Business Analytics: Too Cool (Just) for School
by Vijay Mehrotra
Gregory is an old friend of mine, a seasoned sales leader, a start-up turnaround specialist and an early stage company executive. He has seen an awful lot in his long career, and whenever I get together with him I inevitably learn something. When I see his name flash up on my cell phone, I pick up with a smile, thinking he’s calling to see when we might sneak out of work for an afternoon at the ballpark. Turns out he has something quite different in mind.
“You know about this analytics stuff, right? Great. I’ve got a company that I want you to take a look at,” he says. “They have a software platform that sits in ‘The Cloud’ and it’s using some smart predictive analytics to help on-line retailers do better targeting. You know that ‘The Cloud’ and predictive analytics are both at the top of Gartner’s list of strategic technologies for 2010 , right? So these guys are trying to bring both of them together in a pretty interesting way. Anyway, we’d like to come up to campus and tell you more about the company and see if you are interested in getting involved — can you make time for a meeting sometime next week?”
As I listen to him, I realize that I’ve rarely heard Gregory sound this excited about anything. “Gregory,” I tell my old friend, “come on over. I can’t wait to hear what you guys are up to with analytics out there in the real world.”
A long time ago I was a grad student in operations research, a discipline sitting at an intersection of mathematics, industrial engineering, statistics and computer science. For the past couple of decades, much of my work has involved O.R., first as a consultant, then as an entrepreneur and most recently as a business school professor. Some time back in the last century, I began writing a column called “Was It Something I Said?” in OR/MS Today, the membership magazine for the Institute for Operations Research and Management Science (INFORMS). I screamed at the rest of the world to recognize the power and glory of operations research, and I howled at my O.R. brethren to look for real applications upon which to focus their powerful intellectual capabilities instead of tirelessly pushing deeper and deeper into theoretical crevices. And over the years, while I got a moderate amount of e-mail from readers who appreciated my thoughts on one topic or another and the occasional angry note from someone who I managed to offend, the world outside of INFORMS generally paid relatively little notice to either my column or to our profession.
Meanwhile, in a parallel universe, a number of powerful and (imperfectly) correlated developments were taking place. The cost of computing power was plummeting. The capability of spreadsheets and more sophisticated data analysis platforms was exploding. The business world was growing more and more competitive, pushing managers and executives to search for competitive advantages wherever they could possibly find them. Data storage was getting cheaper and cheaper and “business intelligence” vendors were busy creating data structures and reporting capabilities to give businesses a way to look at all that raw data that was suddenly laying around. The Internet had emerged as an amazing platform for capturing mountains of data, an inexpensive laboratory for conducting statistical experiments, and a superhighway that enabled information to be moved, analyzed and presented at amazing speed. And pioneers in disparate industries — including finance, travel and hospitality, gaming and supply chain management — were demonstrating that, with the clear-eyed application of an appropriate amount of mathematical elbow grease, the growing piles of data could be successfully mined for gold.
And then, seemingly overnight, the world awakened to the potential of quantitative analysis to create huge business value. The past couple of years we have seen a slew of books such as “Super Crunchers” , “The Numerati”  and “Competing on Analytics” , a New York Times article  advocating how cool it is to be a statistician today, and, most recently, huge public validation by people like Gartner and Accenture  of just how important this stuff called analytics is going to be.
Seemingly overnight, the world awakened to the potential of quantitative analysis to create huge business value.
Both INFORMS and I are scrambling to find our place in this world. In addition to launching the online magazine that you are reading right now, INFORMS has recently engaged a major consulting partner to help us understand how we can better serve this bigger, broader domain of analytics. Meanwhile, I have recently been hired as a professor of business analytics at the University of San Francisco, and in an effort to keep up with what my students should know (and what many friends in the business world already know), I have agreed to write this new column.
Is there really a revolution brewing out there in analytics? I’d like to think so, but my strong sense is that there is still a long way to go. A recent Accenture study  of executives in the United States and the United Kingdom confirms a lot of things that many of you no doubt have experienced: data still too often living in silos, a shortage of dedicated analytically skilled resources, and managers who still feel more comfortable relying on intuition and gut feel than on structured analysis, especially when planning for the future. Many of my academic colleagues also bemoan the mathematical preparation of today’s students, suggesting that the pipeline of analytical people needed to solve this talent gap is probably not as full as it needs to be. On the other hand, things are moving so fast — new software tools, new mathematical techniques, new industry applications, and new success stories — that I will no doubt have lots to write about.
Welcome to “Analyze This!,” one man’s imperfect view on the rapidly evolving world of analytics. I’m counting on you all to help keep that view expanding, so feel free to drop me a note to share your thoughts, ideas and experiences. See you next time.
Vijay Mehrotra (email@example.com) is an associate professor, Department of Finance, Economics and Business Analytics, School of Business and Professional Studies, University of San Francisco. He is also an experienced analytics consultant and entrepreneur and an angel investor in several successful analytics companies.
1. See www.gartner.com/it/page.jsp?id=1210613 for the complete list.
- 49Use of the term “business analytics” is being used within the information technology industry to refer to the use of computing to gain insight from data. The data may be obtained from a company’s internal sources, such as its enterprise resource planning application, data warehouses/marts, from a third party data…
- 48Eric Siegel, founder of Predictive Analytics World (PAW, a series of conferences held throughout the year in major U.S. and European cites) and the author of the new book, “Predictive Analytics: The Power to Predict who will Click, Buy, Lie or Die,” is without question a key player in the…
- 41Cathy O’Neil’s provocative book, “Weapons of Math Destruction: How big data increases inequality and threatens democracy,” created quite a stir in the analytics community when it was released last fall.
- 41Hewlett-Packard (HP) knows there are two sides to every coin. The company has achieved new power by predicting employee behavior, a profitable practice that may raise eyebrows among some of its staff. HP tags its more than 330,000 workers with a so-called Flight Risk score. This simple number foretells whether…