Successful Data Governance: Not All Doing is Equal

August 2025, Scott Garner, Senior Consultant

Is your data governance successful?

As a data professional and consultant, I’m thrilled to see that more organizations are achieving success with their data governance efforts. They’re at a point where data governance is driven by the business, and good data hygiene is part of the daily routine. It’s so engrained in the culture that they don’t really talk about the “data governance program” anymore. Data activities are embedded into day-to-day processes, just like any other business as usual activity.

But there are other organizations with data governance programs that simply aren’t working. They’re still on the journey, but things have stalled. The excitement of “what can happen” has been replaced by the stark reality of “what isn’t happening”. Data governance at these organizations is stuck at an impasse.

Why is it that some data governance programs thrive, while others stall? Why do some organizations have data governance fully embedded into daily operations while others are still struggling to get business adoption? If they’re all “doing data governance”, then why do only some organizations experience success? It’s because when it comes to doing data governance, not all doing is equal.

I’ll illustrate with a couple of examples – both based on real patterns I have seen across multiple organizations.

Case Study 1: Doing Data Governance on Paper

Company A launched a data governance initiative two years ago. They developed a PowerPoint presentation outlining the framework, structure, timelines, etc. They defined data governance roles and identified data owners and stewards across the company. They created a structure, including a steering committee for decision-making and an operations council for stewards to collaborate. They published and distributed a governance policy document within the first two months of the program. But they never took any concrete action to solve real business issues. Company A did data governance on paper.

Case Study 2: Doing Data Governance at the Point of Impact

Company B did everything the same as Company A. They had a PowerPoint presentation showing the framework, structure, timelines etc. They defined data governance roles and assigned data owners and stewards across the company. But while all of that was happening, they also took time to solve a real data problem. They identified a pain point, took action and solved something for the business. They had noticed inconsistencies in their monthly sales reports. Depending on which dashboard you looked at, last month’s revenue was either $8.2M or $8.6M. Sales and finance had different answers—and no one trusted the data.

To address the inconsistencies and lack of trust in reporting, they formed a small work group of data stewards from sales operations and finance and traced the issue to a logic difference in how discounts get applied across systems. They agreed on a single definition of “net revenue,” documented it in the glossary, and updated all downstream reports to align with the new standard. Sales VP’s across the company shouted praises to the rooftops because the dashboards had consistent numbers. No more arguing. No more delays waiting for people to defend their number. Just consistent, reliable information. Company B did data governance on paper AND where business action takes place, at the point of impact.

Are both of these companies doing data governance? Technically, yes. But to be successful, data governance must move from paper to action.

For the record I am a firm believer in using a data governance framework, and I am a strong proponent of having a clearly documented data governance structure and workflows. Many of my consulting projects involve helping clients build effective data governance structures, but as I tell my clients, if you’re not also doing data governance where business action takes place, your program won’t thrive.

Why Do Some Programs Not Move Beyond the Paper?

There are several factors that can potentially cause a data governance program to stall, and those factors can happen at the organizational level, program level or individual level.

1. Organizational Readiness & Cultural Acceptance

Becoming a data-driven organization often requires a culture shift, and that takes time. Pushing data governance too fast can cause people to get overwhelmed and confused, and that can stop a program in its tracks.

I experienced this type of stall personally at a former employer. We had developed the data governance structure on paper (roles, decision rights, operating model, etc.), and it was time to make it operational. We’d put a lot of thought into the structure, so we felt confident that we could have things up and running within a few weeks. We were wrong. Why? Because the organization simply wasn’t ready to operationalize what had been designed on paper. Everyone agreed with the idea of having data owners, but nobody wanted to be a data owner. Everyone agreed with the idea of assigning decision rights to specific people, but nobody could agree on which function should have certain decision rights. Our program stalled because the organization simply wasn’t ready to absorb everything at the pace we were driving.

To compensate, we adjusted our change management strategy. We developed new educational materials to better explain the data owner role and shared specific use cases for how the role helps to eliminate many of the data challenges that were negatively impacting the various departments. We scheduled sessions with potential data owners to review the types of decisions that would be required, connecting the dots back to their pain points to help them better understand how those decisions are critical for business success. And ultimately, we got unstuck. Changing a culture isn’t easy, but it’s critical for successful data governance.

