A successful master data management (MDM) strategy begins with quality reference data

Copy updated on September 16, 2024
 

In today's data-driven world, an effective master data management solution is increasingly considered a foundational asset that can benefit a vast range of business processes.

And, when it comes to MDM implementation, taking a phased approach is crucial. Just as you wouldn't run a marathon without training, transforming your data architecture requires careful planning and execution. In short, an effective MDM solution is nothing without high-quality data sources. Below, we explore the importance of global entity reference data and the benefits it brings to large-scale data operations.
 

Taking a phased approach

Large-scale changes to data structures are not to be taken lightly, and require a robust assessment of the potential impact. The key is not only understanding where the data is currently being used, but also identifying the potential risks that must be mitigated.

Once these risks have been cataloged and addressed, it is essential to prioritize the business units that require the most immediate attention. This could be your sales or manufacturing function, or those areas subject to strict supplier audits. Each area will require a tailored approach and specific metrics to measure success. By implementing changes incrementally, you can afford your team the flexibility needed to efficiently address any unforeseen challenges, and establish a standardized blueprint for future rollouts.
 

The role of global entity reference data

Having up-to-date global entity reference data plays a crucial role in large-scale data operations. Indeed, a trusted record for matching, validating, enriching, and maintaining your first-party data is a valuable resource for various reasons. Chief among them is that, as your operations scale, access to a singular view of customer data enables your teams to reduce reliance on time-consuming manual checks. Not only can high-quality reference data make data governance more efficient, it can also help teams to unlock actionable, real-time customer insights that can enhance the client experience or unlock new opportunities.
 

Designing for simplicity and scalability

In our view, MDM strategies have the best chance of success when organizations create a simplified and nimble data design flexible enough to accommodate future changes. That's why simplicity in data design is paramount.

Data can be its most powerful when it has cross-functional utility. Therefore, it is essential that your data model is designed to be nimble and adaptable, minimizing the need for costly future transformations. Start with a simplified structure for uniquely managing organizations, locations, individuals and relationships. This will represent the “golden record” for customers, suppliers and partners in your MDM system or, in other words, a single source of truth that can yield enterprise-wide uses.

Your MDM system can generate unique IDs for the master data and maintain cross-references to unique IDs from your global entity reference data, as well as record IDs from systems across your enterprise. This allows for greater flexibility, which is critical to handle the potential impact of large-scale changes to your enterprise data models. This is especially true if your company plans to acquire new technology, assets, or other companies in the short-to-medium term. In our view, by prioritizing simplicity and scalability, you can future proof your data architecture and avoid unnecessary disruptions.
 

A robust MDM strategy depends on data quality

Implementing a successful master data management strategy, as part of your digital transformation efforts requires a phased approach, with careful consideration of potential risks, and a focus on automation and simplicity in data design. By having reliable global entity reference data at your disposal, your organization's large-scale MDM projects has every chance of setting off on the right course.