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Demystifying Master Data Management

Organizations must understand that improving their data—and building the foundation for MDM—requires them to address internal disagreements and broken processes.

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By Tony Fisher

April 30, 2007 — CIO — Years ago, a global manufacturing company lost a key distribution plant to a fire. The CEO, eager to maintain profitable relationships with customers, decided to send a letter to key distributors letting them know why their shipments were delayed—and when service would return to normal.

He wrote the letter and asked his executive team to "make it happen." So, they went to their CRM, ERP, billing and logistics systems to find a list of customers. The result? Each application returned a different list, and no single system held a true view of the customer. The CEO learned of this confusion and was understandably irate. What kind of company doesn't understand who its customers are?

Unfortunately, most companies don't have a precise view about their customers, products, suppliers, inventory or even employees. Whenever companies add new enterprise applications to "manage" data, they unwittingly contribute to an overall confusion about a corporation's overall view of the enterprise. As a result, the concept of master data management (MDM)—creating a single, unified view of an organization—is growing in importance.

Naturally, where there's a big IT problem, there's a host of vendors lining up with sophisticated technology that provide an "out-of-the-box solution." The rationale is that by plugging an MDM technology into existing applications (CRM, ERP, logistics, billing, etc.) you can build that one "true view" that will then feed consistent, accurate and reliable data back into these systems.

But, as early adopters are finding, MDM isn't just a technology effort. Although MDM technologies can have a dramatic effect on a company's performance, no software is going to magically solve your enterprise's data problems overnight. And at the root of this problem is poor-quality data—and how bad data is created.

Consider a recent report from The Data Warehousing Institute that found 83 percent of organizations suffer from bad data for reasons that have nothing to do with technology. Among the causes of poor-quality data were inaccurate reporting, internal disagreements over which data is appropriate and incorrect definitions rendering the data unusable.

Organizations must understand that improving their data—and building the foundation for MDM—requires them to address internal disagreements and broken processes. Staff must agree on exactly what constitutes a "customer" or a "partner," and how to resolve any disagreements across business units. Departments and divisions need to agree on hierarchies of customers and products and how to resolve duplicate records across sources. Rather than a technology-focused effort, the project becomes one of political strategy and consensus building.