Contextual MDM vs Enterprise-Wide, Global, Multidomain MDM

The term “contextual Master Data Management” has been floating around in a couple of years. We can see contextual MDM as smaller pieces of MDM with a given flavour as for example focussing on sub/overlapping disciplines as:

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).

The list of solutions on this site covers both one-stop-shopping options for all contextual MDM use cases and specialised solutions for a given contextual MDM use case. Check the growing list here.

An MDM / PIM / DQM Easter Egg

It is high season for painting Easter eggs now.MDM PIM DQM Easter EggThis egg is featuring:

  • Master Data Management (MDM),
  • Product Information Management (PIM) and/or
  • Data Quality Management (DQM)

as well as:

  • Application Data Management (ADM),
  • Customer Data Integration (CDI),
  • Customer Data Platform (CDP),
  • Digital Asset Management (DAM),
  • Product Data Syndication (PDS),
  • Product experience Management (PXM) and
  • Reference Data Management (RDM)

Check out the 10 data management TLAs on this list here.

Master Data, Product Information, Reference Data and Other Data

There is a trend on the data management market that the solutions are either going very niche (best-of-breed) in the data domain covered or they are encompassing a broader range of data types.

This can be seen in the spectrum of master data and product information as reported in the post MDM, PIM or Both.

We also see that governance and management of reference data is included in addition to managing master data as told in the post What is Reference Data Management (RDM)?

Some MDM (and RDM) solutions also extend the reach to cover aspects of transaction data and big data. The main scenarios covered are:

  • Matching of party entities in traditional systems of record with the parties referenced in social streams and weblogs (systems of engagement) as well as in sensor data. This can be used in creating a Customer Data Platform (CDP).
  • Extending data quality and data performance dashboards related to master data to cover aggregated transaction data and big data held in data warehouses and data lakes by using a shared set of reference data.

When product information is to be shared in business ecosystems through Product Data Syndication (PDS), this can be accelerated by using a data lake concept and new data stores as staging areas. This is due to that a main challenge here is that the data quality standards on the providing side most often are different from the data quality standards on the receiving side.

MDM PIM RDM and other data

The diagram is a variation of a diagram included in the whitepaper Intelligent Data Hub – Taking MDM to the Next Level. The original is developed together with Salah Kamel, CEO at Semarchy