What Master Data Management Metrics Matter?

I recently had a client ask about MDM measurement for their customer master.  In many cases, the discussions I have about measurement is how to show that MDM has "solved world hunger" for the organization.  In fact, a lot of the research and content out there focused on just that.  Great to create a business case for investment.  Not so good in helping with the daily management of master data and data governance.  This client question is more practical, touching upon:

  • what about the data do you measure?
  • how do you calculate?
  • how frequently do you report and show trends?
  • how do you link the calculation to something the business understands?
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The Great Divide: MDM and Data Quality Solution Selection

I just came back from a Product Information Management (PIM) event this week had had a lot of discussions about how to evaluate vendors and their solutions.  I also get a lot of inquiries on vendor selection and while a lot of the questions center around the functionality itself, how to evaluate is also a key point of discussion.  What peaked my interest on this subject is that IT and the Business have very different objectives in selecting a solution for MDM, PIM, and data quality.  In fact, it can often get contentious when IT and the Business don't agree on the best solution. 

General steps to purchase a solution seem pretty consistent: create a short list based on the Forrester Wave and research, conduct an RFI, narrow down to 2-3 vendors for an RFP, make a decision.  But, the devil seems to be in the details.  

  • Is a proof of concept required?
  • How do you make a decision when vendors solutions appear the same? Are they really the same?
  • How do you put pricing into context? Is lowest really better?
  • What is required to know before engaging with vendors to identify fit and differentiation? 
  • When does meeting business objectives win out over fit in IT skills and platform consistency?
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