Selection Criteria for Master Data Management
According to TDWI’s recent next generation master data management (MDM) survey, half of users surveyed are planning to replace their primary MDM platform within the next three years. Ripping and replacing a platform is time-consuming, expensive, and disruptive for the business. So why would so many users contemplate such a drastic action?
According to the survey, users are looking for a more feature-rich tool that can support them in the mid-to-late life cycle stages of their MDM program. This usually involves MDM functionality considered more mature or advanced, namely multiple data domains handled via a single tool, registry or hub-based architecture, matching for reference records, workflow for change management, and a few data quality and data integration functions. As users struggle to evolve MDM into an enterprise infrastructure, they need bus-based MDM services, multi-system synchronization of reference data, and scalability to millions of reference records. Users might also consider very advanced features for mobile MDM, MDM analytics, and multidimensional repository modeling.
Instead of investing in a platform or homegrown solution that will eventually require rip and replace, user organizations should future-proof their MDM investments by selecting MDM tools and platforms that have a mature set of functionality they can grow into.
What You Will Learn:
- Common generations or life cycle stages of an MDM program
- MDM tool functionality associated with these
- Impact on the business of MDM life cycle stages and tool functionality
- Several tips for future-proofing MDM tool selection and use, so you can get the most from your tool and avoid rip and replace
- A vision for the high end of mature MDM solutions, plus how to get there incrementally
Philip Russom, Ph.D.