The Data Steward problem- Role ambiguity and priority

I think we can agree, in an increasingly data dependant landscape, universities do recognise the importance of improving the quality, availability and use of their data. Less certain is that the solution is a robust and sustainable data governance framework.

There are many reasons for this, and some of those are the subject of a future post. Today though, I want to talk about the problem of onboarding and engaging one of the fundamental roles of when implementing data governance.

At the heart of these frameworks lies the role of the data steward—a critical yet often misunderstood position. While the concept of data stewardship is not new, the expectations placed on those who assume this role have evolved dramatically. And therein lies the challenge: data stewardship is a role, not a new job, and that distinction creates friction.

🧩 The Role vs. The Job Dilemma

One of the primary reasons data stewards struggle to embrace their responsibilities is the ambiguity surrounding the role itself. Most data stewards are not hired explicitly as “data stewards.” Instead, they are mostly subject matter experts who are voluntold into stewardship because they know the data best. This creates a tension between their existing job duties and these new expectations layered on top.

Unlike a formal job title with a clear job description, performance metrics, and dedicated time, the data steward role is often informal and lacks institutional support. It’s not uncommon for stewards to be asked to lead data quality improvement initiatives, define metadata standards, and resolve data issues—all while continuing to prioritise their actual job role.

Without a shift in mindset and structure, this can feel like an overwhelming burden. Which results in stewardship being one of those “end of the desk, end of the day” activities that never gets done.

🔧 Implementing a Data Governance Framework: The Reality Check

The implementation of a data governance framework is the catalyst for assigning stewardship responsibilities. These frameworks aim to bring order to chaos—standardising data definitions, improving data quality, and supporting data consumers. But they also introduce new layers of accountability.

Suddenly, data stewards are expected to:

• Participate in governance groups

• Document data lineage and business rules

• Serve as the expert and advocate for data related decisions

• Mediate disputes between departments over data definitions and quality needs.

This is often a far cry from their previous ad-hoc involvement with data. And without proper training, authority, or time allocation, many stewards find themselves stuck in a reactive mode—fielding endless questions, fixing data issues manually, and struggling to keep up,

📉 The Consequences of Role Ambiguity

When stewardship is treated as a side hustle rather than a strategic function, several problems emerge:

• Burnout: Stewards feel stretched thin, leading to disengagement or resistance to the new role.

• Inconsistency: Without clear processes, data decisions vary wildly across teams. The peril of steward fiefdoms!

• Missed Opportunities: Valuable insights are lost when stewards are too busy firefighting to focus on proactive improvements.

  
  

Moreover, the lack of formal recognition can make stewards feel undervalued. They’re doing critical work, but it’s invisible to leadership unless something goes wrong.

This is almost never a problem with the individual steward. They see the value in what they are being asked to do, but they don’t have the time. It is the classic case of “we have time to do everything twice, but not to do it right first time”

🚀 From Reactive to Proactive: The Stewardship Payoff

Here’s the twist: when data stewardship is embraced fully and supported properly, it actually frees up time for stewards to do their core job better.

Instead of answering the same ad-hoc queries about data definitions, lineage, or quality over and over, stewards can proactively guide and support data consumers with trusted, well documented data sources. By establishing clear standards and educating others, they reduce the noise and increase efficiency.

Imagine a world where:

• Data consumers know exactly where to find the right data

• Data quality issues are flagged and resolved systematically

• Metadata is maintained, accessible and trusted

• Previously siloed teams now speak the same data language

  
  

This is the promise of effective stewardship. It’s not about doing more—it’s about being smarter. First though you must get over the hump of making the case and getting started.

🎯 Conclusion: Stewardship is the catalyst for Data Governance

Yes, it’s difficult for data stewards to take on the responsibilities of the role, especially when it’s not framed as a formal job. But with the right support—clear expectations, training, and recognition—stewards can transform from reactive troubleshooters to trusted advocates of valued data.

And in doing so, they’ll find themselves spending less time answering repetitive questions and more time driving and supporting a institution wide data culture.

So, if you take only one thing from this post, it should be this: Stewardship isn’t a burden—it’s a catalyst for trusted, high quality data.