Mopping Up Dirty Data

Once only direct marketers worried about getting names and addresses right. Now more companies recognize the need to clean up their data.

/zimages/6/17485.gifDirect marketers have long reckoned with cleaning dirty databases loaded with duplicate names, misspelled addresses and other shortcomings. Today, companies in more diverse industries—from technology to manufacturing—are jumping on the information-quality bandwagon to get the most out of managing customer relations and other projects relying on lots of data.

RSA Security, like countless other companies, found out the hard way about the perils of dirty data. The security-software firm had just installed customer-relationship-management software from Siebel Systems in 2001 to make it easier for its 300-person sales force to sell authentication products to enterprise and electronic-commerce customers.

Problem was, the Siebel application was fed by several incompatible systems, each with its own way of identifying customers. And RSA had no way—short of manually going through every record—of being sure salespeople were being given complete and correct information on all customers. If, for example, the companys order-entry system reported information on a customer named James Smith, and the Web server had information on a Jim Smith, the Siebel system probably wouldnt catch on that the two Mr. Smiths were really one customer.

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