Making the business case in those conversations is different from justifying the cost of a new ERP system, says Barbara Wixom, a principal research scientist at MIT's Center for Information Systems Research. She is studying how companies monetize data in a digital economy.
Selling data or new products based on data "is a lot different from using it internally," Wixom says. CIOs have to think about valuation and pricing but also about packaging, customer service and a sales strategy. "All require investment and a vendor mentality," she says.
People should stop thinking of data as something inherently different from tangible products like soap or cars, says Forrester's Ferrara. Data is a by-product created and shed during a company's normal operations.
"This is no different from a company that processes beef to put steaks in the supermarket. They find the by-product of that process can be used for animal feed," he says.
For example, data from sensors built into refrigerators to improve the manufacturing process might also be sold to repair companies that want to target customers as their fridge's cooling coil or ice maker is about to go, he says. Innovation teams that include the CIO or other IT leaders can "take raw information and turn it into a product."
Hubbard contends that the CIO should have data scientists, even a chief data officer, on the technology team to supply quick, thorough data to support burgeoning information products. "You need the equivalent of an actuary in IT."
Kongara at American Family Insurance characterizes data as being "manufactured" and says some products are more valuable than others. Part of his job is to support efforts to create new revenue streams with various business units.
At the same time, his data management group works on perpetual problems, such as trying to find the definitive way to predict the lifetime value of a customer. Insurers, retailers and consumer packaged goods companies all chase this metric, combining many pieces of data via proprietary algorithms. The result is always an estimate, sometimes accurate and sometimes not. An incontrovertible number is "the holy grail in insurance companies," Kongara says. "People are searching for it still."
Dollars for Data
Many types of data already have a price—either in the free market or in the underworld
Putting a price tag on information isn't new. A classic example is the ticker data that flows from stock and futures markets. A 1905 Supreme Court ruling (Chicago Board of Trade v. Christie) gave financial exchanges the right to own and sell that proprietary data, a cash cow that can amount to 30 percent of an exchange's revenue, says Robert I. Webb, a professor of finance at the University of Virginia. A real-time feed of New York Stock Exchange stock prices for use by online media outlets, for instance, costs $25,000 per month.
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