Why do we Need a Simple Data Governance Framework?

Data Governance can be a complex field to work in and on a regular basis, it seems like there is always some sort of newbarrier to overcome, whether you’re a newcomer to the field or a veteran. Yet one thing I bet most Data Governance practitioners will have in common is the understanding that when it comes to being successful with your framework, simplicity is the way forward. And I can vouch for this too. 

In this blog, I want to break down why exactly simple is simply the best (Tina Turner pun intended!).

The Purpose of Data Governance

At its core, Data Governance is about enabling people in your organisation to use data more effectively. It helps them understand the data they have, assess its quality, and take the necessary actions to improve that quality if needed. The aim is to make sure data is working for the business - not the other way around.

But if we design a framework that is overly complicated, we run the risk of turning people off from using it altogether. Instead of engaging with Data Governance, they may see it as a burden that gets in the way of their daily work. And that’s the exact opposite of what we’re trying to achieve.

Complexity Creates Barriers

Let’s face it,no one wants to deal with unnecessary complexity, especially when they’re already juggling a hundred other tasks. If your Data Governance framework feels like a set of obstacles that makes accessing or using data more difficult, people will naturally resist it. Even if you’re telling them that it will make their work easier in the future, it’s hard to convince them if the framework feels like just another layer of complication.

We’ve all been there, haven’t we? We’ve encountered processes that are so complicated they just seem to make life harder rather than easier. When that happens, people tend to disengage, and they’ll stick to what they know instead of adopting new practices - even if those new practices would benefit them in the long run.

Think About it in Terms of Watching TV

To explain this further, I like to use an analogy that most people can relate to - watching television.

Years ago, when I was a child, things were simple. You had terrestrial TV with a few channels and after dinner, my family would gather around, check the Radio Times, and decide what to watch from a limited selection. We all watched the same show together and it was easy.

Fast forward to today, and watching TV is anything but simple! You’ve got cable, satellite, streaming services like Netflix, Amazon Prime, and Disney+, and you can watch on multiple devices. The choices are endless, and sometimes it feels overwhelming.

Earlier this year, I had a rare opportunity to watch something on my own, without my husband. I thought I’d pick out a nice costume drama, but it didn’t go as planned. I spent 45 minutes scrolling through multiple platforms and still couldn’t decide what to watch. In the end, it felt so complicated that I gave up, made a cup of tea, and read a book instead.

Now, imagine that same level of frustration amplified in a work environment. If you present someone with an overly complex Data Governance framework, they’ll feel just like I did when trying to pick something to watch. They’ll give up and move on to more urgent tasks because, even if the framework could help them in the future, they can’t see past the immediate complexity.

Simplicity Is Key

So what’s the solution? Keep your Data Governance framework simple. Start with a framework that’s easy to understand and easy to adopt. The goal is to make it clear, concise, and not intimidating. If people can grasp it quickly, they’re much more likely to engage with it and see its value.

Simplicity doesn’t mean you won’t be able to build on the framework later on. You absolutely can add more detail as your organisation becomes more comfortable with it. But the starting point should always be straightforward. By doing this, you make Data Governance feel like something that helps people do their jobs better, not something that gets in the way.

At the end of the day, the reason we implement Data Governance is to deliver real value to the business. It’s about making data a more valuable asset, making it easier to access, understand, and improve the quality of that data where needed. If the framework is too complicated, people won’t see it as a tool to help them - they’ll see it as a burden.

Final Thoughts

Simplicity is more powerful than complexity in a lot of ways, and this includes Data Governance. When frameworks are simple, people are more willing to adopt them, which leads to better engagement, better data management, and ultimately better business outcomes. Remember, the goal is to help the business, not to create more work.

So, if you’re designing a Data Governance framework, always keep simplicity in mind. Start small, keep it clear, and watch as your business begins to truly see the value of good Data Governance.

If you'd like support implementing an effective Data Governance framework in your organisation, book a call with me below.

