Are you doing MDM, data integration, or data quality?

Imager from pxfue

In a 2012 post, titled MDM without data governance is ‘data integration’, not MDM!, Gartner’s Andrew White made several observations that are still relevant, and poorly understood, today.

  1. Andrew argues that Master Data Management is “data governance applied to master data.” For him then, consolidating data without governance is simply data integration. We have all seen attempts to deliver master data without governance become long, drawn out integration processes ending in yet another muddy backwater of poor quality data. We suggest that master data management is intended to create a consistent, quality set of critical data for reuse across systems and processes. Governance and data quality are critical for success!
  2. We also agree that master data management is not a technology. One of the big challenges of technology first approaches, irrispective of the platform chosen, is that they tend to suffer from a lack of business engagement, and, as a result a lack of buy in. In our master data management implemention approach we recommend that technology selections are made relatively late in the process – after clearly defining the business problem, identifying key stakeholders and decison makers, and building a sound understanding of your master data landscape i.e. where master data lies (in various operation and analytical systems) and how it is used. In other words, governance comes before technology selection and helps to guide the selection of the technology. Of course, the right mdm tool can reduce risk and make the implementation simpler.

Andrew makes the following excellent point:

“MDM is not a project!  MDM is a program, that will spawn off and launch all manner of projects, that span and include DQ work, DI work, deployment of a hub, data modeling, and the list goes on.  None of these individually “are” MDM.  But when organized in a specific way, oriented around a discipline to change the way in which the business users crate, use and abuse their own data, and then MDM persists.”

Sort out the data governance, and the data quality, and the master data management will take care of itself.

We need to shift the mind set that MDM is a big integration project, planned over a number of years, that must consolidate all master data before it can add value. An approach (and technology selection) that allows master data building blocks to be delivered quickly, and then can be added to over time, will show value soon, and add incremental value with time. Data governance helps to define the priorities for these building blocks, and ensures the allignment to the business outcomes. It is the right place to start.