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Do you have any advice for providing some structure for a new master data management project?

Question: We're about to embark on a master data management project at our company. I will be helping to write the charter, and I'll be ultimately working with our data stewards to maintain the master and reference data through an interface that will be built as part of the project. Our talented technical group has already begun to formulate an approach to the project, which concerns me, because our information architecture group isn't involved in these discussions. Do you have any advice for providing some structure for the project? Do you have any advice about drawing people into a discussion of the various approaches to this type of project, before they become too adamant about their approach?

Sid Adelman's Answer: A few thoughts:

  1. Does everyone who will be involved know what the project is trying to accomplish? If the goals have not been defined and communicated, the disagreements on approach and activities will swamp you.
  2. If you haven't done so already, create a glossary of terms and get buy-in from the participants.
  3. If the roles and responsibilities for the MDM project team have not been defined and communicated, they need to be. If you don't have someone in charge who can make assignments and be a decision-maker (the decider) you will bog down.
  4. People will be interested in participating if either they have an interest in the project or if they have an interest in the outcome, meaning how it will affect their jobs or their power/empire.
  5. Common goals and incentives go a long way toward furthering harmony.

Adrienne Tannenbaum's Answer: Master data management (MDM) is no different from any area of information or process management requiring a reusable enforced controlled standard. I actually have been discussing this template for a long time with metadata as a key element of the overall strategy.

Structure and productivity result from assigning master and reference data responsibilities to key groups - along with the ability of each "interest area" to also do their own thing when the impact on the corporate master world is not conflicting and their "also known as" aliases can easily be connected to the master name, value(s) and definitions.

Figure 1

Illustration of the implementation of any type of "master control" with "local freedom" scenario.

At the tier 3 level, people are "playing" so to speak. This is the world of the individual desktop - perhaps the individual developer, perhaps the spreadsheet creator, whatever. Once their world becomes confusing (they try to compare things, join things, etc.- and it sounds like you reached this point a long time ago), they join their desks, so to speak, and standardize a few things - like what "net profit" really means within their world, and how it is calculated. This "net profit" standard then moves to tier 2.

At the tier 2 level, each project has standards, or in the better world, each division or department or data warehouse has standards. Within each little group, the participants must use these in order to create useful and shareable items (whatever they may be) among themselves. For example, now that we have a standard definition of net profit, each individual will now be able to distinguish what they come up with from a recognized benchmark.

The tier 2 benchmarks are where we start our cross-interest group comparisons. Is the marketing definition of net profit one that represents a cross-interest group view? Is this view one that the entire "enterprise" can easily identify with? If so, the data stewards must now focus on moving this to the tier 1 enterprise master data and reference data world. But something should only fall into this category if it is already being shared across interest groups and adds efficiency to the organization. Master data failures are based upon their lack of usefulness to the majority.

Of course, there are some items that are no-brainers here. You already know what they are - those information values that appear everywhere because they already originate in the key enterprise domain.


Sid Adelman is a principal in Sid Adelman & Associates, an organization specializing in planning and implementing data warehouses, in data warehouse and BI assessments, and in establishing effective data architectures and strategies. He is a regular speaker at DW conferences. Adelman chairs the "Ask the Experts" column on www.dmreview.com. He is a frequent contributor to journals that focus on data warehousing. He co-authored Data Warehouse Project Management and is the principal author on Impossible Data Warehouse Situations with Solutions from the Experts and Data Strategy. He can be reached at (818) 783-9634 or visit his Web site at www.sidadelman.com.

Adrienne Tannenbaum is president of Database Design Solutions, Inc. (www.dbdsolutions.com), a New Jersey-based consulting firm specializing in the revitalization of corporate data. The firm focuses on data issues within large organizations and supports all data reconstruction efforts with a solid meta data backbone. Tannenbaum is the author of two popular meta data-focused books: Metadata Solutions: Using Metamodels, Repositories, XML, and Enterprise Portals to Generate Information on Demand (2001, Addison Wesley) and Implementing a Corporate Repository (1994, Wiley).

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