 2. Misaligned Program Success Measures

Measuring success is essential for a data governance program, but it’s important to select success measures that are focused on business value. If success is measured only based on “paper activities”, then the program can stall because the business simply isn’t feeling the value. And remember, demonstrating business value is how you get the business to own and drive data governance.

When selecting success measures for your program, avoid measuring activities that are focused solely on the operational aspects of the data governance program (paper activities). These are valid things to pay attention to, but they shouldn’t be considered success measures since they have no tangible value for the business. Examples include:

  • 85% attendance at steering committee meetings
  • Fill 90% of data stewardship roles
  • Increase the number of data policies by 5%

Moreover, make sure to extend your success measures beyond the data activities themselves. To get the business to own and drive data governance, success should be measured against things they care about.

Data-Focused KPIs

Business-Value KPIs

Improve validity of email addresses by 20%

Improve click-through rate of marketing campaigns by 5% by improving validity of email addresses

Increase completeness of mailing address information by 30%

Reduce the number of undelivered invoices by 10% by increasing the completeness of mailing address information

Reduce duplicate contact records by 25%

Increase conversion rates from marketing qualified leads by 8% by reducing duplicate contact records

The key to demonstrating business value is connecting the dots between the data activities and the business objectives. In other words, your measures should show a direct link between your success and the success of the organization.

3. Individual Fear

One of the most common factors I encounter is more personal in nature: fear of engaging with business colleagues in other departments, particularly when technical people are driving data governance. For some, simply engaging with businesspeople can be intimidating, much less initiating a project that puts you and your value proposition directly in the spotlight. The easier path is to continue focusing on writing data governance policies, which in turn causes the program to stall.

This goes back to the age old, unspoken divide between the business and IT. Of course this isn’t true in every organization, but in my experience there’s an invisible aisle between technical and business resources in most organizations. And for people on the technical side, it’s sometimes just a whole lot easier to stay on the “safe” side of the aisle. But here’s something you need to know: Businesspeople want to work with anyone who can help them achieve their objectives. Once they see that data governance activities lead to tangible business results, the perceived aisle will disappear. Taking that first step can be scary, but it’s the only way to demonstrate business value. And remember, data governance should eventually be driven by businesspeople, not by IT.

How to Move Beyond Paper and to the Point of Impact

If your data governance program is stuck, and you’re looking to get things moving, I’d suggest focusing on the following four steps:

1. Align with Business Value

To provide tangible business value you must align to the things that the business cares about.

  • Prioritize use cases that have high impact for the business
  • Engage business stakeholders through data owners and data stewards to understand the critical pain points and/or challenges

2. Start Small

The goal is to get quick wins that generate momentum, excitement and enthusiasm, so make sure to start small and deliver value quickly. This is not the time to tackle a multi-year issue. These should be 1 to 2 month efforts that solve real-life problems that people will notice when resolved or improved.

3. Solve Across Functions

One of the most impactful ways to demonstrate the business value of data governance is by solving a business issue that spans across functions. In the example above, Company B solved a data challenge across Sales and Finance. Most day-to-day operational processes impact more than one function, and the same is true for data. To maximize the value for the business, focus on issues that benefit several functions.

4..Make it Visible

To generate momentum, excitement, and enthusiasm, your work has to not only be tangible, but also visible to the right people. Once you get alignment on the issue, tell people about it. Let people know what you’re doing, who is involved, why you’re doing it, expected outcomes etc. The win itself is valuable, but transformation happens when people start talking about the win.

  • Create clear, concise narratives for leaders and/or sponsors so they can effectively recognize and articulate the value and benefits
  • Leverage company meetings before, during and after the resolution of a data problem to show the business impact
  • Officially recognize individuals for doing data governance successfully

More and more organizations are achieving success with data governance, and it’s because they’re doing data governance in actionable, impactful ways. If you’re also “doing” data governance but aren’t seeing the results you hoped for, it might be time to move from paper to the point of impact.

Remember, not all doing is equal.

What’s your first high-impact project going to be?