How to Execute Your Master Data Strategy

Master data is increasingly becoming the most important data companies have. It’s the key to managing, organizing and transporting data to make it relevant across the business. NetApp recently shared five tips for how they implemented a master data program within their organization. Speaking from practical experiences, they revealed that companies making a foray into master data need to be nimble, on the same page, thinking about governance, aligning with the C-suite, and continually articulating the value. Now, we’re turning to the experts helping companies like NetApp make their master data goals a reality. We sat down with Dun & Bradstreet’s Distinguished Architect of Master Data, Elizabeth Barrette, to learn more about how companies should approach executing a master data strategy.

Master data is not easy; it’s a time-consuming, labor-intensive process. In fact, it’s often been referred to as a grand journey. That said, can you share some of the things you’ve seen that have failed? What are some of the roads companies shouldn’t be taking on this journey?

Barrette: It always surprises me how often companies are blinded by their own data quality . They look across all their disparate systems and choose one where they think the data is the best and they choose the data from that system as their primary source. From there they take the data from all their other systems and match it to their primary source. It could be bad data matched to bad data and this could end up creating bad decisions. A gold standard is very difficult to create internally. The most successful master data programs look to third parties to help in the mastering of their data. Using a third party helps ensure data quality.

Another pitfall is organizations that allow the continuation of data silos. Making sure your teams work together is really one of the only ways that you can see success happening and ultimately gain value within your master data program. If somebody’s building it, using it, improving it, if someone is getting additional value from it, it’s a real relationship. Siloes can’t be tolerated .

What are some examples where companies are doing the right thing?
Barrette: As a solution architect on the data side, I’ve seen a reoccurring change with technology businesses who were some of the first to implement master data programs 10 to 15 years ago. They are sunsetting what they previously built and reengineering their master data strategies. They are thinking more holistically and futuristically on the changing times, especially on how to match the influx of data, and the speed of data. They are engineering processes that are mastering data on the fly. The best practice is to master data as soon as new data is created. It’s an interesting transition to see how these changes are driving greater value and insights faster than ever before. Essentially, it’s okay to start from scratch.

Is it unfair to expect to start seeing ROI from a master data strategy right out of the gate?
You want to make sure that your master data program is at the forefront of your business strategy, that you’re driving value throughout the entire time.
Elizabeth Barrette, Distinguished Architect, Dun & Bradstreet

Barrette: Actually, you want to show value as early as possible! It comes back to the idea of being on a journey, not working on a one-off project. Businesses can get frustrated if they are not seeing continuous value. You hear a lot more about agile environments. You don’t have runway to show the value of your program, you don’t have years to put together your master data program. You want to make sure that your master data program is at the forefront of your business strategy, that you’re driving value throughout the entire time.

Let’s take a minute to talk about data governance. Many companies don’t equate that to master data.