of feeling the rush of being in charge. Once we get them addicted to that, they’re hooked.”
Studies show that someone’s locus of control can be influenced through training and feedback. One experiment conducted in 1998, for example, presented 128 fifth graders with a series of difficult puzzles. Afterward, each student was told they had scored very well. Half of them were also told, “You must have worked hard at these problems.” Telling fifth graders they have worked hard has been shown to activate their internal locus of control, because hard work is something we decide to do. Complimenting students for hard work reinforces their belief that they have control over themselves and their surroundings.
The other half of the students were also informed they had scored well, and then told, “You must be really smart at these problems.” Complimenting students on their intelligence activates an external locus of control. Most fifth graders don’t believe they can choose how smart they are. In general, young kids think that intelligence is an innate capacity, so telling young people they are smart reinforces their belief that success or failure is based on factors outside of their control.
“Internal locus of control has been linked with academic success, higher self-motivation and social maturity, lower incidences of stress and depression, and longer life span,” a team of psychologists wrote in the journal Problems and Perspectives in Management in 2012. People with an internal locus of control tend to earn more money, have more friends, stay married longer, and report greater professional success and satisfaction.
Locus of control has been a major topic of study within psychology since the 1950s. Researchers have found that people with an internal locus of control tend to praise or blame themselves for success or failure, rather than assigning responsibility to things outside their influence. A student with a strong internal locus of control, for instance, will attribute good grades to hard work, rather than natural smarts. A salesman with an internal locus of control will blame a lost sale on his own lack of hustle, rather than bad fortune.