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The Data Quality Conundrum
Fewer than half of all organizations have a defined strategy regarding customer data, according to research by Experian QAS.
Posted May 28, 2009
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In a sign of just how messy and inaccurate the data floating throughout businesses really is, one out of four organizations isn't able to identify its best customers and best-selling products. The statistic, which comes from new research conducted on behalf of address-verification company Experian QAS, underscores a fundamental flaw: Many organizations still neglect to view caring for data as a mission-critical business process. The research also shows that 55 percent of organizations either said they didn't have a data strategy or weren't aware of one.

Fortunately, growth in the data management market may help combat this failing. According to industry research giant Gartner, the market for database management software increased by more than 24 percent in 2008. And in Experian QAS's survey of more than 2,000 data management personnel, two-thirds of respondents who assessed their investments in data-quality initiatives over the previous six months indicated an intention to match or increase those investments in the coming six months.

Joel Curry, chief operating officer for Experian QAS, says that this apparent commitment to data quality is a sign not only of a maturing market, but of a larger trend as well. "We've been seeing this big shift from customer acquisition to customer retention and knowing your customer base," Curry says. "Fortunately, it accelerates the interest in data quality up to [the] board level."

There may be good reason for the heightened interest in improving data quality. Only half of all organizations trust that their customer data is clean, accurate, and up-to-date, according to the Experian QAS results. (On a departmental level, sales professionals are surprisingly the most trusting of data, whereas those involved in CRM, marketing, and data management are less trusting.)

The report shows three key factors contrbute to this lack of trust in customer data:

  1. inadequacies in relevant technology;
  2. insufficient budgets; and
  3. inadequate data strategy.

During a presentation at Gartner's BI Summit in March, Gartner analyst Ted Friedman spoke to this point. "Despite lots of tools, big investments, many reports, and large data warehouses, without data quality decision-making is still largely a gamble," he stated. "Data is…not only an IT problem. If you look at it [as only that], you're going to fail."

Unfortunately, Curry says, the blame for faulty data too often falls on the technology department anyway, regardless of whether the data is entered by a customer via the Web or by a contact center agent. One reason for the misplaced blame, he says, can be traced to another insight from the Experian QAS research: the fact that 20 percent of business executives have no idea what's going on with their data quality initiatives. Curry says those companies have not recognized the true importance of data quality -- or the significant return on investment (ROI) that a successful data-quality implementation can deliver.

So what will make data quality a business priority? Curry suggests a three-step approach:

  • Tie the project into the corporate agenda.
  • Frame the project in terms of customer retention.
  • Aim to deliver ROI within one year.

News relevant to the customer relationship management industry is posted several times a day on destinationCRM.com, in addition to the news section Insight that appears every month in the pages of CRM magazine. You may leave a public comment regarding this article by clicking on "Comments" at the top; to contact the editors, please email editor@destinationCRM.com.

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