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How the growing
emphasis on quantitative
data affects business—
and you

School of Business faculty members Neeraj Arora,
Kathryn Caggiano, Barry Gerhart and Tim Riddiough recently
sat down with UPDATE Editor Lari Fanlund to explore how access to
more data is affecting business.

Do you see any danger of companies emphasizing areas easiest to quantify?

Riddiough: I can measure it, therefore it exists!

Gerhart: Yes, it’s an ongoing challenge. In management, the easiest thing to quantify is costs, such as labor costs, but you also have to keep an eye on what you get in return, in terms of productivity and how well employees execute the strategy you have.

Caggiano: There’s an important difference between doing your due diligence in terms of quantitative analysis and actually making the decision. Businesses try to put themselves in a position to make a good decision and quantitative analysis can be an important tool. In the long run, a trend I hope we see is companies developing decision-support systems that lead them to make better decisions.

What does the emphasis on quantitative analysis mean for top managers?

Gerhart: The first thing I think about is Sarbannes-Oxley and the pressure on CEOs to know more about their financial numbers because they are more liable than they used to be. Now they have to sign off personally.

Arora: When you deal with multiple brands, multiple categories, you need to know what’s doing well and what isn’t doing well. You need to be able to track growth trends. There’s an increasing need for that analytical mindset. CEOs need to be able to digest report numbers in a meaningful way. That’s what I try to emphasize to our students: You may not want to be a person who does quantitative stuff on a day-to-day basis, but you need to be very comfortable with being analytical. You have to be able to read spreadsheets; it’s a toolkit you must have in your back pocket to be effective.

Caggiano: Not only that, CEOs need to be able to look at data in a spreadsheet and see that it’s telling you a story. One of the skills our MBA students need to have is not just being able to look at a spreadsheet and crunch some numbers. They need to be able to identify when those numbers are telling you, “Hey, there’s something that doesn’t make sense. I need to go find out what’s going on.” In a day and age where systems can gather data so quickly, it’s important to make careful analyses.

Arora: Fifteen years ago, senior managers were relying on predetermined reports. Things are changing. Today, people are much more savvy. You can’t just passively digest information that’s given to you. You can look at information from lots of different ways if you have an analytical mindset. A lot of senior folks that I talk to are doing a lot more of their own work. The days of having a secretary or a backroom analyst spit out reports for the CEO to look at isn’t efficient. Managers are learning to play with the data and test assumptions.

Gerhart: That all sounds good to me. I would just say there are probably different models out there that work. I would guess that there are some UPDATE readers who would say, “I don’t do that and I’m pretty successful.” Being able to analyze information is important, but so are many other things top executives need to be able to do in formulating and executing strategy.

Arora: I would agree. It would be naive to assume that numbers can solve everything.

Riddiough: At the end of the day, smart executives are very good at processing information and thinking through quantitative implications of different measures. We live in an increasingly dynamic, technical world where information is flowing faster and faster. So, by necessity, top executives must be increasingly competent at processing information. But they also need to have terrific intuition and people skills, so it’s a package.

Gerhart: Or, if they aren’t as competent in processing information, they have to understand the importance of having that competence nearby.

Arora: That’s right. It’s like a president with good advisors. Edward Demming, the quality guru, said something that summarizes what we are talking about. His point is that decision making is like a pendulum. On one extreme, you have data-based decisions. At the other extreme, you have decisions based on emotions, intuition and experiences. His point is that profound knowledge exists in the middle. I agree. To me, the sweet spot is in the middle.

Are there some companies or industries doing a particularly good job with quantitative analysis?

Riddiough: I can think of two industries that do interesting things with data. One is the gaming industry. They systematically collect consumer information to identify spending habits and monitor betting by individuals in the casinos. They can follow up and market their gambling products more effectively to those consumers. Another area that I’m interested in from a research standpoint is the mortgage business. When you take on a fixed-rate mortgage it’s probably going to be held by Fannie Mae or Freddie Mac, these two gigantic financial institutions. They’ve spent the last 10 to 15 years developing automated underwriting systems that are very sophisticated. They have a better understanding of credit risk and prepayment risk than their borrowers or their competitors.

