Maybe governance was never meant to work here
Today’s organizations don’t fail at data governance because they ignore it. Gone are the days when information governance could be dismissed as an inconsequential concern. Years of regulatory pressure and AI-driven data expansion have now crystallized compliance as a baseline requirement. So why do even mature organizations still struggle with unreliable results? Perhaps it is because they confuse the existence of governance structures with the actual practice of governance.
Surprisingly, awareness is not the issue; organizations usually understand the importance of governance and have policies, committees, and controls in place. The more difficult challenge is execution. The reality is a messier picture when data ownership rarely sits neatly with one team. Say a product manager needs data to launch a feature, but engineering owns the pipeline and legal owns regulatory interpretation, while a third-party vendor controls the system where the data ultimately lives. Everyone has a role, but no one has the complete picture.
Let’s back up and start at the beginning. Most governance frameworks are built with a straightforward foundation: if ownership is assigned and responsibilities are defined, then accountability will follow. In reality, however, that relationship very quickly fractures because responsibility and authority move in different directions. A privacy team, for example, may be accountable for how data is handled without having meaningful control over the collection (engineering), the usage (business units), or the storage (vendors). As a result, teams interpret policies differently, so controls are applied inconsistently. It comes as no surprise that when business priorities take precedence, people treat governance as an afterthought.
This challenge intensifies as our data environments accumulate more complex technology. Applications, vendors, cloud platforms, and workflows evolve much faster than governance processes can adapt. Where does the most sensitive customer data exist? Who uses it? What is the purpose? A company may believe their governance posture is acceptably strong until an audit or breach investigation crudely exposes the exact opposite. In short, governance requires coordination. Modern organizations, however, operate through fragmentation.
Incentives are an additional problem; teams are evaluated on visible outcomes, like revenue growth and business results. Because the value is much harder to see, regular governance maintenance rarely receives the same attention. Governance inherently introduces friction (controls and reviews take time), so teams naturally perceive it as another obligatory box to check before launch. Over time, governance ends up becoming something people work around instead of an integral part of how work gets done.
Another issue is measurement. Governance teams commonly struggle to explain their value in terms the broader business recognizes. Technical measures (i.e. quality and lineage) matter, but they don’t always connect cleanly to consequences like financial impact or operational efficiency. Consequently, governance is largely treated as a cost center instead of a value driver, thus becoming vulnerable to de-prioritization and budget cuts. After all, governance is invisible when it works, and visible only when it fails.
The future of governance won’t be determined by how many policies or committees are created. It will be by how governance is built into the decisions people already make.