MDM for Business Value: New Approaches

MDM for Business Value: New Approaches

MDM for Business Value: New Approaches

Master data management is entering an ‘evolutionary’ era where MDM implementations better mirror how businesses use data for numerous purposes, and where people, practices and processes come to the forefront as essential elements. MDM functioned as yet another solution space that was harmed by disproportionate attention to its underlying technologies. But MDM has always been far more about business objectives and needs, as well as the problems to be solved to achieve them. Along with a more overt “de-emphasis” on technologies, we are now seeing more vendors enabling the critical integration of technologies, people, practices and processes with near term and long term business objectives, to achieve the successful utilization of MDM programs.

A major change to MDM approaches calls for combining technology and non-technology paradigms, to reflect the new reality that the business world isn’t just “relational”. Relationship (network / graph) data continues to grow in importance – but traditional row-and-column databases are inadequate to properly handle such data. MDM approaches and technologies must now process complex connections, hierarchies and relationships between multiple entities / domains. Organizations want to go beyond traditional transactional data to capture data that describes behavioral aspects that can amplify context.

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Out with the Old

Over the years, organizations often took wrong turns with MDM by relying on problematic approaches like “big bang” or “bottom up”. Either way has usually resulted in big problems and poor outcomes. And both of these approaches have had a history of focusing too much on IT driving the MDM initiative, while failing to incorporate the voices of essential business stakeholders. These traditional approaches usually take too much time, carry too much risk, and end up being too expensive — often not even achieving essential objectives.

Successful MDM projects require strategic vision that connects to current and future business needs and objectives. But too often organizations have decided that ‘strategic vision’ means tackling a large scope of work (“big bang”), instead of fleshing out the right strategies before starting any work. Organizations that attempt to execute an entire MDM strategy at once encounter significant obstacles including serious cost overruns, project management turmoil, and chaotic use of IT resources.

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The “bottom up” approach relies on IT and / or lower level managers to drive the MDM effort, while disregarding vital upper management and business stakeholders. Often disconnected teams work in silos, but are expected to somehow arrive at the same “desired end state”. This introduces the near-impossible task of trying to orchestrate non-collaborative work.

Obviously new approaches for MDM are made better, or even possible, because of newer technologies. But MDM technology by itself will fail to achieve what businesses need. Of primary importance is the work done to establish the right vision and conceptual framework for what master data can accomplish for the business. Organizations need to develop hierarchies of strategies, plan processes and practices, make decisions for design and modeling – among the many preparative tasks that usually ensure more effective utilization of MDM. Then organizations can build out from there, ultimately considering which technologies should be implemented.

Offerings from new MDM vendors and fresh approaches by established vendors are responding to what organizations need and want from master data: centralized reliable data that reflects how organizations work and the kinds of data they need, increasingly in real time contexts. MDM is moving towards faster implementations, broader capabilities in a single extensible platform, and the ability to work with any kind of data.

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