Caggiano: Wal-Mart is a classic example, it’s a company we all know— and that some of us love and some of us vilify. But here’s a company that’s made tremendous advances in the last 10 years on data collection and data mining. It’s put an infrastructure in place to very quickly analyze data and act on it with most of their major suppliers.
Arora: In marketing we talk about the 4 P’s: pricing, promotion, place and product. Wal-Mart is a great example of using quantitative analysis for place or distribution channels. The entire field of marketing really lends itself to these quantitative models. Promotion is a very rich area for this. If I’m a brand manager, I have to decide how to allocate my advertising dollars across multiple media. I could throw it on the Internet, I could throw it on television, I could throw it on radio, outdoor advertising. There are all these avenues. The big question is how to begin to think about what’s most effective.

Is there a danger of companies becoming dazzled by data?

Riddiough: As an economist I look at this and say additional data is a good thing, but socially there’s some real potential downside to having all this information. For example, in health care historically, we don’t know much about individuals, so we’ve more or less charged everyone the same price. With the information available now, we’re able to separate pricing and target the risk. As a society, that’s a very difficult thing to grapple with. Do we want to charge individuals who have a pre-existing condition more for their health insurance?

Arora: A related issue is privacy concerns. As a marketer, I find information on consumers useful. It allows me to make better decisions to target people and fulfill their needs, but that information could also be misused, too.

Caggiano: I see more of a danger of people misusing the numbers. The saying that there are “lies, damn lies and statistics” certainly holds. As people pay more attention to quantitative information, there is more of a risk of them misinterpreting them.
Arora: It’s our job as teachers to teach students how to use quantitative techniques. The more important thing is how not to use techniques. Something basic like regression analysis, for example, is so easy to misuse. If you aren’t checking underlying assumptions you can come up with the wrong kind of inference.

Any advice you can give mid-career employees without strong quantitative skills?

Gerhart: They can always come back to places like the School of Business for lifelong education opportunities. Smart employers try to help their employees keep their skills up. Individuals and employers would both be wise to keep those skills current.

Arora: It’s like what I tell my students. You can’t get out of school and stop learning. It isn’t easy to fit it all in, but the return on investment for continuing education is so large. The other option is to not learn and to be unhappy down the road because you didn’t keep up to speed. It’s not just the quantitative. In general, you have to make a constant effort not to be obsolete.

Caggiano: For mid-level managers, Baby Boomers within 10 to 15 years of retirement for whom these tools may seem new or strange, the good news is that you can get the basics in a comparatively short amount of time. Taking a few day course in Excel, say, could increase their productivity tremendously.

Riddiough: We live in an increasingly complex world. For people who aren’t equipped to analyze data and deal with change, it’s a very difficult place to live.

About Our Panel

Neeraj Arora is the Arthur C. Nielsen, Jr., Professor of Marketing Research. He came to the University of Wisconsin-Madison in 1999 from Virginia Tech. Prior to entering academia, he worked as a marketing executive in the computer industry. His current research focuses on econometric models of individual and group choice. His teaching interests include marketing strategy, marketing research and mathematical models of consumer behavior. Arora is the executive director of the A.C. Nielsen Center for Marketing Research.

Kathryn Caggiano is an assistant professor in the Department of Operations and Information Management. Her research focuses on developing practical mathematical models and solution approaches to assist managers in making tactical and operational decisions in large-scale manufacturing and distribution systems. She has worked on many industry-sponsored projects in the area of service-parts management. Prior to her arrival in Madison in 2001, she spent two years as a visiting scientist at Cornell University’s School of Operations Research and Industrial Engineering.

Barry Gerhart holds the Bruce R. Ellig Distinguished Chair in Pay and Organizational Effectiveness. His areas of expertise include compensation, human resource management, incentives and staffing. Before coming to Wisconsin, he was on the faculty of Cornell University and Vanderbilt University. His writings have been featured in various scholarly journals including the Academy of Management Journal. In 2004, he published a highly regarded book on compensation theory. He directs the MBA career specialization in Strategic Human Resources Management at the School of Business.

Timothy Riddiough holds the E.J. Plesko Chair of Real Estate and Urban Land Economics and is academic director of the Center for Real Estate. He is widely published, with research interests in financial intermediation and debt contracting, investment theory, option pricing, law and economy and regulation—as they apply to real estate issues. He is a fellow at the Homer Hoyt Institute for Advanced Studies. Prior to joining School of Business faculty in 2001, he was a professor at M.I.T.