What is MDM (Master Data Management)?
Master data management (MDM) is the practice of defining and maintaining consistent definitions of business entities (e.g., customer or product) and data about them across multiple IT systems and possibly beyond the enterprise to partnering businesses. MDM gets its name from the master and/or reference data through which consensus-driven entity definitions are usually expressed. An MDM solution provides shared and governed access to the uniquely identified entities of master data assets, so those enterprise assets can be applied broadly and consistently across an organization.
Top 10 Priorities for Next Generation MDM
1. Multi-data-domain MDM Many organizations apply MDM to the customer data domain alone,and they need to move on to other domains, such as products, financials, and locations. Singledata-domain MDM is a barrier to correlating information across multiple domains.
2. Multi-department, multi-application MDM MDM for a single application (such as ERP, CRM,or BI) is a safe and effective start. But the point of MDM is to share data across multiple,diverse applications and the departments that depend on them. It’s important to overcomeorganizational boundaries if MDM is to move from being a local fix to being an infrastructurefor sharing data as an enterprise asset.
3. Bidirectional MDM “Roach motel” MDM is when you extract reference data and aggregate it in a master database from which it never emerges (as with many BI and CRM systems). Unidirectional MDM is fine for profiling reference data, but bidirectional MDM is required to improve or author reference data in a central place and then publish it out to various applications.
4. Real-time MDM The strongest trend in data management today (and BI/DW, too) is toward realtime operation as a complement to batch. Real time is critical to verification, identity resolution, and the immediate distribution of new or updated reference data.
5. Consolidating multiple MDM solutions How can you create a single view of the customer when you have multiple customer-domain MDM solutions? How can you correlate reference data across domains when the domains are treated in separate MDM solutions? For many organizations, next generation MDM begins with a consolidation of multiple, siloed MDM solutions.
6. Coordination with other disciplines To achieve next generation goals, many organizations need to stop practicing MDM in a vacuum. Instead of MDM as merely a technical fix, it should also align with business goals for data. MDM should also be coordinated with related data management disciplines, especially DI and DQ. A program for data governance or stewardship can provide an effective collaborative process for such coordination.
7. Richer modeling Reference data in the customer domain works fine with flat modeling, involving a simple (but very wide) record. However, other domains make little sense without a richer, hierarchical model, as with a chart of accounts in finance or a bill of materials in manufacturing. Metrics and key performance indicators—so common in BI, today—rarely have proper master data in multidimensional models.
8. Beyond enterprise data Despite the obsession with customer data that most MDM solutions suffer, almost none of them today incorporate data about customers from Web sites or social media. If you’re truly serious about MDM as an enabler for CRM, next generation MDM (and CRM, too) must reach into every customer channel. In a related area, users need to start planning their strategy for MDM with big data and advanced analytics.
9. workflow and process management Too often, development and collaborative efforts in MDM are mostly ad hoc actions with little or no process. For an MDM program to scale and grow, it needs workflow functionality that automates the proposal, review, and approval process for newly created or improved reference data. Vendor tools and dedicated applications for MDM now support workflows within the scope of their tools. For a broader scope, some users integrate MDM with BPM tools.
10. MDM solutions built atop vendor tools and platforms Admittedly, many user organizations find that homegrown and hand-coded MDM solutions provide adequate business value and technical robustness. However, these solutions are usually in simple departmental silos. User organizations should look into vendor tools and platforms for MDM and other data management disciplines when they need broader data sharing and more advanced functionality, such as real-time operation, two-way synchronization, identity resolution, event processing, service orientation, and process workflows or other collaborative functions.