Sue Geuens explains why a data governance strategy fails when leaders focus on policies and tools before people, trust, and business context.
During a recent conversation on The Executive Outlook, Sue Geuens shared a truth many data leaders understand but rarely say openly. A data governance strategy can be beautifully documented, formally approved and still fail inside the business.
Sue has spent more than thirty years working across data governance, data quality, metadata and master data management. She has spoken and led workshops across Australia, Brazil, Japan, South Africa, and many other parts of the world. Across industries and cultures, she has seen the same pattern repeat itself. Organizations invest in frameworks, policies, dashboards and data governance tools, but the results do not change because the people expected to follow them never truly understand why they matter.
Sue is the Director of Data Governance and Master Data Management at Elsevier, one of the world’s leading information and analytics companies. Her perspective on data governance strategy is not theoretical. It comes from years of working inside real organizations where trust in data directly affects decisions, operations and leadership confidence.
Her conclusion is simple, practical and uncomfortable.
The reason data governance fails is rarely the framework, the budget, or the technology. It is usually the people.
Sue did not arrive at this belief through a textbook. She arrived there through a real moment in a workshop.
She was working with a financial services organization that had a clear policy about clean workspaces and locked screens. The policy had a valid purpose. The organization handled sensitive information and the risks were real. During the workshop, someone mentioned that a colleague had been challenged for not following the policy.
The colleague’s response stayed with Sue.
She said she had been too busy to read it. And when she finally read it, she did not care.
That moment revealed something every executive should pay attention to. A policy does not create belief. A dashboard does not create ownership. A document does not automatically change behavior.
A data governance strategy that lives only in a document has already started failing.
Sue also shared an important lesson about how governance communication can work better.
She once saw an organization turn a long policy into a simple one page infographic. That infographic did what the policy document could not do. It translated governance language into action. It made the expectation clear, visible and easier for people to follow in daily work.
That example matters because many organizations assume that writing a policy is the same as creating change. It is not.
People do not follow governance because a document exists. They follow it when they understand what it means, why it matters and how it connects to their role.
For executives, this is a critical shift. A strong data governance framework is not only about defining rules. It is about making those rules usable for the people who work with data every day.
Sue does not define data governance in the usual technical way. She does not reduce it to policies, procedures, controls, or ownership models.
For her, data governance strategy is the underlying enabler that makes data trusted enough for business decisions to be made with confidence.
That is the real outcome.
Not more documentation. Not more meetings. Not more governance language. The real goal is trust.
Sue explains this through a simple Monday morning scenario. In one version, a manager arrives at work and opens a set of reports that do not look right. They spend the entire day chasing numbers, checking with different teams, asking which version is correct and still sending the report forward with hesitation.
In the better version, the same manager opens the reports, trusts the numbers, and sends them forward within thirty minutes.
The difference between those two Mondays is not just a better data governance framework. It is a culture where people understand their role in protecting the quality and reliability of data.
That is where data governance becomes a business capability, not an administrative exercise.
One of Sue’s strongest examples is also one of the simplest. It involves a dropdown list.
In many organizations, forms include long dropdown fields. When people are busy, they often select the first option instead of scrolling through the list to find the correct one. The data looks complete, but it is wrong. Because the field is filled, many systems assume the data is valid.
Sue shared the example of a hospital that suddenly appeared to have a major rise in broken leg cases. Leadership began considering whether the orthopaedic department needed more capacity. But when the data was reviewed, the real issue was not patient demand. A developer had placed broken leg at the top of a long triage dropdown list and staff had been selecting it by default.
The hospital did not need a bigger orthopaedic department. It needed better data behavior and a better designed form.
This is where data governance best practices often fall short. They may define what good data should look like, but they do not always account for how people behave under pressure.
No data governance solution can work properly if it ignores the human decisions behind data creation.
Sue also brought the same practical thinking to master data management.
In simple terms, she explained master data management as the structure that helps businesses create one trusted version of important data. That could be customer data, product data, supplier data, or any other core information the organization depends on.
But Sue was clear that MDM often fails for one reason. Organizations do not ask why before they begin.
Many companies hear about master data management and treat it like a new tool to buy. They want the platform, the system, or the new capability, but they do not stop long enough to define the business outcome. Sue’s question is always simple. Why do you need it? What value should it create? What problem should it solve?
Without that clarity, even the best data governance tools and MDM platforms can become expensive technology with unclear impact.
She shared a powerful example of an organization where leaders received three different reports with three different bottom lines. Instead of knowing which number was correct, someone added the three numbers together, divided them by three and sent the average forward. The issue was not just reporting confusion. The organization was responsible for providing economic metrics to a government body, which made the risk far more serious.
In another example, Sue described a telecom company that sent her seven birthday messages because the same customer existed across different systems. From the company’s side, it may have looked like a small data issue. From the customer’s side, it showed that the business did not really know who she was.
That is why master data management matters. It is not about having one more system. It is about creating trusted, consistent and usable business data so leaders can make decisions and customers can receive a better experience.
When Sue is asked about the biggest data challenge she has seen across countries, industries and organizations, her answer is always the same.
People.
Not technology. Not funding. Not complexity. People.
Data does not act on its own. It sits in databases, documents, applications and platforms. People create it. People enter it. People consume it. People interpret it. People decide whether to care about it or not.
That is why a data governance strategy focused only on systems will never be enough.
The organizations that make governance work do something different. They make governance relevant to the people who touch data every day. They explain the business impact of poor data in a way people can understand. They connect data quality to real decisions, real customers, real risks and real outcomes.
Sue learned this lesson deeply when she spent a week working as a call centre agent. She did not do it to audit people from the outside. She did it to understand their world from the inside. She wanted to feel the pressure, see the systems, hear the customer conversations and understand why data issues were happening at the source.
That experience changed how she approached data governance solutions. It reminded her that poor data is often not created by careless people. It is created by people working inside difficult processes, unclear system and unrealistic expectations.
Sue also highlights a common mistake data professionals make. They walk into business conversations with spreadsheets, columns, definitions and technical language. They explain the data problem, but they fail to connect it to the person sitting across the table.
Over time, Sue learned that successful governance begins with empathy.
Before asking people to care about data, leaders must understand what those people are trying to achieve. What pressure are they under? What decision are they responsible for? What problem keeps repeating in their day?
Only then can a data governance strategy become meaningful.
Sue believes data leaders must stop being technical in public before they have earned attention. They must first tell a story that makes the problem real. Once people understand the impact, they are more willing to listen to the data behind it.
That is an important lesson for every CDO, CIO and executive building a data governance framework in 2026. Governance is not only about control. It is about communication, trust and shared responsibility.
Across the full conversation, one thing becomes clear. Sue is not offering another generic data governance strategy template. She is offering a perspective earned through decades of seeing governance succeed and fail in real organizations.
Her message is especially relevant for companies that have invested in data governance tools, data governance best practices, data governance solutions and master data management platforms but still struggle to create trust in business data.
The policy is not the full answer. The framework is not the full answer. The tool is not the full answer.
The real answer begins with people.
When governance becomes something, people understand, believe in and feel connected to, it stops being a compliance exercise. It becomes the trusted foundation behind better decisions, stronger operations and more confident leadership.
That is the kind of data governance strategy modern organizations need now.
Want to hear more conversations with leaders shaping data governance, trusted decision making and enterprise transformation? Explore more on The Executive Outlook.
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