The auto data aggregator ditched its mainframe, spending more than $20 million to build a data factory. Was it worth it?Kevin Vasconi, chief information officer of R.L. Polk & Co., saw the future. And it made him feel a little sick.
In the fall of 2004, Vasconi was meeting with other top executives of the company, one of the largest providers of marketing data to automobile manufacturers, in the boardroom of its suburban Detroit headquarters—in the heart of the U.S. auto industry.
It was a state-of-the-company gathering to discuss Polk's strategic direction. And the consensus was that its information systems wouldn't be able to support the business into the next decade. "If you have that discussion honestly," Vasconi says, "it will scare the crap out of you."
The Southfield, Mich.-based company's business, at its core, is data aggregation. Polk compiles vehicle registration and sales data from 260 sources. These include motor vehicle departments in the U.S. and Canada, insurance companies, automakers and lending institutions. The company then repackages that data and sells it to dealers, manufacturers and marketing firms—anyone who wants detailed information about car-buying trends, such as the top-selling SUV for a particular ZIP code.
For years, Polk's process of consolidating data ran on IBM mainframes. By the time Vasconi joined the company in 2003, portions of the software were 20 years old. "Some of the people working here are younger than the code," he says.
Read the full story on Baselinemag.com: SOA Case Study: How R.L. Polk Revved Its Data Engine
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