On Sept 19, 2012, renowned MDM expert Andy Hayler will review “Best practices in MDM vendor selection” in an hour long webcast, sponsored by Orchestra Networks. In the lead up to this exciting session with The Information Difference, we have decided to examine several facets of the master data problem that are commonly overlooked when companies plan their MDM programs. And by MDM, we mean master data management. This is not to be confused with mobile device management (the other MDM that Gartner covers).
Master data is defined as data shared across business teams and IT application, that defines key information of a company such as products, organization, customers, suppliers, financial hierarchies, assets, locations or reference codes. A Master Data Management platform will help defining, managing, sharing and governing all those shared data in a central solution where business users can collaborate and application consume it in a secure, consistent way.
Master data is a complex, multifaceted object. It relies on a definition, has relationships with other master data (and itself), lives sometime in past, present and future, needs to be adapted to multiple contexts, has various owners across the organization, is based on a specific life cycle and integrates with applications using many patterns.
Not only is master data complex, but all your master data have different characteristics. So before you launch a project or shop for an MDM software, we think it is important to understand those various facets. It will have an impact not only on your vendor selection, but also in the way you will conduct the initiative and ultimately get adoption – and success – of MDM across the enterprise.
In the popular literature, some but not all, of the characteristics that one should look for in an MDM platform are documented. In this series we’ve decide to focus on the gaps, the areas that can be the tipping point between project success of failure. Over the next several weeks, we plan on examining the following factors that we believe are overlooked by many when evaluating an MDM platform:
1. Modeling – Documenting and defining your master data
2. Relationships – Managing the intra and inter-domain relationships in your data
3. Time – Going beyond simple versioning
4. Points of entry – How does you master data get in?
5. Business context – Sharing master data across groups, divisions and functional areas
6. Governance/Lifecycle – Managing different scopes
7. Integration – How does your master data get out?
As per usual, we welcome any comments or questions!
By Conrad Chuang