Andrew White

A member of the Gartner Blog Network

Andrew White
Research VP
8 years at Gartner
22 years IT industry

Andrew White is a research vice president and agenda manager for MDM and Analytics at Gartner. His main research focus is master data management (MDM) and the drill-down topic of creating the "single view of the product" using MDM of product data. He was co-chair… Read Full Bio

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More on The Perils and Pitfalls of Managing Master Data “Inside” ERP Systems

by Andrew White  |  May 10, 2013  |  1 Comment

I wrote, “The Perils and Pitfalls of Managing Master Data “inside” ERP Systems” April 24th.  Unfortunately I did not get to see the comment, or get to replay, until after our self enforced time limit for comments expired.  So I apologize for getting so long to back to this topic and comments.

Here is my response to Sowmindra.

Thanks for leaving a comment.

You ask a good question.  We tend to call the set of questions related to “where the master data resides” as “implementation styles” type questions.  That is, the degree to which the data is instantiated.  We have seen a wide array of requirements that favor a centralized approach (push out), a registry approach (point to), as well as a consolidated approach (collect and harmonize).  All three styles have, to varying degrees, worked for operational/transactional MDM situations.  There are also some industry specific “favorites” such as registry for patient data in healthcare.  So there does not seem to be one answer to your question.  We distilled the more notable characteristics that end user organizations consider in this discussion in a note we updated in 2011: The Important Characteristics of the MDM Implementation Style – Update.  My colleague, Lyn Robison, also tackled the same question and drilled down on the decision drivers in more detail with A Comparison of Master Data Management Implementation Styles in October 2012.

IBM’s book, Enterprise Master Data Management (2008), is a pretty good resources for some of this dialog, but even it has a few gaps and the models in the book do not align quite with ours (which makes using the rest of the research harder than it needs to be).  Most other so-called MDM books really don’t cover all the basis at all; mostly because the authors only have limited exposure or experience with one type of master data (i.e. Customer), or one industry (i.e. banking).  One needs a wide array of experiences to spot the real patterns in this topic.

Again, sorry for lateness. 

Andrew

1 Comment »

Category: Implementation Style Master Data Management MDM     Tags:

1 response so far ↓

  • 1 Michele   May 16, 2013 at 2:30 am

    Hi Andrew,
    could you share a couple of gaps you spotted in IBM’s book?

    Thank you.
    Michele