Data quality: 'The cornerstone of CRM'

Inaccurate and low-quality data costs U.S. businesses $611 billion each year in bad mailings and staff overhead alone, according to a recent report by The Data Warehousing Institute in Seattle.

"Yet, most executives are oblivious to the data quality lacerations that are slowly bleeding their companies to death," says the report by analyst Wayne Erickson.

"More injurious than the unnecessary printing, postage and staffing costs is the slow but steady erosion of an organization's credibility among customers and suppliers, as well as its inability to make sound decisions based on accurate information," the report concludes.

A company can spend $10 million on a customer relationship management (CRM) system but not get a return on investment because the data is bad, says Tim Waggoner, chief technology officer at Group 1 Software Inc., a data quality software vendor in Lanham, Md.

"Data quality is the cornerstone of CRM," Waggoner says.

"Organizations can frustrate and alienate loyal customers by incorrectly addressing letters or failing to recognize them when they call or visit a store or Web site," says the Data Warehousing Institute report. "Once a company loses its loyal customers, it loses its base of sales and referrals and future revenue potential."

The study was co-sponsored by vendors Arkidata Corp., DataFlux Corp., DataMentors Inc., Sagent Technology Inc., SAS Institute Inc. and Vality Technology Inc.

The problem with data is that its quality quickly degenerates over time. Experts say 2% of records in a customer file become obsolete in one month because customers die, divorce, marry or move.

However, the institute's survey of 647 data warehousing and business-intelligence professionals found that almost half of the respondents have no plans to implement an initiative to improve data quality.

The problems range from redundant data and incorrect mailing addresses to failed IT projects and bad corporate decisions based on bad data.

Forty percent of the survey respondents said their companies have suffered "losses, problems or costs" due to poor-quality data. The two most common problems caused by such data are the extra time required to reconcile data and the loss of the system's or application's credibility.

Sometimes, employees know the data is bad, so they avoid using it, says Charles Chung, vice president of information intelligence at Experian Information Solutions Inc. in Orange, Calif. The company, which is a subsidiary of Manchester, England-based GUS PLC, helps clean databases by matching them with credit records.

"I call it 'data skepticism.' They're worried about the quality of data and won't use certain data fields because they've been burned before," Chung says. "And that leads to underutilization of the information that's available -- a real shame."

The irony is that companies go to great lengths to manage their cash but not their equally valuable information. One company that understands the issue -- and is cited in the report -- is Cullen/Frost Bankers Inc., an $8 billion financial holding company in San Antonio.

In its mission statement, Cullen/Frost Bankers articulates its rationale for investing in high-quality data: "More than 98% of our company's assets and those of our customers are managed by data and information -- and less than 2% are in the form of cold, hard cash. Just as we are careful and meticulous in managing cash and negotiables, we have a duty and obligation to exercise a high degree of care with the data that is the basis for customer relations and decision-making."

Some analysts say the issue of data quality is too important to be left to the CIO alone; it needs CEO- or boardroom-level attention (see story).

But that requires showing top executives the costs of bad data and the benefits of clean data. "Unless we get it into financial figures, it won't get executive or board attention," Chung says.

"Data stewardship needs high-level attention and assignment. Some companies are even hiring a full-time data steward, but sometimes I think they lack enough authority to improve things," he says. "There's a lot of political friction, so you need the right person at the right level."

Historically, the person in charge of data has been the CIO. "Now the CIOs find it's a really big job, so they're appointing people to be data officers," Waggoner says.

What's a company to do? Waggoner identifies three key steps: Clean up the data you already have; stop the bad data from coming in; and remember that data gets stale the minute it's collected, so data quality is a never-ending mission.

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