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Master Data Management: Debunking Mega-Vendor Hype
A flexible MDM platform delivers rapid return-on-investment.
Posted Sep 10, 2007
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Leading industry analyst firms Gartner and Forrester each claim that master data management (MDM) provides significant business benefits and is a critical foundation for managing enterprise information assets. IDC is predicting the MDM market to grow to $10.4 billion by the year 2009, with a compound annual growth rate of 13.8 percent. Not surprisingly, the market hype from the mega-vendors (IBM, SAP, and Oracle) has been deafening as each one attempts to position its single enterprisewide platform as a complete solution to your company's MDM strategy. Despite the flurry of activity, no one is talking about MDM in the same way, and there is no consensus on crucial questions that CIOs and executive management teams want to address. While MDM has come to the fore as a critical area of data management with each master data domain presenting unique challenges, MDM requirements have not yet coalesced into a coherent market. Rather, there is a strategic process requiring an adaptive approach to allow you to take immediate, substantive steps down the path toward MDM without compromising your ability to later adopt a full enterprisewide MDM platform. Master Data Defined Starting down the path toward MDM begins with an understanding of what constitutes master data. Master data includes the critical data entities and their common attributes which qualify a company's business events. Customer and product are the two most common master data domains. Invariably, firms begin with managing one domain (say, the customer data) and soon encounter the need to manage the other master data (such as products associated with a customer). Other well-established master data domains include location, employee, asset, and financial entities. However, there is often a debate whether certain data domains need to be treated as master data. For instance, should pricing be master data? What about contracts? Whether structured or unstructured, master data is best understood in the context of business processes. For example, in an order-to-cash process, a contract may be deemed as master data to be tied to customer data -- but associated with multiple accounts over time. While debates may rage on for some time, it is important not to be stymied by them: Simply begin your MDM journey with a confirmed master data domain, such as customer data.
Can Mega-Vendors Deliver on the Hype? At the organizational level, MDM is a cohesive strategy for managing all master data domains, whether product, customer, employee, asset, or financial. Each of these master data domains differ greatly. For instance, customer master data often originates from multiple sources, including several from outside the company. customer master data is often structured and well understood while typically following a "business party" model. On the other hand, product master data is usually generated internally and shared among suppliers. The characteristics of product master data -- such as in a product catalog or an item master -- are both structured and unstructured while requiring a "hierarchical" data model. It is being debated whether any mega-vendor today can handle these differing requirements in a single integrated MDM platform. But here is the more pertinent question to ask: Is centralizing on a single mega-vendor MDM platform even necessary? If the promises of services-oriented architecture (SOA) coming from mega-vendors are indeed true, then why not select different best-of-breed solutions that work together to deliver the most suitable solution? Shouldn't each MDM solution leverage your past investments in data integration infrastructure, legacy data hubs, and external data sources? Perhaps, the more critical question to ask is: Where is your organization most likely to derive business value from an MDM platform? Adaptive Master Data Management Many companies are finding that the simplest route toward MDM involves initially deploying one master data domain for a specific business need, and then extending to other data domains over time. Which data domain to start with will differ by industry. For example, it may be customer data in high-tech, doctor or hospital data for a pharmaceutical company, counterparty reference data in institutional banking, or product data in retail. By starting with a single data domain, companies are able to achieve immediate ROI in an identified area, typically in less than six months' time. However, the key to this approach is to select an adaptive MDM platform that can easily be extended to different data domains over time to meet future requirements. An adaptive MDM platform should not only support SOA and allow you to coexist with existing data hubs, data sources, and the larger application platforms; a successful platform should also allow you to evolve the architectural style over time across the organization. Remember: MDM is a strategic process and while mega-vendors are vying for dominance, each master data domain presents unique challenges. An adaptive approach is necessary to meet these challenges and enable you to start down the path to MDM without compromising your ability to evolve toward an enterprisewide master data management platform. About the Author Anurag Wadehra is Vice President of Marketing and Product Management at Siperian, developers of an award-winning adaptive platform for master data management. For further information, contact the author at awadehra@siperian.com
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