Data Governance on a Shoestring Budget

There’s no denying it. The demand for Data Governance is growing fast. Whether it’s because of changing regulations, technology, or economic pressures, more organisations are finally realising they need to get serious about their data. But there’s a problem…

Budgets are tight. People want Data Governance, but they don’t always have the time, team, or money to implement it properly. So how do you move forward when the pressure is high but the resources are low? You take a minimal approach.

What is Minimal Data Governance?

So, first of all, let’s clear something up. “Minimal” doesn’t mean careless or incomplete. It’s not about doing the bare minimum to keep the regulator off your back or to tick a box in a report. Minimal Data Governance means being focused and deliberate about what you're doing and why you're doing it, so that even a small initiative delivers visible value.

You start with a narrow scope. You choose just one area or one goal to tackle. Maybe it’s improving the quality of customer data, or making financial reports more reliable, or helping the business meet compliance rules. Whatever it is, it should matter to your organisation right now. That one focused goal becomes your anchor. It helps you design a framework that works, even on a budget.

Does “Minimal” mean less time and effort?

Unfortunately not! Whether your scope is large or small, setting up Data Governance still takes time and attention. If you try to rush it or cut corners, you won’t get the results and that can hurt your reputation and your chances of getting support for future work.

But here’s the good news: if you do minimal Data Governance well, it becomes your foundation. Something you can build on over time and that proves the value of Data Governance to your stakeholders. You don’t need to do everything at once. You just need to do the first thing right.

You don’t have to do it alone

If you're wondering how to get started with a limited budget or team, remember: you don’t have to go it alone. That’s why I offer flexible coaching options that help you do Data Governance in a practical, structured way without wasting time or money.

The first option is Coaching, which gives you one call per month for six months. Each session lasts one hour and is recorded so you can refer back to it. You're welcome to bring along team members, and you can also use a session for stakeholder discussions, reviewing documents, or getting help implementing your framework. You’ll also receive my detailed Data Governance Checklist - a practical tool to help you keep track of what you’ve covered and what still needs attention.

The second, most popular, option is Coaching Plus. This gives you ten one-hour sessions to use at any time over a six-month period, offering greater flexibility if your needs vary from month to month. Like the standard coaching option, the sessions are recorded and team members can join in. You can use the sessions however you like, from strategic planning to stakeholder engagement. In addition to the Data Governance Checklist, this option includes a licence for my online Data Governance training course. There is also the option to add on access to my Data Governance-specific AI assistant, trained on my own 20+ years of experience and knowledge.

Both packages are designed to help you focus your efforts and adapt as your initiative evolves without overcommitting your time or your budget. Take Volkswagen Financial Services UK, for example. They chose the Coaching Plus package to guide their Data Governance work over six months. Their lead explained how valuable it was to have someone to check in with, saying it gave them confidence they were doing the right thing—not just for the business, but for the people and customers too. With a modest amount of support, they were able to avoid common pitfalls, sense-check their approach, and move forward with clarity. That’s exactly what minimal, focused support should offer. 

Start small, think long-term

The trick to Data Governance on a shoestring is focus. Choose one benefit that matters, design a simple, strong approach to deliver it, and make sure what you build today can be reused and scaled tomorrow.

And, you don’t need a big budget to get started. You just need a clear goal, a smart plan - and maybe a little help from someone who’s done it before!

If you’d like any further help or information about coaching, take a look at my website coaching page. 
Or, check out this case study on coaching to see how it’s benefited my clients.

If you would like further support with anything Data Governance related in your organisation, you can book a call with me using the button below.

What is Data Custodianship?

What is Data Custodianship? It's a question that seems straightforward, but sometimes in Data Governance, definitions can vary depending on who you ask. And this is okay because some terms might not suit the culture or structure of your organisation. It's always best to prioritise what will work for your organisation specifically.

However, it is something to be aware of, particularly when ‘googling’ terms online or you're new to an organisation. Do not assume that when colleagues say Data Custodianship, they mean what I'm about to tell you. I would say the best thing to do if somebody uses a term like Data Custodian is to ask them what they mean by that and who that is. This clears things up from the start. You'll be on the same page as everyone else and can have useful conversations.

Who are Data Custodians?

