Management Education in the Age of Big Data

What if business schools based their entire curriculum on the fundamentals of business analytics?

McKinsey estimates that the demand for “deep analytical positions” in the U.S. will exceed supply by 140,000 to 190,000 positions and that there will be a need for 1.5 million additional ”managers and analysts who can ask the right questions and consume the results of the analysis of big data effectively.”

What if business schools based their entire curriculum on the fundamentals of business analytics?

Why assume that “the analysis of big data” will be some special skill performed by a select group of “managers and analysts”? I think that it’s plausible, even desirable, that in the future all managers will be able to speak the language of business analytics and that it will become an integral part of their job.

This goes to the heart of what a manager’s job is. Managerial hierarchies have always been hierarchies of information flows and a significant part of a manager’s job since the advent of the modern corporation has been to move information up and down the organization. It is a century-plus model that is still dominant in established enterprises and edgy start-ups alike. Dustin Moskovitz recently complained about his experience at Facebook: “At the end of a four-week cycle [of information going up and down the management chain], I would know what was going on the previous month.”

Managerial hierarchies are running out of bandwidth today. They can’t cope with the amount of information moving from one layer to the next. The solution may lie not in getting rid of the layers but in investing the power of analytics in each layer, so what moves from one layer to another is analysis, not information.

Existing management education is based on the old model of management hierarchies. In the age of big data, management education should evolve to reflect the new reality that all information is available to everybody in the organization. What all managers need to do is analysis. But U.S. business schools each year graduate more than 500,000 holders of Bachelor’s and Master’s degrees with little or no knowledge and understanding of analytics and analytical/scientific thinking.

Management educators should assist aspiring managers by teaching tools and techniques for developing models and testing them, not much different from the tools taught to aspiring scientists. They should show future managers how to be critical and skeptical. Currently, most business students hear about testing a hypothesis only in the required statistics course. They pass the exam and move on.

I’m not calling for business schools to produce even more “quants” or “financial engineers” than they already do. My analogy is science—the study of empirical reality—not the production of “elegant” mathematical models that have nothing to do with reality, their assumptions are never questioned, and “are too complex for you to understand.” Managers, in any industry, should never be in a position where they are told that just like they don’t know how their television works, they don’t need to understand how the analytical models driving their business work.

Business schools should revamp their curriculum with courses and hands-on practice in scientific methods, analytical tools, and data mining/programming. Yes, a little bit of coding will go a long way towards preparing students for management in the 21st-century, as will a general knowledge of statistical modeling tools, statistical programming languages, and relational and non-relational databases. I think it will be best to infuse these new knowledge strains and practical experiences in all the traditional courses—marketing, finance, accounting, operations—rather than have a separate “analytics track.” This will give business schools a new focus on a renewed understanding of what management is all about: using analytical methods to make better decisions.