Poor quality customer data costs U.S. businesses a staggering $611 billion per year in postage, printing and staff overhead.Consider the example of an insurance company that receives 2 million claims per month with 377 data elements per claim. Even if the error rate is only .001, that translates to 754,000 claims data errors per month and more than 9.04 million per year.
If 10% of the data elements are critical to the insurer's business decisions and processes, the company must fix nearly 1 million errors each year. And, if the company estimates its risk at $10 per error-to cover the staff time to fix the error after the customer discovers it, the loss of customer trust and loyalty, and erroneous payouts, the company's exposure to poor quality claims data is $10 million per year.
That doesn't include the firm's exposure to poor quality data in its financial, sales, human resources, decision support and other areas.
Source: The Data Warehousing Institute, www.dw-institute.com.
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