When I talk about Data Custodians, I’m referring to the IT department. I often talk about the importance of business in taking ownership in managing and understanding data but, in this instance, IT remains a crucial player.

The role of Data Custodian differs from other roles in Data Governance, such as data Owners and Data Stewards etc. With these roles, I'd always recommend that you go and find named individuals. However, the opposite is true when it comes to Data Custodians because generally, I would say the whole of your IT department are Data Custodians. There are so many different areas of expertise and disciplines within an IT department that no one person will know absolutely everything about that system to be the Data Custodian for it. So I usually just say that IT are the Data Custodians for all the data that's held on IT supported systems at your organisation.

The responsibility of IT, as Data Custodians, lies in maintaining data on systems in line with the requirements of the business. This involves tasks such as data maintenance, migration, aggregation and transformation - all guided by business needs.

The misconception that IT own the data

FIt's important to realise that IT does NOT own the organisation’s data. Yes, it is on their systems, and they have the expertise that the business side of the organisation may not have, but IT shouldn't be expected to work out what to do with the data.

Before the introduction of formal Data Governance, businesses often rely on IT to make business data-related decisions, but this can lead to them being blamed for things. I think is unfair because sometimes they're just doing the best they can with poor requirements from the business.

Defining Data Custodianship helps both the business and IT

Data Custodianship helps to clarify roles and responsibilities within the IT department. When I work with IT departments, they are pleased with this Data Governance role as it gives them very clear business requirements and named business people to go to make decisions about data.

So this is a really good way of starting to break down some silos and get the business to understand what happens to the data when it's on systems. IT has always played the role of Data Custodian but, without Data Governance, they've perhaps done it without the input they needed from the business.

So having a Data Governance framework in place and identifying IT as Data Custodians is a really good way to start improving communications and making consistent, holistic decisions about data.

Understanding Data Custodianship is essential for establishing effective Data Governance practices. By recognising the roles of both the business and IT, organisations can foster collaboration, enhance data quality and make informed decisions that align with business objectives.

If you would like further support with anything Data Governance related in your organisation, you can book a call with me using the button below.

The Relationship Between Data Governance and Data Quality

We often talk about Data Governance and Data Quality in the same breath. This can lead to confusion, with some people assuming they are the same thing when actually, they’re not. However, they’re closely related, and in my experience, they work best when managed by the same team.

Understanding Data Quality and Data Governance

Data Quality is about making sure that data is good enough to use. It’s a straightforward concept, if data is incorrect, incomplete or inconsistent, it can’t support business decisions effectively.

Data Governance, on the other hand, is about creating a structured framework of roles, responsibilities, and processes to manage data.

Although they’re separate disciplines within data management, they are very much intertwined. When you try to improve data quality without governance, you usually end up applying short-term fixes rather than solving the root cause of data issues.

Why You Can’t Have Good Data Quality Without Governance

From my experience, many organisations focus on Data Quality long before they consider Data Governance. After all, it’s easy to understand the need for clean, reliable data. The problem is that without Data Governance, Data Quality efforts are often tactical rather than strategic.

For example, businesses might:

• Regularly fix errors in reports but do not address the source of the errors.

• Use automated data cleansing when loading data into analytics systems.

• Have teams manually correct data every month, quarter, or year.

These approaches may make data usable in the short term, but they do not prevent problems from recurring. The same errors will keep happening, and this is where Data Governance comes in.

Data Governance establishes:

• Roles and responsibilities so that specific people (Data Owners and Data Stewards) are accountable for data quality.

• Processes to resolve data issues at the source, rather than just fixing them repeatedly at the point the data is used (one of the most valuable Data Governance processes, in my opinion, is data quality issue resolution. This identifies and fixes the root causes of poor data quality rather than applying endless fixes).

Why Data Quality and Data Governance Should Be Managed by the Same Team

Because of their close relationship, Data Quality and Data Governance should be managed together. When separate teams handle them, challenges arise. I have seen organisations where the Data Quality team is focused on fixing errors while a Data Governance team tries to implement a structured framework of definitions and roles, and responsibilities. In such cases, business users tend to bypass Data Governance efforts entirely and go directly to the Data Quality team when they need a quick fix. Their immediate concern is solving their problem in the moment rather than considering long-term improvements.

