Big data is poised to transform society, from how we diagnose illness to how we educate children, even making it possible for a car to drive itself. Information is emerging as a new economic input, a vital resource. Companies, governments, and even individuals will be measuring and optimizing everything possible.
But there is a dark side. Big data erodes privacy. And when it is used to make predictions about what we are likely to do but haven’t yet done, it threatens freedom as well. Yet big data also exacerbates a very old problem: relying on the numbers when they are far more fallible than we think. Nothing underscores the consequences of data analysis gone awry more than the story of Robert McNamara.
McNamara was a numbers guy. Appointed the U.S. secretary of defense when tensions in Vietnam rose in the early 1960s, he insisted on getting data on everything he could. Only by applying statistical rigor, he believed, could decision makers understand a complex situation and make the right choices. The world in his view was a mass of unruly information that—if delineated, denoted, demarcated, and quantified—could be tamed by human hand and fall under human will. McNamara sought Truth, and that Truth could be found in data. Among the numbers that came back to him was the “body count.”
McNamara developed his love of numbers as a student at Harvard Business School and then as its youngest assistant professor at age 24. He applied this rigor during the Second World War as part of an elite Pentagon team called Statistical Control, which brought data-driven decision making to one of the world’s largest bureaucracies. Before this, the military was blind. It didn’t know, for instance, the type, quantity, or location of spare airplane parts. Data came to the rescue. Just making armament procurement more efficient saved $3.6 billion in 1943. Modern war demanded the efficient allocation of resources; the team’s work was a stunning success.
At war’s end, the members of this group offered their skills to corporate America. The Ford Motor Company was floundering, and a desperate Henry Ford II handed them the reins. Just as they knew nothing about the military when they helped win the war, so too were they clueless about making cars. Still, the so-called “Whiz Kids” turned the company around.
McNamara rose swiftly up the ranks, trotting out a data point for every situation. Harried factory managers produced the figures he demanded—whether they were correct or not. When an edict came down that all inventory from one car model must be used before a new model could begin production, exasperated line managers simply dumped excess parts into a nearby river. The joke at the factory was that a fellow could walk on water—atop rusted pieces of 1950 and 1951 cars.
McNamara epitomized the hyper-rational executive who relied on numbers rather than sentiments, and who could apply his quantitative skills to any industry he turned them to. In 1960 he was named president of Ford, a position he held for only a few weeks before being tapped to join President Kennedy’s cabinet as secretary of defense.
As the Vietnam conflict escalated and the United States sent more troops, it became clear that this was a war of wills, not of territory. America’s strategy was to pound the Viet Cong to the negotiation table. The way to measure progress, therefore, was by the number of enemy killed. The body count was published daily in the newspapers. To the war’s supporters it was proof of progress; to critics, evidence of its immorality. The body count was the data point that defined an era.
McNamara relied on the figures, fetishized them. With his perfectly combed-back hair and his flawlessly knotted tie, McNamara felt he could comprehend what was happening on the ground only by staring at a spreadsheet—at all those orderly rows and columns, calculations and charts, whose mastery seemed to bring him one standard deviation closer to God.
In 1977, two years after the last helicopter lifted off the rooftop of the U.S. embassy in Saigon, a retired Army general, Douglas Kinnard, published a landmark survey called The War Managers that revealed the quagmire of quantification. A mere 2 percent of America’s generals considered the body count a valid way to measure progress. “A fake—totally worthless,” wrote one general in his comments. “Often blatant lies,” wrote another. “They were grossly exaggerated by many units primarily because of the incredible interest shown by people like McNamara,” said a third.
The use, abuse, and misuse of data by the U.S. military during the Vietnam War is a troubling lesson about the limitations of information as the world hurls toward the big-data era. The underlying data can be of poor quality. It can be biased. It can be misanalyzed or used misleadingly. And even more damning, data can fail to capture what it purports to quantify.
We are more susceptible than we may think to the “dictatorship of data”—that is, to letting the data govern us in ways that may do as much harm as good. The threat is that we will let ourselves be mindlessly bound by the output of our analyses even when we have reasonable grounds for suspecting that something is amiss. Education seems on the skids? Push standardized tests to measure performance and penalize teachers or schools. Want to prevent terrorism? Create layers of watch lists and no-fly lists in order to police the skies. Want to lose weight? Buy an app to count every calorie but eschew actual exercise.
The dictatorship of data ensnares even the best of them. Google runs everything according to data. That strategy has led to much of its success. But it also trips up the company from time to time. Its cofounders, Larry Page and Sergey Brin, long insisted on knowing all job candidates’ SAT scores and their grade point averages when they graduated from college. In their thinking, the first number measured potential and the second measured achievement. Accomplished managers in their 40s were hounded for the scores, to their outright bafflement. The company even continued to demand the numbers long after its internal studies showed no correlation between the scores and job performance.
Google ought to know better, to resist being seduced by data’s false charms. The measure leaves little room for change in a person’s life. It counts book smarts at the expense of knowledge. And it may not reflect the qualifications of people from the humanities, where know-how may be less quantifiable than in science and engineering. Google’s obsession with such data for HR purposes is especially queer considering that the company’s founders are products of Montessori schools, which emphasize learning, not grades. By Google’s standards, neither Bill Gates nor Mark Zuckerberg nor Steve Jobs would have been hired, since they lack college degrees.
Google’s deference to data has been taken to extremes. To determine the best color of a toolbar on the website, Marissa Mayer, when she was one of Google’s top executives before going to Yahoo, once ordered staff to test 41 gradations of blue to see which ones people used more. In 2009, Google’s top designer, Douglas Bowman, quit in a huff because he couldn’t stand the constant quantification of everything. “I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that,” he wrote on a blog announcing his resignation. “When a company is filled with engineers, it turns to engineering to solve problems. Reduce each decision to a simple logic problem. That data eventually becomes a crutch for every decision, paralyzing the company.”
This is the dictatorship of data. And it recalls the thinking that led the United States to escalate the Vietnam War partly on the basis of body counts, rather than basing decisions on more meaningful metrics. “It is true enough that not every conceivable complex human situation can be fully reduced to the lines on a graph, or to percentage points on a chart, or to figures on a balance sheet,” said McNamara in a speech in 1967, as domestic protests were growing. “But all reality can be reasoned about. And not to quantify what can be quantified is only to be content with something less than the full range of reason.” If only the right data were used in the right way, not respected for data’s sake.
Robert Strange McNamara went on to run the World Bank throughout the 1970s, then painted himself as a dove in the 1980s. He became an outspoken critic of nuclear weapons and a proponent of environmental protection. Later in life he produced a memoir, In Retrospect, that criticized the thinking behind the war and his own decisions as secretary of defense. “We were wrong, terribly wrong,” he famously wrote. But McNamara, who died in 2009 at age 93, was referring to the war’s broad strategy. On the question of data, and of body counts in particular, he remained unrepentant. He admitted that many of the statistics were “misleading or erroneous.” “But things you can count, you ought to count. Loss of life is one.”
Big data will be a foundation for improving the drugs we take, the way we learn, and the actions of individuals. However, the risk is that its extraordinary powers may lure us to commit the sin of McNamara: to become so fixated on the data, and so obsessed with the power and promise it offers, that we fail to appreciate its inherent ability to mislead.
Kenneth Cukier is the data editor of The Economist. Viktor Mayer-Schönberger is a professor of Internet governance and regulation at the Oxford Internet Institute in the U.K. They are the authors of Big Data: A Revolution That Will Transform How We Live, Work, and Think (Houghton Mifflin Harcourt, 2013), from which this article was adapted.
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