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Big Data: How a Trucking Firm Drove Out Big Errors

Rob Lemos | March 3, 2011
A balkanized IT environment left U.S. Xpress unable to mine its massive and disparate databases. Here's how IT found new ways of grabbing more -- and better -- data on its trucking fleet, saving big money and fueling business agility.

"It is a zero sum game," says Ivan Chong, general manager for Informatica's data quality business unit. "So the savings in trucks is the ROI (return on investment)."

Using Informatica, for example, the company's IT team can profile a legacy database made more than a decade ago and get an understanding of how it works, says U.S. Xpress's Langley. It makes no sense to build more complex applications, without first cleaning up its databases, Langley says.

"Initially, they wanted a customer relationship management (CRM) system," he says. "I told them, we are not even going to start CRM until we have data quality in place."

The pressure to cut costs and save money is another reason the company tackled its information problems. During the stark recession, demand for the transportation industry's services sank nearly a quarter, compared to its prior peak, he says.

"The transportation industry itself has been very, very tough," Langley says. "Most people have lost money in the last two years."

Improving data quality across the company has resulted in a more agile business, a situation that is not specific to the transportation industry, says Rob Karel, principal analyst with Forrester Research (FORR). Every industry could use better data on operations, he says.

"The goal is not to get clean data, because clean data does not get you money," Karel says. "The goal is to fuel your business processes and decisions in the best way possible."

 

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