How Adaptable Is Your Customer Master Data?

Whether it is due to a market shift, merger, acquisition, restructuring, departmental change, or infrastructure transition, in the corporate world we know that change is a regular occurrence.

Although companies go to great lengths to build data warehouse models to retain corporate data, it's the business operations, business intelligence teams, and strategic decisions that dictate what data is actually most important and useful. Because of this, the data that is stored often becomes optimized to best serve the operational and BI needs. However, when a large organizational or operational change occurs in a company, it's not unusual for the value, context, or even the need for that data to quickly diminish in light of new priorities, new applications, change of ownership, or simply a loss of ability to maintain what may now be considered legacy data.

Changes in business practices and data requirements are a constant challenge for IT. This is particularly true with operational processes and data, but can also be the case for master data where internal system transitions or mergers and acquisitions occur.

The good news is that customer master data can be much more adaptable, transferable, and able to retain its context and value if good MDM practices have existed with it. The ability to quickly integrate the customer master data into new models and environments can equate to not only a large cost savings compared to the cost of a much larger effort usually needed to align and integrate data of poor quality and integrity, but it also enables the new environment or acquiring company to minimize disruption and maintain business continuity.

Let's talk about some good MDM practices to keep in mind that can help the customer master data and the MDM model best adapt to and survive organizational change. We'll look at this topic both from a data quality perspective in terms of how quality factors such as data completeness, consistency, and integrity can inhibit or enable the transformational ability of the master data and its context, and from a change management perspective in terms of how the data governance council and the data steward process can greatly assist with managing change.