by David Brooks
Of course he started talking about himself. “I owe it to myself to live up to the highest standards. I owe it to myself to provide legendary excellence.” This phrase was apparently a buzzword that had been circling around in the company propaganda. As the session went on, he turned into a little jargon machine. “At the end of the day, we try not to boil the ocean but just look for the best win-wins,” he told her. Apparently people at this company were always drilling down and disintermediating the dialogue. They were driving maximum functionality, with end-to-end mission-critical competence to incent high-level blue-ocean change.
Erica sat there with a smile pasted on her face. She appeared eager and supplicating. She debased herself. When he asked her what she wanted to do at the company, she slipped into the argot and threw it all back at him. She would save self-loathing for after she got the job.
He said he would call in a week, but it took two. She had her phone on vibrate the whole time, and every little tingle, real or imagined, sent her grabbing for the thing. The call finally came. Follow-up interviews were arranged and after another month or so she was an employee once again. She had a nice office. She began going to meetings and found herself surrounded by the lords of self-esteem.
Overconfidence
The human mind is an overconfidence machine. The conscious level gives itself credit for things it really didn’t do and confabulates tales to create the illusion it controls things it really doesn’t determine. Ninety percent of drivers believe they are above average behind the wheel. Ninety-four percent of college professors think they are above-average teachers. Ninety percent of entrepreneurs think that their new business will be a success. Ninety-eight percent of students who take the SAT say they have average or above-average leadership skills.
College students vastly overestimate their chances of getting a high-paying job, traveling abroad, and staying married when they reach adulthood. When shopping for clothes, middle-aged people generally choose clothes that are too tight on the grounds that they’re about to lose a few pounds, even though the vast majority of people in their age bracket get wider year by year. Golfers on the PGA tour estimate that 70 percent of their six-foot putts drop in the hole, when in reality 54 percent of the putts from that distance actually make it in.
This overconfidence comes in many varieties. People overestimate their ability to control their unconscious tendencies. They buy health-club memberships but then are unable to work up the willpower to go. People overestimate how well they understand themselves. Half of all students at Penn State said they would make a stink if somebody made a sexist comment in their presence. When researchers arranged for it to actually happen, only 16 percent actually said anything.
People overestimate what they know. Paul J. H. Schoemaker and J. Edward Russo gave executives questionnaires to measure how much they knew about their industries. Managers in the advertising industry gave answers that they were 90 percent confident were correct. In fact, their answers were wrong 61 percent of the time. People in the computer industry gave answers they thought had a 95 percent chance of being right; in fact, 80 percent of them were wrong. Russo and Schoemaker gave their tests to more than two thousand people and 99 percent overestimated their success.
People not only overestimate what they know, they overestimate what they can know. Certain spheres of life, like the stock market, are too complex and too random to be able to predict near-term events with any certainty. This seems to have no effect on actual behavior, as the entire stock-picking industry demonstrates. Brad Barber and Terrance Odean analyzed over sixty-six thousand trades from discount broker accounts. The traders who were the most confident did the most trades and underperformed the overall market.
People get intoxicated by their own good luck. Andrew Lo of MIT has demonstrated that when stock traders experience a series of good days, the dopamine released into their brains creates a surge of overconfidence. They believe they’ve achieved this good fortune themselves; they have figured out the market. They become blind to downside risk.
People overestimate their ability to understand why they are making certain decisions. They make up stories to explain their own actions, even when they have no clue about what is happening inside. After they’ve made a decision, they lie to themselves about why they made the decision and about whether it was the right one in the circumstances. Daniel Gilbert of Harvard argues that we have a psychological immune system that exaggerates information that confirms our good qualities and ignores information that casts doubt upon them. In one study, people who were told they had just performed poorly on an IQ test spent a lot more time reading newspaper articles on the shortcomings of IQ tests. People who had been given a glowing report from a supervisor developed an increased interest in reading reports about how smart and sagacious that supervisor was.
And the telling thing is that self-confidence has very little to do with actual competence. A great body of research finds that incompetent people exaggerate their own abilities more grossly than their better-performing peers. One study found that those who scored in the bottom quartile on tests of logic, grammar, and humor were especially likely to overestimate their abilities. Many people are not only incompetent, they are in denial about how incompetent they are.
So it is fair to say that human beings are generally overconfident. But Erica’s colleagues at Intercom not only rode the steed of arrogance, they took it out for a parade. The CEO, Blythe Taggert, never met an organization he didn’t want to transform. When he came to the company he declared war on entrenched bureaucracy and “old thinking.” The result was that his revolutionary fervor sometimes turned into a contempt for experienced managers and time-tested practices. He issued middle-of-the-night memos, often composed off the top of his head, which caused chaos in department after department. He was guided by aphorisms and rules that sounded good in speeches but often had nothing to do with real-life situations. He’d impatiently sit through presentations that had taken weeks to prepare, then he’d absentmindedly observe, “These ideas don’t really bite me in the ass,” and he’d stroll out while his acolytes laughed.
