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The MDM Institute predicted that in 2008, the master data management (MDM) market will continue to transition from early adopter to mainstream, with more than 95 percent of some industries actively exploring replacements to their homegrown MDM solutions.¹

As with all hot initiatives, there's often a rash of hype and interest from vendors looking to jump on the bandwagon. Suddenly, every vendor has an MDM success story to tell. Analysts and vendors contradict each other as they highlight which route they think you should take.

When overwhelmed by market information, companies need to evaluate the needs of their organizations and tailor an MDM program that will best meet those needs. Before you even begin to look at vendors and technology, you need to appreciate that MDM is a long-term program - a corporate discipline - not a one-time project. Think of MDM's function as similar to the finance function in your organization, except it manages data assets rather than financial assets.

Getting Started

First, you need to set an expectation: MDM will never be easy. No amount of technology will make it a turnkey operation. There is no single approach that will work for all - or even for most. By nature, MDM needs to be highly customized to the needs of your organization. And while IT organizations have to be involved in the adoption of MDM, the content of the data is inherently the responsibility of the business. So the real challenge is - how do you get started?

First, stop worrying about implementing "master data management." Take stock of your individual environment and business needs, figure out what will make the biggest impact on your organization and focus on addressing that problem.

Recognize that regardless of where you start, you'll need to address inherent data governance issues. Unlike automated data quality, master data requires human judgment (and therefore governance) at some level. A business can tackle a small piece of the data in the organization - finance data, perhaps - to learn how to develop data governance practices and use MDM tools to effectively manage the process in a way that works for it.

You hear a lot about the different kinds of MDM, but there are really two primary use cases: MDM for operational purposes and MDM for analytical purposes. Both manage master data, and both seek to get a single view of the data. However, they differ in where and how they plan to use that golden copy of master data.

Operational MDM

The focus of operational MDM is to make sure that data in multiple operational systems that should be the same is actually the same. The goal is to synchronize operational systems data so that you have consistency at the front end, such as in customer-facing systems, which is particularly important for organizations with a lot of customer contact.

Companies that favor adopting an operational MDM approach first are often focused on improving their operational efficiency or creating synchronized records. They may have a customer service issue, where an individual customer's account information is scattered across multiple systems, leading to a disjointed customer experience. Or they may be concerned with process consistency and are seeking to reduce process errors (such as delivering the wrong products to the wrong location). They may be actively looking into a service-oriented architecture (SOA), which needs consistent master data to work properly. Or they may be looking for better supply chain consistency in working with partners and throughout their product line.

In theory, regardless of the primary driver, once a company has synchronized their master data across all operational systems, they won't need to harmonize that master data for business intelligence (BI) because the data will already be consistent. In practice, however, MDM is such a new market that few, if any, companies have truly synchronized all their systems, and to get to this stage will take many years, probably decades. Most companies have smartly tackled a small portion of that to increase the chances of success. As a result, many who wish to deploy a holistic MDM program find that they need to tackle components of the solution separately in the near term.