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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What's The Difference Between My Live and Pre-recorded Online Training Sessions?

When it comes to training in Data Governance, I like to keep the options available to you as flexible as possible. That's why, as well as the usual in-person courses, I offer two other types of training: live online sessions and pre-recorded courses. Both options have their unique advantages, so let me explain the differences to help you decide which is best for you or your team.

Live Online Training

If you’re looking for an interaction and you like learning amongst others, live online sessions are fantastic. Not only do you get to ask me questions on the spot, but you also get to meet others in the same field. There’s something quite helpful about hearing others’ stories and challenges – it builds a real sense of community, which I think makes learning more enjoyable (and a bit less daunting!).

I keep the sessions engaging by blending live calls with pre-recorded modules. You can work through the recorded material on your own, and then we come together for live Zoom calls to chat, answer questions, and bring everything together. This blended approach lets you learn at your own pace while still having that live, personal touch.

Pre-Recorded Training

If you prefer flexibility and want to go through the content on your own schedule, the pre-recorded sessions are ideal. With these, you can dive into the material whenever and wherever it suits you, and go back to any tricky parts as often as you need. I designed these courses with busy people in mind! So you can learn at your own pace and revisit bits until they click.

Pre-recorded training also has the benefit of consistency, so if you’re part of a team spread across different time zones or you’ve got a varied schedule, this option makes sure everyone gets the same high-quality content. Plus, it’s cost-effective for organisations that need frequent access to training or regular onboarding.

Which is Right for You?

Ultimately, it’s all about what works best for you. If you need flexibility, pre-recorded courses are a great choice. If you’re after real-time interaction and a bit of a boost from group discussions, live online training is right up your street. And if you’d rather meet in person and tackle your questions face-to-face, I also offer live in-person sessions.

I hope this gives you a clear picture of the options available. Whatever you choose, I’m here to support you if needed - you can reach out and book a call with me using the button below!

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Should the Data Governance Manager be Responsible for Implementing an MDM Tool?

This week, I'll be delivering a workshop on Master Data Management (MDM) at a conference, so this topic is top of mind for me right now and I thought I would quickly jot down some thoughts.

When you become known as the Data Governance manager or lead in your company, people might start thinking you're responsible for everything related to data. But that's not really the case.

So, when a company needs to choose a master data management (MDM) tool, should the Data Governance manager be in charge? Or is there a better way?

Balancing responsibilities 

Data Governance is vital to making an MDM project successful. If data quality problems aren't fixed first, even the best MDM tool won't work well. So, the Data Governance manager definitely needs to be involved. That’s a no-brainer.

However, I don’t believe that the Data Governance manager should be responsible for project managing the implementation of the MDM tool. Selecting and deploying an MDM tool is a big job that needs proper project management.. It makes more sense for a dedicated project manager to handle it, focusing entirely on getting the tool up and running.

The Data Governance team will have its hands full with its own important tasks, such as establishing and implementing Data Governance frameworks, defining and enforcing data quality rules and potentially cleansing data ahead of its migration into the MDM tool. These tasks are essential to ensure that the data managed by the MDM tool is consistent and reliable.

Effective collaboration between Data Governance and MDM teams is crucial

While the Data Governance team will be too busy to take on the whole MDM project, there still needs to be a degree of communication and collaboration between them and the MDM project manager. The Data Governance team brings expertise in data quality standards and the data governance framework, while the MDM project manager focuses on the technical and logistical aspects of the tool deployment. Below I have listed some practical tips on how to reach a level of collaboration between these two departments and their skill sets.

Practical Tips Towards Collaboration: 

1. Communication often and clearly -ensure that there is strong communication between the Data Governance team and the MDM project team. The Data Governance team should provide guidance on data standards, data quality metrics and governance policies to be followed during the MDM implementation.

2. Define the data - ensuring that you match and merge the correct data is key for a successful MDM implementation.  The Data Governance Team will be working with the Data Stewards and Data Owners to ensure that this is done for the data which is in scope for the MDM implementation.

3. Focus on data quality - the other main contribution of the Data Governance team will be to ensure that data quality is addressed. This involves defining data quality rules, monitoring data quality reports and resolving any data quality issues that arise.

4. Define roles and responsibilities - clearly define the roles and responsibilities within the project. The Data Governance team should focus on governance-related activities, liaising with Data Owner and Data Stewards,, while the MDM project team handles the technical and project management aspects of the tool’s implementation.