When the same team is responsible for both Data Quality and Data Governance, they are able to provide short-term fixes while simultaneously working on long-term solutions, ensuring that immediate needs are met without neglecting the bigger picture. It’s also great because they can demonstrate the true value of Data Governance by proactively solving recurring data issues rather than simply reacting to them.

Moving From Reactive to Proactive Data Management

Without Data Governance, organisations are stuck in a cycle of fixing the same problems repeatedly. With Data Governance in place, they can shift to a proactive approach:

• Data issues are resolved at the source, reducing ongoing fixes.

• Business users understand their role in maintaining data quality.

• Data Owners and Stewards take responsibility for preventing and fixing errors.

Many organisations still manually cleanse data before they can use it. However, this is a waste of time and resources and is something which Data Governance eliminates.

Final Thoughts

If your organisation is focusing on Data Quality without Data Governance, you are likely applying temporary fixes rather than permanent solutions. While Data Governance and Data Quality are distinct disciplines, they should work together, ideally within the same team, to ensure sustainable data improvements.

If you found this helpful, please consider sharing this article to help others improve their approach to Data Governance and data quality. And if you’d like more support, you can book a call with me using the button below.

If you would like further support with anything Data Governance related in your organisation, you can book a call with me using the button below.

Who is Responsible for Drafting Data Definitions?

Good data definitions are essential. I can’t emphasise enough that without them, you’ll lack clarity and accuracy, and your data will suffer for it. But who should actually be writing them? I’ve written extensively over the years about how to create strong data definitions (read more about that here), but I don’t think I’ve ever really tackled the question of who’s responsible for writing them.

Spoiler: it’s not the Data Governance team!

Who Should Really Be Writing Data Definitions?

I recently heard from a Data Governance Analyst whose team was under pressure to write data definitions for their entire organisation. The business wanted the Data Governance team to take ownership of this task, but from my perspective, this is not the Data Governance team’s job.

The reason is simple: the Data Governance team cannot possibly be experts in every single piece of data that your organisation owns. It’s the business users who know the data best, so they are the ones who should write the definitions.

By all means, the Data Governance team can support the business by providing guidance, advice and training on how to write good definitions. You might run workshops, offer templates, or give feedback, but the actual drafting needs to come from the business. After all, if the business uses the data and relies on it for decision-making, it only makes sense that only they are in the position to define what it means.

The Role of Data Owners and Data Stewards

This is where the roles of Data Owners and Data Stewards become essential.

Data Owners - accountable but not for drafting

Data Owners are senior people in your organisation. They are accountable for a specific set of data, which includes being responsible for reviewing and approving definitions. However, they’re typically too senior and busy to draft definitions themselves.

Data Stewards -drafting the definitions

This is where Data Stewards step in. Drafting data definitions is a key part of their role. They are usually the subject matter experts on that data, and therefore, have the knowledge and expertise to create definitions for the data.

Sometimes, a Data Steward might not have all the answers and will need to work with other business users in their area. That’s perfectly fine, as long as the definitions are drafted by those who truly understand the data.

Good data definitions are the foundation of reliable, usable data but creating them isn’t the job of the Data Governance team alone. While data governance provides the framework, tools, and support, it’s the business, especially Data Stewards and knowledgeable users who must do the heavy lifting.

If your organisation wants meaningful, accurate, and widely accepted data definitions, involve the people who use and understand the data every day. Empower your Data Stewards, support your Data Owners, and let the Data Governance team guide the process - not own it.

That’s how you build definitions that actually work.

If you would like further support with anything Data Governance related in your organisation, you can book a call with me using the button below.

Why Every Organisation Needs a Data Governance Council

Data is evolving all the time, and many organisations find it hard to keep up with how to manage it properly. As data piles up, so do the problems. Ownership confusion, unclear responsibilities, data quality issues, and regulatory compliance risks. That’s where a Data Governance Council or Committee (DGC) can become really helpful. In fact, I would go as far as saying that they are essential for successful Data Governance.

