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Analytics Magazine

Profit Center: An analytics education

January/February 2011

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E. Andrew BoydBy E. Andrew Boyd

A young man recently contacted me about finding a good graduate program in analytics. I was happy to oblige, but couldn’t immediately answer him. Had he asked about graduate programs in economics, mathematics or some other well-defined, well-established discipline, I could have responded without pause. Analytics, however, is neither well defined nor well established as a stand-alone university discipline. This isn’t to say universities aren’t busy training students in the tools of analytics. Schools simply haven’t offered degrees bearing the name “analytics.”

This state of affairs, however, is changing. North Carolina State University lays claim to the first Master’s of Science in analytics through the affiliated Institute for Advanced Analytics. The thoughtfully developed degree program was first offered in the 2007-2008 academic year and is growing and thriving. SAS, an established software vendor and consultancy located near N.C. State’s Raleigh campus, was instrumental in spearheading the effort. In June 2010, DePaul announced a master’s of science in predictive analytics through its College of Computing and Digital Media and the Center for Data Mining and Predictive Analytics. The program was developed in cooperation with sponsor IBM. Northwestern’s School of Continuing Studies will begin offering a program in predictive analytics in fall 2011.

DePaul draws heavily upon traditional courses such as those offered through the math department. Students at N.C. State take courses specifically designed for the analytics program, as do students at Northwestern. It’s reasonable to assume DePaul graduates will be proficient with IBM’s analytics software and N.C. State graduates with software from SAS.

Additional programs of study can be found under the name “business intelligence.” Neither analytics nor business intelligence can be unambiguously defined, though they overlap extensively and some consider them essentially identical. As a catch phrase, “analytics” appears to be gaining the upper hand. Saint Joseph’s University offers a master’s of science in business intelligence through its business school, and the University of Denver offers a similar degree, also through its business school.

A look at the various curricula shows common themes: mathematics, computers, data and modeling. Many programs place an emphasis on marketing. While marketing is a fertile area for the application of analytics, it’s no more a part of analytics than finance, operations or sales. Notable exceptions to the marketing emphasis are the programs at N.C. State and Northwestern.

The emergence of these new programs attests to the growing importance of analytics, but it also raises the question of whether such programs must actually bear the name analytics (or business intelligence, or a similar label). Setting aside the name, there are well-established university programs that intersect with analytics.

One area is statistics. Forecasting, the design and analysis of experiments and data mining are fundamental components of analytics, and statisticians come ideally trained for these activities. Unfortunately, many aspects of analytics don’t easily fit within a statistics program, among them, optimization and non-statistical problem solving.

Another area that isn’t as commonly known as statistics is operations research (O.R.) O.R. has its roots in operational problem solving for the British and U.S. armed forces during the Second World War. Early O.R. practitioners thought of O.R. in the same, somewhat amorphous way people now think of analytics: the use of models, data, mathematics and good sense to solve problems. Over time, the study of optimization and stochastic processes came to form the core of O.R. curricula, together with some introduction to statistics and simulation. More recently, O.R. programs have broadened their requirements, including coursework in such areas as computers and non-textbook problem solving.

O.R. programs are housed in various locations within universities. The Industrial and Systems Engineering Department at Georgia Tech, for example, offers master’s and Ph.D. degrees in O.R. The Web site of GradSchools.com lists more than 150 degree programs in O.R., though the list is far from complete (www.gradschools.com/search-programs/operations-research). At present, most such programs emphasize optimization and stochastic processes more extensively than might be considered ideal for an analytics curriculum. This emphasis comes at the expense of more thorough training in areas such as statistics. However, many of the departments that house O.R. programs provide sufficient flexibility for students to fashion a well-rounded “analytics” course of study.

It’s likely that in the near future some departments housing O.R. programs will offer master’s degrees or concentrations in analytics. INFORMS, the leading U.S. professional society for academics and practitioners of O.R., appears on the verge of embracing analytics. INFORMS underwrites the publication of this magazine, and in 2011 it’s changing the name of its annual practitioner conference from the INFORMS Conference on O.R. Practice to the INFORMS Conference on Business Analytics and Operations Research.
So where does this leave the student looking for a professional degree in analytics? In fact, there are already some good choices, and we’re sure to see more emerge this year and for years to come.

Of course, getting an analytics education isn’t about the name on the degree. It’s about learning a set of skills – even though the skills that comprise analytics aren’t entirely well defined. An individual who is interested in data mining might do very well in a statistics program. The downside is that statistics programs cover an important but specific set of analytics tools, not analytics broadly defined.

All things considered, O.R. programs are an excellent starting point for individuals seeking an analytics education (or employers seeking to hire students trained in analytics). With the many different types of O.R. programs being offered, it’s necessary to look into the details to find a program that best meets an individual’s needs. The INFORMS Conference on Business Analytics and Operations Research is an ideal opportunity to talk to academicians about educational programs and to ask people in industry what specific analytics skills they’re looking for.

Will we one day see analytics recognized in universities alongside economics and mathematics departments? Probably not. Will we see more analytics programs and concentrations emerge? Without question. The extent to which “analytics” embeds itself in the academic lexicon remains to be seen. And given the breadth of territory it covers, it’s unclear that a uniform curriculum will ever materialize. However the details unfold, the analytics skill set will be taught for the simple reason that the market demands it.


Andrew Boyd served as executive and chief scientist at an analytics firm for many years. He can be reached at e.a.boyd@earthlink.net.

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