5. Encourage stakeholder engagement: The success of both Data Governance and MDM initiatives depends on active engagement and buy-in from stakeholders across the organisation. This requires communicating the benefits and importance of both initiatives effectively.

Well governed data sets the project up for success 

In short, while the Data Governance manager should not be responsible for the implementation of an MDM tool, their involvement is critical to make sure that the Data Governance principles are integrated into the project. This collaboration will help in achieving the ultimate goal of having high-quality, well governed data within the MDM tool, thereby maximising the return on investment for your organisation.

I hope you found this helpful. If you did, please help me reach as many people as possible by sharing this blog post on your socials. If you have any further questions or need to chat about something Data Governance related, feel free to book a call with me below.

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The Backstory of Data Governance and My Path Alongside It

I once read that every good story starts with a solid backstory. It got me thinking about Data Governance, this field I’ve dedicated nearly two decades to.

Data Governance didn’t just appear out of thin air; it evolved because organisations realised they needed better ways to manage, protect and make sense of all their information. But it hasn’t always been this way. Data Governance wasn’t always seen as the essential function it is today. In fact, when I first got into it, the field was still finding its feet.

The Backstory of Data Governance

Data Governance began when organisations started realising they needed a better way to manage their growing amounts of data. You see, at first, data was just a by-product of business activities, handled here and there by different departments without a clear plan. But as data volumes exploded and businesses relied more on data to make key decisions, it became clear that handling data inconsistently was causing problems.

In industries like finance and healthcare, where data accuracy is essential to meet regulations, the need for organised data management became apparent. These sectors were among the first to put formal practices in place to ensure their data was accurate and reliable, especially for reporting and managing risks. Over time, other industries saw the benefits, realising that structured data management helped them make better decisions and work more efficiently.

To address these challenges, Data Governance frameworks started to emerge. Tools like data catalogues and roles like “Data Stewards” and “Data Owners” were created to help standardise and oversee data quality. This approach encouraged businesses to treat data as an asset - something valuable that needed clear ownership, quality checks and consistent standards.

It’s been quite the journey so far and today, many organisations understand that Data Governance is essential if they want to make the most of their data. But it hasn’t always been this way. The best way I can describe this is by taking a look at my own backstory within Data Governance.

My Journey into Data Governance

Today, I call myself  "The Data Governance Coach," because I help organisations successfully implement Data Governance, but my journey here was accidental. For over two decades, I’ve been helping companies clean up messy data and avoid costly mistakes from poor data quality.

It all began when I was a project manager at a bank, leading a data warehouse project. We delivered it on time and on budget, yet users soon complained that the data itself wasn’t reliable. That’s when I realised that no shiny new system can fix bad data if the data itself isn’t improved. I wanted to address this, but my boss told me, “You’re just a project manager.” It was her gentle way of saying, “Stay in your lane.” But the data issues kept gnawing at me - I knew the data was bad and that nothing would improve if the data didn’t first. So, even though I’d been officially “put in my place,” I kept quietly poking around, asking questions and finding every opportunity to chip away at those data issues. Little did I know, that was my first step into Data Governance.

I started from scratch, learning through plenty of early mistakes. One of my first lessons was talking to the wrong stakeholders - those who didn’t care all that much about data. I’d excitedly dive into data issues with senior execs, only to realise they really weren’t interested. I learned that Data Governance isn’t just about fixing the data; it’s about getting the right people on board.

These early missteps taught me how to speak the language of decision-makers and build support for data initiatives. What seemed like mistakes at the time ended up shaping how I approach Data Governance today, focusing more on the people side of things than the technology that our data sits on.

Then and Now

Looking back, both the evolution of Data Governance and my own journey have been somewhat intertwined. When I first started, Data Governance was still finding its footing, and now it’s clear that it’s more critical than ever. Companies today rely on data for nearly every decision they make, and without strong governance, that data can quickly become more of a liability than an asset.

Just as I’ve learned the hard way over the years, Data Governance has evolved into something more complex, and vital. It’s no longer just about managing data; it’s about treating it as a valuable resource and ensuring that the right people are responsible for it.

So, I’ll leave you with this: Is your Data Governance where it should be? Are you fully utilising your data as the asset it is? If not, don’t worry! You don’t have to figure it all out on your own. You can book a call with me using the button below.