He was so eager to be seen as a heroic innovator, he led the company through a series of acquisitions into markets and niches nobody really understood. The company became too big to manage, and in his quest for the latest and most cutting-edge techniques, he tolerated accounting practices and organizational charts that were too complex to fathom.
He spoke first at every meeting. He had such definite views that few were willing to challenge or question him after he was done. The senior management team, meanwhile, encouraged this diversification into new sectors. The theory seemed to be that by spreading into many markets with many products it would be possible to diversify risks. The reality was that the more sectors they entered, the less they knew about any one of them. This strategy empowered executives who did deals and marginalized executives who had spent their lives in a specific market and had concrete knowledge of how it worked.
The company spent more time managing its structure than improving its products. Hoping to find a single measure that could be used to compare results across a wide variety of product lines, managers devised pseudo-objective success criteria. These success metrics had only tangential relationships to long-term growth. Managers spent more time trying to figure out how they could game the metrics than in actually producing sustainable results.
The finance and accounting departments, with the CEO’s approval, became enamored of arcane risk-management devices that seemed brilliant to the very few who claimed to understand them, but which muddied risk analysis in real life. Erica noticed that nobody colored in the future in the PowerPoint charts. At every other company, past data was shown on a white background and future projections were distinguished with a yellow background or a dotted line. These folks, the team of assholes, were so confident of their predictive abilities they didn’t bother. They were embedded in a macho culture in which admitting they didn’t know
something was not an option.
The odd thing was that as the company got more diverse the executives became more conformist. There were people in many different sectors in offices spread throughout the world. You’d think this configuration would yield a range of viewpoints and expectations that would balance each other out. But time and time again, instant communications and instant judgments based on those communications created a herd mentality and an astonishing culture of intellectual homogeneity. Time and time again, people made the same one-way bets at the same time. Maybe this is what happens when a whole company (or a whole global economy) lives off its BlackBerries and makes decisions at the speed of electrons.
While all this was happening, the chairman and the CEO were making ever more lavish claims about the company’s success. During the conference calls, the sales meetings, and the self-congratulatory corporate retreats, there would be one grandiose boast after another—that this was the greatest corporation in America, that this was the most innovative company in the world.
The most frustrating thing of all was that, in meeting after meeting, Erica had nothing to add. It’s not that she didn’t see huge problems in the company. There were big hairy monsters everywhere you looked. It’s just that the mode of analysis was a closed language. Erica had her own way of looking at things and her own vocabulary, which emphasized culture, social life, and psychology. All of her new colleagues had a different way of seeing, based on amassing huge piles of data and then devising formulas and building systems. The two modes seemed non-overlapping.
Maybe it was in B-School, maybe it was somewhere else, but the team of assholes had been trained in certain methodologies. They had been trained to turn management into a science. They didn’t really grow up steeped in the features of a specific product. They were trained to study organizations. Some did Dynamic Systems Theory, some did Six Sigma Analysis, or the Taguchi Method or Su-Field Analysis (structural-substance field analysis). There was TRIZ, a Russian-made model-based technology for producing creativity. There was Business Process Reengineering. Erica looked this one up on Wikipedia. According to one of the management books quoted on the site, BPR “escalates the efforts of JIT [Just In Time] and TQM [Total Quality Management] to make process orientation a strategic tool and a core competence of the organization. BPR concentrates on core business processes, and uses specific techniques within the JIT and TQM ‘toolboxes’ as enablers, while broadening the process vision.”
Erica read sentences like that, or heard them at meetings, and she just had no clue how they applied to the problems at hand. The sounds just sort of bounced off her brain. The people who uttered them seemed to value precision and clarity. They sought to be scientific. But the jargon just seemed to float in the air.
The Rationalist Version
Of course these management whizzes did not come into being by accident. John Maynard Keynes famously wrote that “practical men, who believe themselves to be quite exempt from any intellectual influences, are usually the slaves of some defunct economist.” The people Erica now worked with were the slaves of a long philosophic tradition. This tradition, rationalism, tells the story of human history as the story of the progress of the logical, conscious mind. It sees human history as a contest between reason, the highest human faculty, and passion and instinct, our animal natures. In the upbeat version of this story, reason gradually triumphs over emotion. Science gradually replaces myth. Logic wins out over passion.
This historical narrative usually begins in ancient Greece. Plato believed the soul was divided into three parts: reason, spirit, and appetite. Reason seeks truth and wants the best for the whole person. Spirit seeks recognition and glory. Appetite seeks base pleasures. For Plato, reason is like a charioteer who must master his two wild and ill-matched horses. “If the better elements of the mind which lead to order and philosophy prevail,” Plato wrote, “then we can lead a life here in happiness and harmony, masters of ourselves.”
