The landscape of Master Data Management (MDM) is evolving, and organizations that rely on legacy MDM systems built on probabilistic matching are facing increasing challenges. Rising subscription costs, scarce skilled resources, and aging technology with limited investment are causing many businesses to rethink their MDM strategy. However, transitioning to a modern MDM solution isn’t always straightforward. The question many long-term MDM users, like those on IBM Initiate, are asking is: How do we modernize without completely replacing our existing system?
To address this challenge, we explore three strategic augmentation approaches that organizations can take to modernize legacy MDM systems while continuing to derive value from their existing investments.
Why Modernization is Necessary
Legacy MDM systems have been a cornerstone for many businesses, but organizations are increasingly encountering roadblocks such as:
- High maintenance costs – Subscription and operational costs continue to rise.
- Limited expertise – Fewer resources are available to support and optimize IBM MDM.
- Aging technology – A lack of significant investment in updates and innovations.
Despite these challenges, completely replacing an existing MDM isn’t always feasible in the short term. Instead, businesses can take an incremental approach to modernization, adding value while gradually reducing dependency on the current MDM.
Three Ways to Augment and Modernize IBM MDM
1. Automating Duplicate Resolution with Advanced Matching
One of the core challenges with MDM is resolving duplicate records. Many organizations still rely on manual review processes to confirm duplicate suspects, which is time-consuming and costly.
Solution: Implement an Auto Stewarding solution that leverages advanced AI-driven referential matching to automatically resolve duplicate records.
Case Study: A major U.S. insurance company using IBM as their MDM had a backlog of 4 million duplicate suspect pairs. By augmenting IBM MDM with an automated stewardship solution, 75% of these duplicates were resolved without human intervention. This not only reduced operational costs but also significantly improved the accuracy of customer data, leading to better decision-making and enhanced customer experiences.
2. Building a Data Mesh for Customer Domain Services
Another common issue with IBM MDM is its tight integration with business applications, making it difficult to adapt to new business needs, integrate AI, or incorporate external data sources.
Solution: Develop a data mesh that abstracts IBM MDM’s customer data services and integrates them into a more flexible, scalable architecture.
Case Study: A U.S.-based financial services firm used IBM MDM for customer account management but struggled to unify customer data across different personas, such as marketing prospects and financial instrument assignees. By implementing a modern data mesh strategy, they:
- Discovered 2 million missed matches
- Improved customer retention by 10% through better journey analytics
- Enhanced fraud detection and claims processing efficiency
By abstracting IBM MDM’s services and integrating additional data sources, organizations can future proof their MDM strategy while increasing agility.
3. Incremental Transition to a Next-Generation MDM
For many organizations, the long-term goal is to fully replace IBM MDM with a cloud-native, AI-powered MDM solution. However, making the business case for a full replacement can be challenging.
Solution: Instead of a rip-and-replace approach, organizations can adopt an iterative migration strategy, where IBM MDM is gradually phased out while modern solutions are implemented alongside it.
- Start by augmenting IBM MDM with modern MDM capabilities
- Capture new business value with each augmentation
- Abstract IBM MDM dependencies to ease the transition
This step-by-step approach ensures business continuity, allows for a smoother adoption process, and maximizes ROI over time.
Final Thoughts: A Smarter Path Forward
The transition from IBM MDM to a modern MDM strategy doesn’t have to be overwhelming. By leveraging augmentation strategies such as automated stewardship, data mesh abstraction, and phased migration, organizations can minimize risks while unlocking significant business value.
If you’re interested in discussing tailored augmentation strategies for your organization, let’s connect. The future of MDM is here, and with the right approach, you can modernize your MDM while staying ahead in 2025 and beyond.
Learn more about best practices, pitfalls and success with MDM in our upcoming webinar, register here.
