MBAs can't afford to end their math education with calculus

By James Manyika and Michael Chui
MBAs can't afford to end their math education with calculus

The effective use of big data will increasingly determine whether companies—and the US—can compete, write James Manyika and Michael Chui in Business Insider.

From financial transactions to consumer purchases to political polling, a torrent of data now flows into every area of the global economy.

Yet that river of information is meaningless without a workforce that can harness and analyze it.

The effective use of big data will increasingly determine whether companies—and the US—can compete.

But our education and training programs haven’t adapted to develop the skills big data demands. US students are shuttled along a familiar path in mathematics: first stop algebra, then geometry and trigonometry, and finally, the ultimate destination, calculus. This time-honored curriculum seems increasingly out of touch in a world that is flooded with noisy and voluminous data. The majority of students need to be immersed in the more practical discipline of statistics, which has greater relevance for the jobs being generated by a digital economy.

Consider the teams of medical researchers running clinical trials or analyzing the outcomes of patients after a therapy has been made widely available: they have to select the parameters to study, assess the results, and draw the right conclusions about a drug’s effectiveness and safety. Online advertisers trying to micro-target consumers must be able to detect patterns in the massive amount of clickstream data they gather from the Web. Risk managers on Wall Street, retail buyers choosing this season’s merchandise, environmental scientists, sports analysts, and military strategists all rely on the ability to synthesize data and predict outcomes.

The key to making sense of all the data now at our disposal is statistics. At leading companies, decisions once driven by HiPPOs (the Highest-Paid Person’s Opinion) are increasingly made by conducting experiments that draw on the core skills of statisticians. Rather than relying on gut instinct, businesses now find ways to test hypotheses and use statistical methods to analyze the results, applying the classic scientific method to decision-making.

Big data promises big things—but only if we have people in place who know what to do with it. The United States has led the big data revolution but faces a shortage of the analytical and managerial talent needed to maximize its potential. The McKinsey Global Institute estimates that the US will face a shortage of up to 190,000 professionals with advanced training in statistics and machine learning (“data scientists”) within six years. But more broadly, another 1.5 million executives and analysts will need enough proficiency in statistics to work closely with data scientists to design experiments and make better decisions. As Google’s chief economist Hal Varian put it, “the sexy job in the next 10 years will be statistician.”

Cultivating those skills can start in the classroom. This year, some 361,000 US high school seniors took the Advanced Placement (AP) calculus exam, while fewer than half that number opted to take the AP statistics exam. There’s no question that calculus offers valuable training in how to think and apply logic, and many of its concepts, such as rates of change, are certainly important.

But the actual use of calculus in the workforce is largely limited to fields such as physics and some engineering disciplines. By contrast, many of the fundamentals of statistics—conditional probabilities, sampling bias, and the distinction between correlation and causation, for example—are broadly useful to people as they make decisions in their roles as professionals, citizens, and even parents.

Some students hit a wall when they come up against calculus, finding it too abstract. Teachers can engage students in a tangible way with statistics, challenging them with real-world exercises like finding errors in reported studies, designing experiments to test hypotheses in the real world, or analyzing real data from the Web to determine what factors drive online behavior. Generating this kind of excitement earlier in a student’s high school years might even build a stronger lifelong affinity for mathematics.

Beyond secondary school, statistics should be a required course in many more degree programs. MBA programs are already placing greater emphasis on quantitative data analysis in their core curricula, recognizing that no business leader can afford to lack the ability to analyze data.

In fact, no informed citizen should be without these skills in the age of big data. This particular kind of quantitative literacy serves individuals beyond the workplace, whether they’re evaluating a politician’s claims about the economy or deciding whether home prices are likely to rise. During the 2012 campaign season, for example, bloggers like Nate Silver and Sam Wang proved that cogent use of statistics was far more accurate in predicting election outcomes than analysis from pundits that was based on little more than opinion and observation.

In a world where uncertainty is the only certainty, there is a growing need to transform massive troves of data into information that produces better decision-making. But if schools cling to their old curriculum, the US economy may come up short. Just do the math.

This article originally ran in Business Insider.

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