There is evidence that the master data management (MDM) movement is maturing, as organizations consider the incorporation of data quality and data governance processes to supplement the emergence of master data systems. Yet, there is room for improvement, and for those intrigued by the potential benefits of MDM, it is worthwhile to understand the potential pitfalls and potential “stalls” in a successful deployment.
Some of the barriers to success are “people related”—a lack of understanding who the consumers of master data are or their expectations, and failing to ensure that the MDM framework meets their needs. Others are “data related,” where data consolidation greatly magnifies the impacts of minor differences across data subsystems. Some barriers are systemic issues related to modeling, standards for information sharing, or general data governance and oversight.
This TDWI Checklist Report reviews opportunities where anticipating potential roadblocks can help improve planning, identify issues early in the program, and generally eliminate barriers to MDM success.
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