Best Practices for Developing a Master Data Management Strategy

Master data management strategy (MDM) refers to the governing procedures for entering, aggregating, consolidating, de-duping, standardizing, and maintaining data en masse throughout an organization. By ensuring control and reliability, MDM creates a single source of master data that can be applied and maintained by many different entities throughout a business.    

Companies increasingly need cost optimization, faster product launches, and more efficient regulatory compliance, and having an effective Master Data Management strategy is critical for all of that to happen. Without it, cross-organizational data misalignment can lead to sub-optimal decision making and decelerated growth. But developing a Master Data Management strategy and putting it into practice across an organization is no simple task, and achieving dependable data quality is one of the biggest pain points for enterprises. 

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Creating a Good Master Data Management Strategy

There are several best practices your enterprise should consider when developing and implementing a master data management strategy:

MDM is not one and done: Your Master Data Management strategy should be woven into the foundation of your business. If data alignment is considered merely a one-time occurrence, you will encounter the same data mismanagement issues repeatedly.

Buy-in at the top: For MDM to be successful, leaders within all business units must be engaged in the development of the strategy, as well as continuously involved in ongoing governance conversations.

Education is key: On the other hand, all personnel and departments must be trained and regularly retrained on how to format, enter, store, and access data.

Start small, but think big: When rolling out a new MDM strategy, you want to first focus on a smaller data set that may be causing some current business pain (e.g. customer or product data for a specific geography). Done this way, you can assure buy-in for a larger rollout.

Keep your eye on ROI: Since business units have different objectives, a common ROI should be established at the outset of a MDM strategy development, and the return on investment should be examined after each phase of rollout to maintain buy-in.

Don’t forget to update: Your master data management strategy must include regular, synchronized updates to ensure that your single source of data has the most accurate information.

What’s on the Horizon for MDM?

There are a number of trends shaping the future of master data management. Here are a few:

Multiple Domains
MDM products that manage multiple master data domains – customer, product, locations, finance, and employee—will increase. Today, most large companies maintain at least two MDM technology solutions because no single MDM product meets all their needs.

The Cloud
The need to secure and quickly integrate vital master data may make companies reluctant to put their master information in the cloud. Still, increasing integration of data with SaaS applications may increase the development of MDM solutions that are cloud-based.

Big Data
These days MDM must incorporate big data strategy. A protocol must be developed for how to handle the volume and complexity of data, be “social networking aware,” and have a way to tie unstructured data to master customer profiles.

Data Wrangling: The Next Frontier

As MDM strategy, and data itself,  becomes more sophisticated, incorporating data wrangling, or cleaning and unifying diverse data sets, will be imperative to incorporate into a successful MDM strategy.

Forward-looking businesses seeking to differentiate themselves on speed and efficiency are already integrating data wrangling into their master data management strategy.