In classical Greece and Rome, according to this narrative, the party of reason made great strides. But after the fall of Rome, the passions reasserted themselves. Europe fell into the Dark Ages. Education suffered, science lay dormant, superstition flourished. Things began to pick up again during the Renaissance with the developments in science and accounting. Then, during the seventeenth century, scientists and technologists created new forms of machinery and new ways to think about society. Great investigators began to dissect and understand their world. The metaphor, “the world is a machine,” began to replace the metaphor, “the world is a living organism.” Society was often seen as a clock with millions of moving pieces, and God was the Divine Clock-maker, the author of an exquisitely rational universe.
Great figures like Francis Bacon and René Descartes helped create a different way of thinking—the scientific method. Descartes aimed to begin human understanding anew. He would start from scratch and work logically and consciously through every proposition to see, step by step, what was true and certain. He would rebuild human understanding on a logical foundation. In this scientific age, the mind could not, Bacon urged, be “left to take its own course, but guided at every step.” What was needed was a “sure plan” and a new reliable methodology.
In this new mode of thought, the philosopher and scientist must begin by purging his mind of prejudice, habit, and prior belief. He must establish a cool, dispassionate distance from the subject of his inquiry. Problems must be broken down into their discrete parts. He must proceed consciously and methodically, beginning with the simplest element of the problem and then proceeding step by step toward the complex. He must develop a scientific language that will avoid the vagueness and confusion of ordinary language. The aim of the whole method is to arrive at certain lawlike generalizations about human behavior—to arrive at certainty and truth.
The scientific method brought rigor to where there had once been guesswork and intuition. In the realm of physics, chemistry, biology, and the other natural sciences, the results were awesome to behold.
Inevitably, rationalist techniques were applied to the science of organizing society, so that progress in the social realm could be as impressive as progress in the scientific one. The philosophies of the French Enlightenment compiled a great encyclopedia, trying to organize all human knowledge in one reference book. As Dumarsais declared in the encyclopedia, “Reason is to the philosopher what grace is to the Christian. Grace moves the Christian to act, reason moves the philosopher.”
As the centuries passed, social scientists tried to create a science of human nature. They worked to create models that would enable them to predict and mold human activity. Political scientists, international-relations professors, and others developed complex models. Management consultants conducted experiments to better understand the science of corporate leadership. Politics became organized around abstract ideologies, grand systems that connect everything into one logically consistent set of beliefs.
This rationalist mode of thought is omnipresent and seems natural and inevitable. The rationalist tradition proved seductive. It promised certainty, to relieve people of the anxiety caused by fuzziness and doubt. People’s perceptions about human nature seem to be influenced by the dominant technology of their time. In the mechanical and then the industrial age, it was easy to see people as mechanisms and the science of human understanding as something akin to engineering or physics.
Rationalism gained enormous prestige during the nineteenth and twentieth centuries. But it does contain certain limitations and biases. This mode of thought is reductionist; it breaks problems into discrete parts and is blind to emergent systems. This mode, as Guy Claxton observes in his book The Wayward Mind, values explanation over observation. More time is spent solving the problem than taking in the scene. It is purposeful rather than playful. It values the sort of knowledge that can be put into words and numbers over the sort of knowledge that cannot. It seeks rules and principles that can be applied across contexts, and undervalues the importan
ce of specific contexts.
Moreover, the rationalist method was founded upon a series of assumptions. It assumes that social scientists can look at society objectively from the outside, purged of passions and unconscious biases.
It assumes that reasoning can be fully or at least mostly under conscious control.
It assumes that reason is more powerful than and separable from emotion and appetite.
It assumes that perception is a clear lens, giving the viewer a straightforward and reliable view of the world.
It assumes that human action conforms to laws that are akin to the laws of physics, if we can only understand what they are. A company, a society, a nation, a universe—these are all great machines, operated through immutable patterns of cause and effect. Natural sciences are the model that the behavioral sciences should replicate.
Eventually, rationalism produced its own form of extremism. The scientific revolution led to scientism. Irving Kristol defined scientism as the “elephantiasis of reason.” Scientism is taking the principles of rational inquiry, stretching them without limit, and excluding any factor that doesn’t fit the formulas.
Over the past centuries, many great errors and disasters have flowed from the excessive faith in pure reason. At the end of the eighteenth century, revolutionaries in France brutalized the society in the name of beginning the world anew on rational grounds. Social Darwinists imagined they had discovered the immutable laws of human evolution, which could be used to ensure the survival of the fittest. Corporate leaders under the influence of Frederick Taylor tried to turn factory workers into hyper-efficient cogs. In the twentieth century, communists tried to socially reengineer whole nations, attempting to create, for example, a New Soviet Man. In the West, Le Corbusier and a generation of urban planners sought to turn cities into rational machines—factories for traffic—by clearing away existing neighborhoods and replacing them with multilane highways and symmetrical housing projects cut off from the older city. Technocrats from affluent nations tried to plant large-scale development schemes across the developing world without much concern for the local context. Financial analysts at the big banks and the central banks thought they had mastered economic cycles and created a “Great Moderation.”