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Management in Practice

How Can You Get the Most out of Big Data?

The theoretical possibilities for big data are limitless, but putting so much information to good use requires big thinking. Unilever’s Gina Boswell ’89 explains the principles that the global company uses to effectively mine their data troves.

Every day, our digital lives—social networks, mobile activity, the internet, purchase transactions —generate over 2.5 exabytes of data. That’s 50 million filing cabinets. Or a library of MP3s that would take 5 million years to play.

The impact of all that data on business is transformative—but not effortlessly so. Back in 2011, The Economist predicted that “companies that can harness big data will trample data-incompetents” while warning, “Big data has the same problems as small data, but bigger. Data-heads frequently allow the beauty of their mathematical models to obscure the unreliability of the numbers they feed into them. (Garbage in, garbage out.)”

More recently, the New York Times published a widely discussed op-ed, “Eight (No, Nine!) Problems With Big Data,” that included a list of the challenges faced by anyone trying to sift signal from noise. The final problem in the list: overhyping the promise of big data.

Despite the hype, data and analytics are driving decisions across the business world—from mobile advertising at Facebook to tennis’s Wimbledon Championships, where weather data and onsite systems are used to predict crowd sizes and dynamically redirect resources to meet shifting needs.

But the applications of big data aren’t always straightforward. Sometimes retailers can have too much information about customers. “If we come across as a stalker, we break trust,” Gene Alvarez, an e-commerce analyst at research firm Gartner, told Bloomberg. The same article noted, “Retailers have discovered that customized circulars mixing targeted ads with items the customer probably won’t want—a coupon for diapers alongside a lawnmower—are more effective, because the recipient won’t assume she’s being spied on.”

Yale Insights talked with Gina Boswell ’89, executive vice president for personal care at Unilever, about how the global brand uses data and analytics to understand trends and interact more effectively with customers.

Handing petabytes of undifferentiated data to every employee every day is senseless. “The key,” Boswell said, “is the strategic interpretation of that data and using it in ways where it’s filtered to the right people at the right time. So the data is accurate, is useful—so it’s put in useful formats, which is not a small feat—and most importantly, it’s relevant.”

One important use of big data for a big company is that it can start to do some of the things that in the past were only possible for small businesses. “At Unilever, we have global reach beyond compare, but we’re also striving for that local intimacy that information like this will bring to bear,” Boswell said.

How does that work? “We have a vast amount of demographics data,” she said. “The beauty embedded in data and analytics is that you can do consumer segmentation to the levels where you can really start to tailor to a particular segment of the population.”