Applying change to a master data process is similar to applying changes to any other process but with nuances unique to the nature of master data. The fundamental principles of process change communication, stakeholder buy-in, planning, and continuous improvement apply just as strongly. However, master data processes intersect with multiple systems, departments, and business activities, adding layers of complexity.

I like to envision master data as a three-legged chair, where each leg represents a critical pillar: governance, ownership, and measurement. Together, these three elements provide the stability required to support effective data management and enable successful process changes.

Governance ensures that the rules, standards, and policies around data are well-defined and consistently applied. It acts as the framework for maintaining data quality, security, and compliance, laying the foundation for trust in the data. Without governance, the chair becomes unstable, leading to inconsistencies, confusion, and potential errors in decision-making.

Ownership is about clearly assigning responsibility and accountability for data. This includes defining who maintains, updates, and uses the data, as well as fostering a sense of stewardship within the organization. Without ownership, the chair tips as there’s no one accountable to ensure that governance policies are upheld or that the data remains accurate and timely.

Measurement provides the ability to evaluate and monitor the health and performance of master data. It involves tracking key metrics, assessing data quality, and identifying areas for improvement. Without measurement, the chair collapses because there’s no way to validate the effectiveness of governance and ownership or to guide continuous improvement.

If any one of these legs is missing or weak, the chair will tip over, undermining your master data initiative and potentially causing your process change journey to fail. Achieving balance among these three pillars is essential for creating a sustainable and successful approach to master data management.