In today’s blog, I want to talk about how a DGC can tackle your organisation’s challenges and support you.

1. Accountability

Imagine this… You’ve been named a data owner. It sounded important at the time… but months later, no one’s reminded you what that role actually means.

That’s a common scenario. And that’s exactly what a DGC prevents.

Why it matters:

• It clarifies roles for data owners and data stewards so no one’s left guessing.

• It keeps governance alive, not just as a one-off project but a consistent business practice.

• A functioning DGC doesn’t let responsibilities slide. It builds accountability into the structure.

2. A place to go when problems arise

There are many problems which can arise with data and they happen more often than anyone likes to admit. What matters is how your organisation responds.

The DGC advantage:

• The council acts as an authoritative escalation point run by peers who understand the business.

• It creates a safe space for collaborative problem-solving, not blame.

• Instead of letting issues fester, the council ensures they’re dealt with constructively and with the right people in the room.

3. Making the invisible visible

Ever spotted dodgy data in a report and thought you’d better not say anything? Maybe it felt too risky, or perhaps you weren’t sure it was your place to speak up. You’re not alone. In many organisations, poor-quality data flies under the radar simply because people stay quiet and do not escalate the issues to senior stakeholders.

Why?

Sometimes it’s fear of blame. Other times, it's just unclear where to take the problem. So the issue stays hidden and becomes part of the decision-making process anyway. That’s when risks really start to build up. And this is where a Data Governance Council is useful.

• It creates a safe and structured channel for raising concerns so people aren’t left wondering if they should speak up or stay quiet.

• It gives staff a clear process to follow, which helps them act early rather than waiting for a crisis.

• And most importantly, it brings these issues to senior leadership, turning vague worries into visible problems that can be prioritised and fixed.

Over time, this shifts the culture. Raising a concern about data quality stops feeling like "making a fuss" and starts being seen as good data governance. That makes it easier to catch issues early, before they impact customer experience, compliance, or strategy.

4. From rules to culture

Policies alone will not change behaviour, and that is why, as well as being operational, a well-composed DGC is also supportive of Data Governance culture.

Here’s how it shifts mindsets:

• Data Owners from across departments make decisions, promote best practices and lead by example.

• It sends a clear message that senior management has signed up to and is supportive of the Data Governance initiative.

5. Governance that guards against risk

Compliance and risk are constant concerns, but a static framework might not be the most beneficial. You need active oversight.

That’s exactly where the DGC proves its value:

• It ensures that your Data Governance Framework evolves to meet the changing needs of your organisation.

• It keeps Data Governance practices aligned with changing regulations, helping your organisation stay compliant without constantly scrambling to catch up.

• It enables ongoing monitoring, so gaps are spotted before they become Issues going forward.

Final thoughts

A Data Governance Council might sound formal and it plays a serious role. But at its heart, it’s about creating the right conditions for people to do the right things with data. It gives structure to conversations that otherwise get lost, and it brings clarity where confusion often lives.

If you're building, or rebuilding, your data governance approach, having a council in place won’t solve every challenge overnight, but it will give your organisation the foundations, the forum, and the follow-through it needs to make real progress.

If you’d like to discuss getting support for your Data Governance initiative, why not book a call with me below?

What Problems Do Data Governance Councils and Domain Forums Actually Solve?

Data Governance councils and domain forums are often seen as just ‘talking shops’; all discussion, no action. But when done right, they can be much more. I asked data professionals from my network what problems these groups actually solve, and their answers offered lots of food for thought! Here’s what I learned from the discussions.

What Do Data Governance Councils Solve?

Think of a Data Governance council as the command centre for an organisation’s data strategy. Their job is to set the rules, define roles and make sure everyone understands how to manage and use data properly. When I asked my network of data professionals, 'What problems do Data Governance Councils solve?' here's what they had to say:

Councils can create a clear framework - councils establish processes, assign responsibilities, and even decide how data projects get funded. This makes sure there’s no confusion about who owns what.

