NOV 26, 2008 3:41am ET

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Easing Into Master Data Management


In my blog, I‘ve outlined the five essential elements of master data management (MDM):


  1. An MDM hub of some type,
  2. Data integration or middleware,
  3. Data quality capabilities,
  4. External content and
  5. Data governance.

One of the challenges of MDM is trying to make progress in all five of these areas at once, while simultaneously working across the spectrum of people, process, technology and information.


Think of it as the “big bang” approach to MDM. You evaluate and select an MDM hub, and in the process, you discover that your organization doesn’t have adequate data integration or data quality tools available. And while working with the business on what internal source systems and external content providers need to be integrated with the new hub, you realize that your organization finally needs to get serious about data governance as well. It can be a little overwhelming.


In the current economic climate, some companies won’t have much appetite for spending large amounts of money on multiyear MDM projects, and I’ve heard people argue that MDM should always be phased in gradually. Every company’s situation is different, and MDM projects are sometimes so strategic that they are immune to short-term economic ups and downs.


However, what if your company wants the benefits of MDM, but can’t commit to large strategic initiative all at once? Does that mean that there’s no hope and the visionary data champions who work at those companies are out of luck? Thankfully, no. Start with data governance. Build a small data governance program around existing source systems, people and technology. It may be a far cry from the high-impact data governance organization you’d ultimately like to build, but it will get you started and allow you to socialize data governance as a concept, get the business owners involved and show some results that will hopefully make the rest of the process a little easier.


You’ll need to find the people currently working with critical master data and bring them together, changing their roles to include active data stewardship. You’ll need a small data governance council to make corporate policy on ownership questions and to make decisions on business rules and other issues. You’ll also need at least some support from the C-suite, so people don’t think you’ve started building a data governance fiefdom without active executive support.


On the data integration question, spend some time investigating your current integration capabilities.  Hopefully, your company has evolved beyond the “custom code for everything” stage and at least has some extract, transform and load (ETL), metadata management tools or publishes and subscribes tools. If you’re lucky, you’ll find out that you’ve already got a robust data integration tool in-house and ready to go. If not, you’ll be better informed about past struggles with data integration at your company and better prepared to fold that into your MDM initiative at the proper time.


A similar approach to data quality is worthwhile. Figure out what data quality tools your company has and uses, and look into whether it would make sense to use them in your MDM plans. A surprising number of companies still have no data quality tools, and they rely on handwritten SQL programs or “eyeballing” thousands of rows of data in Excel to find and fix data quality issues. If that’s the case at your company, you may find that you’re not ready for MDM anyway, and that you’ve got to resolve one or more of these issues before tackling MDM.


For one client, I mapped out a strategy to begin with a small scale “just in time” data governance program. At the same time, I redefined how they worked with their main external content provider:

After about six months for that phase, the roadmap included selection and implementation of a robust data quality tool. Initially, they worked with their newfound data stewards and fed data quality improvements back to their legacy applications and source systems. Eventually, the data quality platform would be tightly integrated with the MDM hub they are planning to invest in later on.


About one year into the roadmap, as preparation for the MDM project, we mapped out an upgrade to a new service-oriented architecture-based data integration technology, which gave them the ability to move data around the enterprise in both real time (as a service) and in large batches. Having done all this, they were ready to tackle the selection and implementation of an MDM hub with a new data governance organization, more rational use of external content and new data quality and data integration technologies to build on.


Keep in mind that this organization is very large - the timeline might be shorter for a smaller, less complex company.  

So if your budget doesn’t permit the ultimate MDM wish-list project, ease into it by building a data governance program first, with existing resources and applications. Revisit how you think of external and internal information sources. Tackle data quality and data integration tool implementations as predecessor steps to MDM. Then, with your successes documented in your MDM business case, you can add a robust MDM hub into the infrastructure you’ve been building, with a much higher chance of succeeding and a track record of wins along the way that have delivered real business value.

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