Data Governance Isn’t a Sprint, But It Doesn’t Have to Be a Marathon Either.

Data governance often gets a bad rap. It’s seen as time-consuming, complex, and disconnected from real business outcomes. But it doesn't need to be that way.

Whether you're just getting started or trying to bring order to the chaos, this blog is for you.

Here, I share nine practical ways to make data governance work in the real world. No jargon. No red tape.

Just clear advice, grounded in experience and supported by a few running metaphors to keep things moving. Read on to find out more. 👇

Over the years, I’ve seen Data Governance framed in all sorts of ways. You’ve probably heard the metaphors too:

• It’s like flossing your teeth: everyone knows they should do it, but it’s easy to ignore until something goes wrong.
• It’s like cleaning out the garage: no one’s excited to start, but everyone enjoys the results.
• It’s like going to the gym: consistency beats intensity, and showing up is half the battle.

But being a runner myself, one of my favourites is this:

Data governance is a lot like going for a run. Buying the flash gear doesn’t guarantee results, and skipping the warm-up almost always ends in pain. You start with smaller distances, build your stamina, and gradually work your way toward the big events. With the right plan, a bit of consistency, and a clear sense of purpose, the benefits start to show.

The same goes for data governance.

In my experience, governance doesn’t fail because it’s a flawed idea. It fails because it’s misunderstood. Often, it’s introduced as a technical project or a compliance requirement. Other times, it’s treated like a one-off effort instead of something that supports the wider organisation.

But at its core, governance is about people, process, and purpose. It’s about making sure your data is accurate, consistent, and ready to support the decisions your organisation needs to make. Done well, it empowers your teams rather than slowing them down.

Here’s what I’ve learned about getting it right.

1. Tools Don’tDeliver Value on Their Own

‍Buying fancy running shoes won’t make you a runner

You can invest in the best platforms, data catalogs, or quality monitoring tools available. But without clearly defined roles, processes, and buy-in, they won’t get used properly. Tools support governance, but they don’t deliver value by themselves.

A data catalog with no clear ownership or accountability ends up being underused and undervalued.

2. One Size Doesn’t Fit All

Trail runs, road runs, and track runs all require different shoes

Every organisation has different governance needs. What works for one team might not work for another. The approach needs to reflect your priorities, whether that’s compliance, cleaning up legacy data, or enabling more advanced analytics.

Finance teams may need detailed access control and audit trails, while marketing might focus on standardising customer definitions across platforms.

3. Start Small and Build

You can’t go from the couch to an ultra-marathon overnight

A lot of governance programmes struggle because they try to cover everything from day one. That approach is hard to implement, difficult to measure, and nearly impossible to sustain. Starting with a focused area, building credibility, and scaling from there is a more effective path.

Pick a specific challenge like cleaning up customer records or improving data lineage in an area of your business and use it as your starting point.

4. Make It Routine

Consistency matters more than speed

Governance works best when it becomes part of day-to-day operations. That means clear ownership, embedded workflows, and regular reviews. It shouldn’t feel like a side project that gets revisited once a quarter.

To make this shift successful, change management plays an important role. People need to understand what is changing, why it matters, and how it supports their work. Clear communication and support during the transition are essential.

When teams see data quality as a shared responsibility, governance becomes a natural part of how they work.

5. Have a Plan and Stick to It

Training with a structured plan gets better results

Without a clear plan, governance efforts can quickly lose focus. Start by defining what success looks like for your organisation. This could be improving trust in reporting, increasing confidence in data for decision-making, or reducing time spent fixing data issues.

Once you understand where you are today and what you are trying to improve, you can begin to identify ways to measure progress. These might turn into KPIs over time, but the most important thing early on is to align your efforts to real business outcomes.

A clear sense of direction keeps teams focused and helps you track whether your governance approach is delivering value.

6. It Doesn’t Need to Break the Budget

Improving your form often makes a bigger difference than buying better shoes

Governance often gets lumped into the "expensive and complicated" category, especially when it sits alongside big-ticket items like cloud migrations, AI initiatives, or data platform upgrades. But compared to those investments, governance is low-cost and high-impact.

Think of it as an insurance policy for your data strategy. It protects the tools you’ve already paid for and ensures they deliver the outcomes you expect.

Because without governance, even the flashiest AI model is just making educated guesses (and sometimes, not very good ones!)

7. Track Progress to Improve It

If you don’t track your runs, you won’t know if you’re improving

Governance needs to be measurable. If no one is tracking progress, it’s hard to know if it’s working. I recommend setting up simple dashboards or regular reviews to track key governance metrics like data quality, usage, and issue resolution.

You wouldn’t run without checking your pace. The same goes for your data.

8. Shared Definitions Reduce Risk

A marathon is always 42.2km, no matter where you run it

One of the most powerful things you can do is agree on standard definitions. When different departments use different meanings for the same term, it leads to confusion, misalignment, and rework.

Aligning on terms like “active customer” or “net revenue” can have a massive impact on reporting, strategy, and communication.

9. Build on What You’re Already Doing

Everyone runs, even if they don’t call themselves runners

In most organisations, governance is already happening. People are fixing data issues, managing access, and questioning reports. These are all governance activities, but they tend to be informal and inconsistent.

The people doing this work are already in your organisation. They might be CRM owners, finance leads, analysts, or operations managers. Rather than hiring a new team, the focus should be on recognising these existing efforts and building support around them.

Creating structure, shared language, and space for collaboration turns reactive work into repeatable practice. And when things get more complex, such as meeting compliance standards or scaling governance across teams, it helps to bring in external support.

Governance does not need to start from scratch. You already have the people and the momentum. Now it is about making it intentional.

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And here's the bottom line...

Data governance doesn’t have to be big or slow or complex. It just needs to be intentional. Start with what’s already happening. Focus on solving real problems. And build a culture where people know how their data responsibilities connect to the bigger picture.

It’s not about running a marathon. It’s about running smarter, together.