Data quality leaders must rethink their role. They are neither compliance officers nor gatekeepers of platonic data ideals. They are advocates. Using their language and metrics, they must campaign for change, build coalitions, and show stakeholders why quality matters.

This is not a theoretical shift; it is a practical one. In this new approach, the data quality assessment becomes a tool of persuasion and influence. It is no longer about documenting problems for posterity. It is about demonstrating how poor data hurts specific business outcomes and presenting a clear, actionable path to improvement. The number of issues identified does not define success, but rather the number resolved.

To support this approach, a new methodology has emerged—one that is small in scope, fast in execution, and laser-focused on stakeholder value. It doesn’t begin with a taxonomy—it begins with a problem.