Data Governance Interview with Marti Smith

Welcome Marti Smith to the Data Governance Interview!

An intro to Marti!

Marti Smith, CDMP Associate, is an experienced Data Governance professional with a proven track record of implementing and managing Data Governance programs across diverse industries. Currently serving as Master Data Governance Manager at EnerSys, Marti has also held key roles at Tyson Foods and Smith & Nephew. Marti’s expertise spans Master Data Management, Data Quality programs, and BI/Analytics Governance, including leading the operational implementation of Collibra, transforming the existing installation into a fully functional Data Governance program.

With a passion for data quality and process optimisation, Marti has consistently delivered measurable improvements in data accuracy and operational efficiency. She holds a Master of Science in Supply Chain Management from the University of Arkansas and a Bachelor of Science in Finance from Wilmington University.

I first met Marti when she came on one of my training courses. It was so lovely meeting her and I just loved her enthusiasm, so I had to ask her to be a part of one of my blogs.

How long have you been working in Data Governance?

I officially began my journey in Data Management and Data Governance about 10 years ago, starting as a Data Quality Analyst in 2014. Since then, I have taken on various roles within the Data Management spectrum, which has allowed me to explore different facets of Data Governance, including Master Data Management and Data Quality programs. This diverse experience has equipped me with a comprehensive understanding of how effective Data Governance can drive organisational success.

How did you get into Data Governance?

Throughout my career, I found myself being the "go-to" person for data in every role I held since 2008. This natural draw towards managing data led me to meet my mentor, Melissa Hollingsworth, who introduced me to the formal practice of Data Management. Initially, I was working on the business side, where I developed a strong understanding of how data impacts business operations. My innate interest in organising and leveraging data effectively caught Melissa's attention, and she recognised the potential in me to pursue this as a dedicated career path.

In 2014, I made a significant transition to IT when I accepted my first official role in Data Management as a Data Quality Analyst. This shift was made possible thanks to Melissa, who took a chance on me and encouraged me to pursue this field.

Now, do I believe Data Governance belongs in IT? Well, that’s another story for a different day!

What characteristics make you successful at Data Governance and why?

I believe my success in Data Governance comes from my passion for helping people improve their processes. I truly believe that 99% of business problems are tied to data or process issues, and I love working with teams to identify and fix these challenges.

I have a knack for analysing problems and finding practical solutions that make life easier for everyone involved. My ability to communicate technical concepts in a straightforward way helps bridge the gap between IT and business teams, fostering collaboration and trust. Overall, my focus on process improvement and my collaborative approach are key to my success in this field.

Are there any particular books or resources that you would recommend as useful support for those starting out in Data Governance?

The first book that significantly influenced my journey was the Data Management Maturity Model, developed in conjunction with the CMMI Institute. Melanie Mecca, who was instrumental in writing and developing this model, provided incredible insights into data management practices.

I frequently refer to DAMA's Data Management Body of Knowledge (DMBoK), which provides best practices and a common language for Data Governance professionals. The DAMA organisation has made significant contributions to the field by establishing standards and resources that guide practitioners. Additionally, their CDMP certification program provides practitioners with a valuable platform to showcase our capabilities and expertise in Data Management.

I also recommend following thought leaders in the field, such as Sunil Soares, who has authored numerous books on Data Management and Governance, and Nicola Askham. Their articles, publications, and insights can be invaluable for those of us looking to deepen our understanding of Data Governance.

What is the biggest challenge you have ever faced in a Data Governance implementation?

The most significant challenge I've consistently encountered in Data Governance implementations is navigating internal politics and driving adoption. It often feels like pulling teeth to get stakeholders on board and fully engaged with Data Governance initiatives.

This resistance typically stems from a combination of factors: fear of change, lack of understanding about the benefits, and concerns about increased workload or loss of control. Overcoming these barriers requires a delicate balance of education, diplomacy, and persistence — areas that I honestly consider to be some of my weak spots.

Is there a company or industry you would particularly like to help implement Data Governance for and why?

For my next role, I aspire to work for any company that genuinely values Data Management and Data Governance. I seek a leader who strikes the right balance between providing hands-on support and allowing me the autonomy to excel in my role. It’s important to me to be part of an organisation that embraces Data Governance as a core function and fosters a culture of collaboration and kindness.

