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Big Data and Competitive Intelligence

Bill Franks, chief analytics officer at Teradata, is like the chief software architect at Microsoft, the vice president of search at Google or the head of design at Apple. He’s a voice of authority in his discipline in a way having little to do with his position on the organization chart.

Franks spoke today to the Business Marketing Association of Atlanta, describing the practical challenges of Big Data. While Gartner says Big Data has entered the trough of disillusionment, Franks remains enchanted.

There’s a bubble in the market for Big Data, Franks conceded, but the stock market says nothing about the long-term power of analytics to reveal practical money-making connections.

Take mixed martial arts and the History Channel. Seems like an odd match, unless you’re looking for the physical equivalent of Epic Rap Battles of History. But it turns out that Franks' colleague noticed a connection between the two media properties while looking for ways to boost pay-per-view advertising value for a UFC match. “It wasn’t just generic History Channel,” Franks said. “It was one show on the History Channel. Swamp People.”

The gold nugget in the data: UFC could direct some of their very expensive ESPN advertising budget to Swamp People at more value for the dollar, because advertising on the History Channel comes cheap.

Big Data disrupts industries in much the same way the Internet does, Franks said. With the History Channel, for example, Big Data exposes the relative lack of rigor used by broadcasters in traditional media measurement. Folks selling ads don’t know what they’re worth. They’re guessing. But a Big Data professional will have a much better guess.

For competitive intelligence professionals, Big Data represents a major opportunity. Franks figuratively encourages firms to “ignore their own business” and find outside companies that might profit from the valuable data businesses collect. Firms have tremendous information about their own processes and their markets, but they’re also unintentionally gathering huge amounts of information about the competitive environment. Some of that will be about their own competitors – that’s not data they’ll share. But about firms they don’t compete with?

One might imagine brokering access to aggregated sales data from a credit card company, not just of one’s own merchandise but that of a competitors as well. Or perhaps an analysis of traffic patterns from a telecommunications provider can show how a rival shop’s customers come and go.

Time to cut a deal.

One drawback to all of this – it remains labor intensive. To start, data often has to be “cleaned” of errors, a task that might take 75 percent of a project’s time, Franks said. And there’s a major skill shortage in analytics to boot, he added.

“That’s why it’s great to be me.” 

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