MDM's Monumental Momentum

HOLLYWOOD, FLA. -- Like a ticking time bomb, the problems associated with data quality have been slowly building within enterprises over the years -- a development that harbingers the coming era of master data management (MDM), according to the opening keynote session of the Gartner MDM Summit here yesterday. "MDM's time has come," said Ranjay Gulati, a distinguished professor of strategy and organizations of the Kellogg School of Management at Northwestern University. "For years, enterprises have been product-driven businesses. Now, the shift is under way to become more customer-centric, and that's going to require MDM." Driven by the commoditization of products and services -- such as faster product life cycle, more informed consumers, constantly shifting market pressures, and competitive forces -- organizations are finally looking to implement enterprisewide information strategies. "Linking up customer data isn't enough, though it's a good start," Gulati told attendees. "To become more customer-centric, all enterprise data -- including product, accounting, supply chain, etc. -- it all has to be brought together under a single layer of data that gives the enterprise flexibility and adaptability." The prime reason for MDM's emerging popularity, and the principal failure of data quality strategies and solutions to date, has been the development and deployment of enterprise applications that have remained siloed, said Andrew White, research vice president at Gartner, during his part of the keynote presentation. While most CRM systems have done an admirable job of gathering customer data, those same systems have now become repositories of information often unavailable for other business processes. "Enterprise applications -- whether it's ERP, CRM, or SCM -- they've all become silos of information within the enterprise. As a result, the data has been duplicated over and over again," White said. White suggested that the continued efforts to unify business software via enterprise information integration (EII) and enterprise application integration (EAI) solutions have only alleviated some of the symptoms, but they have yet to solve the overall problem. "All you're doing is moving the data around faster and more efficiently," he said. "You're still not getting to the root cause. We've now learned that you have to attack data quality at its heart, at the very foundation, and that's what MDM is all about. It's a fundamental shift in how you govern, classify, store, distribute, and use all of your enterprise data." Despite its popularity, MDM's underlying concept and resulting technology are still in their infancy, said John Radcliffe, another of Gartner's research vice presidents, later in the keynote presentation. Many businesses are still experimenting and struggling with the business process and data steward shifts associated with MDM. With that in mind, Radcliffe outlined an MDM maturity model:

• Stage 0 - Unaware. A company totally unaware that MDM exists.
• Stage 1 - Aware. A company aware of MDM strategies, but lacking any vision or direction in what it means to the business.
• Stage 2 - Reactive. A company with little vision or direction, and still firefighting data quality issues by reacting to problems as they arise.
• Stage 3 - Proactive. A company that has decided it wants to implement MDM and has begun the process.
• Stage 4 - Managed. A company that has MDM in place in at least multiple departments, but still has improvements to make.
• Stage 5 - Optimize. A company that has MDM on an enterprisewide basis, and, as a result, information has become the golden asset of the business.

In general, Radcliffe said, most businesses land in either Stage 2 or Stage 3, with leading firms landing in Stage 4 and (for a very few) Stage 5. MDM's slow adoption, Radcliffe noted, is a result of the hugely disruptive impact any MDM initiative has on an enterprise's business processes, including:

• determining and classifying what data a business uses;
• determining common definitions that all departments within the organization can agree upon for that data;
• how that data impacts the company's business processes (and vice versa); and
• data governance issues such as access and maintaining data quality.

"It's a lot to digest," he said, "but only after this information is determined can a business start to consider the technology," Radcliffe said. The technology itself poses another problem, he added, thanks to "a highly fragmented vendor market." To this end, Radcliffe presented Gartner's "7 Building Blocks of MDM":

• MDM Vision
• MDM Strategy
• MDM Governance
• MDM Organizational
• MDM Business Processes
• MDM Technology and Solutions
• MDM Metrics to Measure Success

Because the deployment of MDM inevitably has wide-ranging impact, White contends that any initiative will also require a "fundamental shift in application architecture" -- a nod toward the services-oriented architecture (SOA) that is the foundation of any successful MDM project, offering data quality as a set of services to the entire enterprise. "Currently systems are developed and deployed in silos," White said. "MDM is going to change that as more businesses adopt it, and as SOA becomes more mainstream." SOA and MDM, he pointed out, "are systematically linked." Despite the repercussions of any MDM project, its business benefits can be "colossal," Radcliffe said, and can provide companies with:

• process optimization;
• compliance and risk management benefits;
• homogeneity across applications and disparate data sources;
• increased performance from operational sectors (such as CRM);
• a firm foundation for analytics and becoming a more predictive enterprise; and
• a data-driven foundation for the adoption and use of SOA.

These benefits are the main reason why 70 percent of Global 1000 companies will be using MDM by 2012, according to Radcliffe -- and yet they're not quite the finish line for business transformation. "Semantics are at the heart of MDM." he said. "MDM isn't the end-all silver bullet, but it's a big part of it, and addresses many of the fundamental issues that are driving corporations in the 21st century."

Related articles: Feature: Dirty Little Data Secrets CRM's real truth requires enterprises to clean up -- reorganize -- customer information with data integration solutions, Web-services technology that integrates data applications. Feature: The 2007 Market Awards: Data Quality Customer data is still king, but data quality is expanding to include other forms, such as financial and product data, along with master data management (MDM) solutions. The MDM Effect: Who Stands to Gain? A study finds businesses are turning to master data management solutions to improve their business intelligence results; data governance best practices are still key. DataFlux Accelerates the Path to MDM and CDI Version 8 of the company's flagship product introduces new, prebuilt Accelerators that assist customers in overcoming common data challenges associated with making the transition to MDM and CDI. MDM for Companies on the Go Purisma's new Data Hub product focuses on improving data accuracy while reducing implementation times, which one analyst says increases these types of solutions' value. Viewpoint: Master Data Management: Debunking Mega-Vendor Hype A flexible MDM platform delivers rapid return-on-investment. Viewpoint: Master Data Management: Considering the Customer First Get an enterprisewide system of record. Viewpoint: Demystifying Master Data Management The truth behind a successful MDM implementation. Master Data Management Studies and service offerings point to the need for better information herding.

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