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Most organisations know they need data governance. Far fewer have it working in a way that genuinely helps the business.
Ask a team what their data governance looks like, and you’ll often hear about a policy document somewhere on the intranet, a committee that meets quarterly, and a vague plan to “get the data in order.” What you rarely hear about is how any of it connects to real decisions, real outcomes, or real change.
We see this regularly with clients. And it matters, because without good governance, even the best analytics investments can struggle to deliver.
It’s a people problem more than a technology one
IBM’s 2024 Cost of a Data Breach report put the average cost of a breach at $4.88 million. Gartner research points to poor data quality costing organisations significant sums every year. The stakes are real.
But here’s the thing: 93% of data leaders say their biggest governance challenges are people and process issues, not technology ones. You can implement the most sophisticated data catalogue on the market. If nobody agrees on what “active customer” means across sales, finance, and marketing, you still have a problem.
Good governance starts with getting the right people in the same room and agreeing on definitions, ownership, and accountability. That’s less glamorous than buying a tool, but it’s where the real work happens.
Clear ownership makes everything else easier
One of the clearest signs of mature data governance is that every important data asset has an owner. Not a team. A person.
Data ownership means someone is responsible for accuracy, access, and quality. When a report shows conflicting numbers, there’s someone to call. When a new regulation requires specific data controls, there’s someone accountable.
Without ownership, governance becomes everyone’s problem and therefore nobody’s. We’ve helped clients establish data stewardship models that work in practice, starting small with their most critical datasets and building from there rather than trying to govern everything at once.
Quality over quantity
A common mistake is trying to govern too much too soon. Organisations launch ambitious governance programmes covering every data domain, only to watch them collapse under their own weight six months later.
The better approach is to start with the data that matters most to the business. What data drives key decisions? What data feeds your most important reports? What data has caused the most pain or confusion?
Fix that first. Establish quality checks, clear definitions, and reliable processes around a small set of high-value datasets. When that works, expand. Governance built this way tends to stick because people can see the difference it makes.
Connect governance to business outcomes
If your governance programme is built around compliance and risk alone, it will always feel like a burden rather than a benefit. The organisations that do it well tie governance directly to things the business cares about: faster reporting, more reliable forecasts, better customer insights, lower risk.
That connection matters for getting leadership buy-in too. Governance requires investment, and that investment is a lot easier to justify when you can point to the cost of bad data or the value of trusted data. The goal isn’t governance for its own sake. It’s better decisions, faster.
Where to start
If your governance feels more theoretical than practical, here’s a simple place to begin. Pick one business question that depends on data and trace that data from source to report. Where does it come from? Who touches it? Where might it break? What would “good” look like?
That exercise tends to reveal gaps quickly, and it gives you a clear, bounded problem to solve. From there, you can build outward.
In our experience, governance programmes that start with a real business problem, rather than a framework, get traction far more quickly.
If data quality or governance is something your team is wrestling with, we’d love to have a conversation. Sometimes an outside perspective is all it takes to see a clear path forward.