I want to work in an environment where team members support one another, share knowledge, and encourage growth. A positive workplace culture that prioritises respect and teamwork is essential for me, as it not only enhances productivity but also makes the work experience enjoyable and fulfilling. Ultimately, I’m looking for a company that aligns with my values and is committed to leveraging data effectively for better decision-making.

What single piece of advice would you give someone just starting out in Data Governance?

Start small and find your tribe. Begin by familiarizing yourself with the fundamental concepts of Data Governance and gradually build your knowledge from there. Don't hesitate to ask questions and learn from those with more experience.

Additionally, focus on solving a business problem. If possible, talk to your leaders and executives to understand what keeps them up at night. Identify their key challenges and work backwards to determine how Data Management can help address those issues. This approach not only demonstrates the value of Data Governance but also positions you as a proactive problem solver within the organisation.

As you grow, remember that building relationships and collaborating with others will be key to your success in Data Governance.

Finally, I wondered if you could share a memorable Data Governance experience (either humorous or challenging)?

I would like to share a personal experience that underscores the importance of a robust Data Governance program that incorporates Data Quality Management. In 2006, my bank mistakenly deposited $45,000 into my checking account due to a data quality issue. While it was certainly a surprising moment, I recognised the significance of accurate data and the potential consequences of errors like this. Naturally, and sadly, I returned the money. However, it is a vivid reminder that effective Data Management is not just about compliance; it directly impacts people's lives and the reputation of businesses.

Do You Need a Data Strategy and a Data Governance Strategy?

With the increasing importance of data, many organisations are asking whether they need both a data strategy and a Data Governance strategy. I've been doing Data Governance for over twenty  years now and I'll be honest - in the first fifteen years, no one even talked about a data strategy or a Data Governance strategy. But, before we dive into the answer, let's start by getting the basics straight.

What Is a Data Strategy?

A data strategy is like a game plan for how a company uses its data to reach its business goals. Think of it like an architect’s blueprint for building a house—it lays out exactly how data will be collected, managed, and used across the organisation.

Here’s what a data strategy can include:

1. Vision and Objectives – This is the big picture. It’s about how the company wants to use data to support its goals.

2. Data Governance Framework – These are the rules and roles that keep data organised, secure, and compliant.

3. Data Quality Management – This makes sure the data is accurate and reliable by setting clear standards.

4. Technology and Tools – These are the systems and software that help collect, store, and analyse data for better decision-making.

A data strategy is important because it acts like a map in a world overflowing with data. Without it, organisations can easily lose direction. With a clear strategy, businesses can make smarter, faster decisions because they’re working with accurate and reliable data. So, in short, a solid data strategy turns scattered information into meaningful insights that drive success.

So Where Does a Data Governance Strategy Come in?

Over the last few years, there's been a lot more of a focus on data as a valuable asset than ever before and with this has come a shift in focus from individual fields, such as Data Governance, to broader ones, like data strategies. Therefore, Data Governance should be a key part of the data strategy yet a Data Governance strategy differs because it focuses only on setting policies, procedures and standards to ensure data is accurate, consistent and used correctly. It’s not usually the job of someone working on a Data Governance strategy to create the entire data strategy yet there can be some confusion surrounding this.

Due to Data Governance being part of a data strategy, it can get a bit confusing when we call what we do a ‘Data Governance strategy’. As a Data Governance lead, your job is to make sure your governance practices fit within the broader data strategy and align with the organisation's corporate strategy and goals.

Therefore, if you have a data strategy in place, then I don't think you need a Data Governance strategy. You've already done the work and can take the Data Governance elements out to form your plan, which you'll be able to share with stakeholders when talking about Data Governance.

If you don't have a data strategy, it's up to you whether you create a Data Governance strategy, but remember you must align it first and foremost with your organisation's corporate strategy.

At the end of the day…

You can call your plan a Data Governance strategy if you want to. I rarely do, and I rarely recommend that my clients do because I prefer keeping terms simple and not confusing.

Overall, as a Data Governance lead everybody will expect you to have a high-level plan or approach for what you're doing and, if you think it will help you, you can call it a Data Governance strategy. However, from my experience, if your organisation has a data strategy I would avoid having a separate Data Governance strategy. We need to embrace simplicity and avoid scaring people away with the prospect of more documents to read!

If you found this helpful, please share it on social media, and if you have any more questions about this or anything about Data Governance, you can book a call with me below.