Councils can solve data disagreements - when different teams have conflicting views on how data should be defined or used, the council acts as a referee. They can resolve disputes and provide clarity on tricky issues.

Councils can spotlight hidden problems - councils bring important data issues to senior leaders’ attention. Problems that might be ignored in day-to-day work can be raised and discussed.

Councils can provide executive backing - they help secure leadership support for new ways of working, ensuring changes are properly approved and supported.

Councils can manage risk and compliance - councils reduce business risk by making sure data policies comply with legal and regulatory requirements. They also set protocols for handling data breaches or other serious issues.

And What About Domain Forums?

While councils focus on the big picture, domain forums dive into the details. They take the council's decisions and make them work within specific business areas. Here's the problems they solve, as found by my network:

Putting plans into action - forums turn high-level strategies into everyday practices. They adapt enterprise-wide policies to fit the specific needs of different teams or departments.

Fixing data problems locally - if a team notices data quality issues, they can raise them in their domain forum. This helps catch and fix problems early before they become company-wide headaches!

Promoting collaboration - forums encourage teams to work together; sharing insights and learning from each other’s experiences. This can be invaluable for improving data processes across the business.

Clarifying accountability - forums make sure everyone understands their role in managing data. This helps prevent tasks from falling through the cracks.

Making It Work

So it’s not just me believing that they add value. There is a lot of value to be gained Data Governance councils and domain forums. These are answers by real people who find value in these groups. But remember, for councils and forums to be effective, they need clear goals and active participation. If they become one-sided updates or just another meeting on the calendar, they lose their impact. However, when run properly, they create space for collaboration and highly effective problem-solving.

As always, if you’d like any support with your Data Governance initiative, book a call with me below and we can discuss your needs further.

How Often Should You Revisit Your Data Governance Maturity Assessment?

One of my clients recently asked how often they should be assessing their Data Governance maturity. It’s a great question because many people underestimate how long Data Governance takes to implement and a maturity assessment is a useful tool to track progress and figure out what to focus on next.

In today’s blog, I’ll be exploring Data Governance maturity assessments in more detail.

What is a Data Governance maturity assessment?

A Data Governance maturity assessment helps you see what’s working, where the gaps are, and what needs improving.

But, the timing of carrying out these assessments is important because, as I mentioned above, Data Governance does take longer than you think, so you don't want to overestimate the number of assessments you need. You want to find a balance between making improvements and not overwhelming the team or resources. 

How often should you assess maturity?

From my experience, once a year is usually enough. This is because real change takes time. If you assess too soon, you might not see enough progress to justify the effort. Plus, people are busy - you don’t want to keep asking for their time if nothing major has changed.

That said, the timing can depend on how quickly your organisation is evolving. The best approach is to look at what’s been happening internally and decide whether it’s the right time for a reassessment.

Communication and culture

Maturity assessments aren’t just about checking progress - they also reveal how well Data Governance is being communicated across the organisation. 

When you're looking at the results of a Data Governance maturity assessment, don't take every result to mean that you're not doing certain things - it might be your communication at fault rather than the fact that you haven't done something! 

I remember times during my early career in Data Governance when I'd got results back from a maturity assessment and had been devastated because it stated that we hadn't done something that we had actually worked really hard on doing! I remember thinking, ‘We've done that. Why are they saying there are no data owners in this area? There clearly are!’ 

And then when I actually thought about it, I realised that yes, we'd done the work as a Data Governance team but what we hadn't done was communicate it to the wider audience. And the problem with this is that Data Governance doesn't work unless everybody's on board. You need to make a culture change and for that, you need to communicate. If people don’t know what you’ve achieved it’s as though it hasn’t happened for them!

Data Governance maturity assessments are brilliant tools for guiding and measuring the progress of an organisation's Data Governance efforts. However, they are most valuable when done at a pace that aligns with the organisation's ability to make change. Whether done every six months or annually, the focus should always be on actionable steps and creating a culture that values data as a business asset.

As always, if you have any questions or need further support with optimising your Data Governance initiatives, feel free to book a call with me using the button below.

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