ADG 1: Making the case for Data Governance Summary

Alex Leigh

September 01 2025

4 min read

At the start of 2025, we ran the Agile Data Governance (ADG) webinar series.  In this collection of short articles, we’re going to look back at each one to summarise the most important takeaways. It’s been fun going back after a few months to see if there’s anything we missed or even forgotten!

ADG 1 - Making Introduction to Data Governance

Overview:

Define data governance and its importance in the context of cost savings.

Key Points:

• What is data governance?

• The positive impact of effective data governance.

What good looks like: Enablers for data governance in Higher Education (HE)

Data governance (DG) in higher education isn’t just about policies and platforms—it’s about people, behaviours, and building trust in data across the institution. Over the course of the ConnectED webinar series, we’ve explored what “good” really looks like when it comes to embedding DG capability in UK HE.

Here’s a practical summary of the foundational elements to get your DG capability started.

1. Start by building assurance not a rigid framework

In the first year of DG, the goal isn’t to transform everything overnight, it’s to build assurance. That means setting up the operating model, identifying priority data domains (eg. admissions or enrolment) and onboarding data owners and stewards. You won’t see huge returns straight away—and that’s fine. The first year is about laying solid foundations, even if the benefits take time to show.

2. Make It visible

One of the simplest but most powerful elements is visibility. A central portal or “shop window” for data governance—where staff can find tools, documents, contacts, and accountability frameworks—signals that DG is a serious institutional commitment. It’s not just a back-office function; it’s a resource for everyone.

This hub should connect with existing processes and systems, making it easy for users to interact with DG in their day-to-day work. It’s also a great way to drive traffic, build awareness, and promote collaboration.

3. Embed DG into Projects Early

DG works best when it’s woven into the project lifecycle—not bolted on at the end. Whether it’s a new student record system or a data-heavy transformation initiative, embedding DG principles from the start ensures that data is treated as a valued asset. This also helps raise the profile of DG across the institution and aligns it with broader change programmes.

4. Deploy tools (but not ones you have to pay for)

Only these two tools are needed at the start:

• Data Quality Issues Log: Enables staff to report, track, and resolve data issues. It supports accountability and helps surface problems that might otherwise stay hidden.

• Data Glossary: Standardises definitions and reduces confusion. Ask three people what a “student” is, and you’ll likely get three different answers. A shared glossary helps everyone speak the same language and improves the utility of existing data. It should reduce unreconciled data sources which are such a problem in most institutions we work with.

These tools aren’t just operational—they’re cultural. They help shift the conversation from “we need more data” to “we need to better understand and use the data we already have.”

5. Build Relationships, not just frameworks

DG is as much about people as it is about processes. Success depends on building relationships across departments, fostering collaboration, and creating a community around data. This isn’t about hierarchy—it’s about connection.

When people know who to ask, feel confident in the answers they get, and trust the systems they use, DG becomes part of the institutional fabric. It’s no longer a separate initiative—it’s how things get done.

6. Trust in data is for everyone not just senior leadership

Trust in data shouldn’t be limited to senior leaders. It needs to exist across the entire chain—from those inputting data at the coalface to those making strategic decisions. Often, the biggest improvements are felt by those closest to the data issues. Their experience is a powerful indicator of progress—and a solid foundation for broader cultural change.

7. Measure what you can, showcase what you can’t

Not everything valuable can be measured. But that doesn’t mean it’s not important. Some of the best indicators of DG success are felt:

• Are more people using and trusting the same data?

• Are there less ad-hoc requests for narrow data sets?

• Are staff spending less time “wrangling” data?

These “soft” outcomes—collaboration, trust, shared understanding—are harder to quantify but essential to long-term success.

8. Invest in skills

DG doesn’t work without people who understand data. Organic learning happens when staff sit next to data-savvy colleagues, but real transformation comes from intentional investment in data literacy. Institutions like Birmingham City (BCU ) have shown that equipping staff with the right skills is key to unlocking the value of data governance. Worth checking out some of their public webinars to show what they’ve done.

Final thought: Data Governance is a strategic enabler

Data governance isn’t just a technical fix—it’s a strategic enabler. It builds trust, drives collaboration, and empowers institutions to make better decisions. This is true if you’re just starting out or embedding DG into mature processes.

We hope that first of the ADG series has shown that good DG is visible, practical, and people first, middle and last. It’s not about perfection—it’s about progress. And it starts with the foundational behaviours, processes, and the visible changes which make data governance both a positive initiative, and valued as a sustainable institutional capability.

Coming next: Data Vision- what is that, and do I need one?