There are two kinds of organizations: those that have implemented a master data management (MDM) solution, and those that haven't but undoubtedly will in the near future. Despite where each organization may be in their MDM effort, what each have in common are questions about achieving better business processes. Companies planning an MDM implementation tend to have important questions regarding vendors, strategies and creating road maps to ensure success and a healthy return on investment. Fortunately, these companies can learn and benefit from the experiences of organizations that have pioneered MDM and organize their efforts around a common set of principles. For those organizations whose initial MDM efforts brought early success, the question is: how can the lessons learned be leveraged to drive more effective data governance across other lines of business and more elements of the system's infrastructure?

Some first-generation MDM adopters have been able to build on their initial implementations to address other important business problems. Observing these efforts, certain IT analysts and industry observers are beginning to publish articles laying out models for taking MDM implementations from the early planning stages through to mature, second- or third-generation stages. Many of these observers advocate an incremental approach, usually based on a particular data type or within a single system, such as a data warehouse. Others advocate targeting a single architectural style, such as a registry style, and then building on that implementation to address other styles, such as collaborative, transaction or hybrid.

The reasoning behind this type of approach follows a conservative "technology maturity curve" as a way to keep data governance requirements in check and the overall risk of failure as low as possible. These are legitimate concerns, and many organizations have been able to realize modest gains in solving their master data problems by following these precepts. However, limiting the scope of your initial MDM implementation is also likely to constrict the potential for greater success and return on investment down the road.

The true promise of MDM is that it enables the organization to create a single, clean and correct version of its most important reference data, and eliminate the business process inefficiencies that arise from conflicts in various data sources. This is why it is far more effective to organize MDM implementations around specific business problems such as compliance objectives, business process optimization, customer on-boarding, financial risk management and so forth.