ADG 4: The Data Governance Operating Model

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 4 - The Data Governance Operating Model

Overview:

Exploring different models and frameworks for data governance.

Key Points:

• Centralised vs. decentralised models.

• Choosing the right model for efficiency and effectiveness.

Data Governance from strategy to action: A simple guide to building a Data Governance Operating Model (DGOM)

We often hear that “data is one of the most valuable assets in any organisation”- managing it so it is recognised as such is rather more difficult! The bridge between talking about data governance and implementing it is the Data Governance Operating Model (DGOM)

So let’s dive in, what is a DGOM, why does it matter, who is involved and how to get started.

What is a DGOM (and why should you care)?

If your data strategy is the “why,” then your operating model is the “how.” It’s the practical framework that helps you land that strategy and manage your operational data governance efforts. Think of it as the instruction manual for all your data governance activities.

Even if you don’t have a formal data strategy yet, you still need an operating model. It’s what allows you to:

• Define your domains and prioritise your coverage

• Build an accountability model for data owners and stewards*

• Agree your most critical data and hold it to a higher standard of care

• Introduce or extend a data quality framework focussed on that critical data.

• Collect issues and prioritise improvement activity

• Increase utility through business glossaries and new ways of communicating

• Help and support teams everywhere but mostly at the “data coal face”

• Build something that feels valuable, real and sustainable.

  
  

Without it, your data governance efforts are likely to stall or stay stuck in a document!

*these are just some of the roles. See below for more details

Who really matters in a DGOM.

Spoiler: it’s everyone! However a pragmatic operating model is built around clearly defined roles. Here are the three most important:

• Data Executive: Senior leaders who champion the DG activity. Think of them as your virtual “Chief Data Officer”. They set policy and – most importantly – prioritise the work.

• Data Owner: Accountable for specific data areas (or domains) (like student or finance data). They assure the data in their domain services as many use cases as possible. They choose their stewards and give them time and support to be successful in the role.

• Data Steward: The hands-on experts who know how the data works inside and outside systems and where the issues are. They’re often already doing  much of the work under the scope of DG—it just hasn’t been formalised.

These roles might go by different names in your university (like custodian or guardian), and that’s fine. What matters is that the responsibilities are clear, embedded and respected by all data consumers at all levels!

Who else?

Beyond the core trio, there are a few more people who help make the model work:

• Data Governance Team: Usually, one or two people who manage the framework, support the other roles, and keep everything connected.

• Data producers and consumers: The people who create and use data every day. They need to understand the data they in their purview and improve it when asked.

• IT and custodians: IT teams manage the systems where data lives, so they’re essential partners. Custodians (like your Data Protection Officer) help make sure governance aligns with legal and compliance needs.

How to get started?

For the DGOM to succeed, it needs to feel real—not just another project that fades away. Three simple rules are a test for this:

• Giving it a visible presence (like a SharePoint site or a named team) which includes useful information (such as who to contact and where to find data) to make it stick.

• Backing it with senior sponsorship. That often is those leaders acting as advocates who repeat the messages “the right way will be the easy way” and “just because it worked yesterday doesn’t mean it’ll work tomorrow”.

• Making it more professional and polished than anything else related to data. There’s a bit of “fake it before you make it” with all things DG, so it must pass the sniff test! Does it feel real, and do I want to engage with it?

  
  

Also, don’t reinvent the wheel. If you already have committees or working groups that deal with data, build on them. The goal is to connect the dots, not create more silos.

So what’s in the model?

We introduced a high-level view of the operating model, which includes 12 key components—from strategy and design to measurement and improvement. These are the building blocks of your governance framework.

Here’s a summary for design and operation:

This is your handbook. It’s the foundation for you to build, run, and grow your data governance capability.

One size fits none!

Before starting on your DGOM, you need to answer these two questions:

1.     What kind of approach would work best in your organisation?

2.     What already exists that you can build on?

Chances are that some governance activities are already happening informally. Maybe someone’s already checking data quality, or there’s a team that owns a key dataset. Use these as your starting points. Don’t duplicate or re-invent.

Final Thought: A DGOM isn’t just a document—it’s a way of working. With the right people, support, and structure, it becomes the foundation for better, more trusted data across your organisation.