The term “contextual Master Data Management” has been floating around in a couple of years as for example when tool vendors want to emphasize on a speciality that they are very good at. One example is from the Data Quality Management leader Precisely in the August 2020 article with the title How Contextual MDM Drives True Results in the Age of Data Democratization. Another example is from the Product Information/Experience Management leader Contentserv in the 2017 article with the title Contentserv Expands its Portfolio with Innovative Contextual MDM.
We can see contextual MDM as smaller pieces of MDM with a given flavour as for example focussing on sub/overlapping disciplines as:
- Product Information Management (PIM)
- Product Experience Management (PXM)
- Product Data Syndication (PDS)
- Data Quality Management (DQM)
- Customer Data Platform (CDP)
The focus can also be at:
- A given locality
- A given master data domain as customer, supplier, employee, other/all party, product (beyond PIM), location or asset
- A given business unit
You must eat an elephant one bite at a time. Therefore, contextual MDM makes a good concept for getting achievable wins.
However, in an organization with high level of data management maturity the range of contextual MDM use cases, and the solutions for them, will be encompassed by a common enterprise-wide, global, multidomain MDM framework – either as one solution or a well-orchestrated set of solutions.
One example with dependencies is when working with personalization as part of Product Experience Management (PXM). Here you need customer personas. The elephant in the room, so to speak, is that you have to get the actual personas from Customer MDM and/or the Customer Data Platform (CDP).
In having that common MDM solution/framework there are some challenges to be solved in order to cater for all the contextual MDM use cases. One such challenge, being context-aware customer views, was touched upon in the post There is No Single Customer 360 View.