Yikes! What can I say about 2025 except that it’s been life changing.

When you get to my age, sometimes you feel like there’s not much more to learn but guess what; that’s just not true. I am blessed that I am still learning.

Being by default a teacher, I have always been interested in the process of learning and trying to help people improve their knowledge and skills, their understanding and interest.

I am keen to hear how people are doing, where they are succeeding and where they face challenges, and to share what is working for me.

So, how has this year been for you, has it been a good one, or has it been a challenging year? For me it has been quite exciting. I travelled to Norway and Iceland and would you believe it, Greenland, and gained a different perspective of the world I live in. I saw real icebergs and they reminded me of the complexity of data. Data is something in which I have always had in interest.

Standing there in the Arctic, watching these vast ice formations, I realised that ignoring what lies beneath the surface is exactly what causes us problems. You can't navigate safely by only focusing on what's above the water. You need to grasp the full picture: the good, the bad, and the hidden, to truly master your environment.

Coincidentally, this year I also gained a different perspective at work. I have been involved in new tasks that use data with which I am not very comfortable. It has made me practice what I preach: to go back to basics, following the same advice I have been sharing with others, to ensure that this data and its environment are managed properly.

How has 2025 been for you?

As we approach the end of the year, in addition to how well has your 2025 gone, let me ask you a few data specific questions:  

• Have you tackled specific data initiatives?
• Have you established useful data forums?
• Have you, or your organisation, acquired new data skills?

Overall, are you satisfied with your data?  Does your data meet your needs? Is it available when & how you need it? Is it of good quality? Can it support your future business requirements?  

Most of the people I have asked have not been able to answer positively. Considering this, I looked back on the year to see what we had tried to teach people.  

Looking back on 2025

Overall, we covered quite a lot in what has been an interesting year. I certainly found ‘back to basics’ to be an excellent reminder that what seems simple and obvious holds great value.  

Often, we overlook the basic truths of data and the fundamental things we need to do.

Getting back to basics - understanding each other

My role as a trainer mainly involves understanding. Understanding what people want to know versus what they need to know and balancing the two, so I meet expectations. Therefore, I spend time ensuring my language is suitable for the audience and continually evaluate their understanding.

• Does your organisation speak a common language when dealing with data?
• How well do you all understand the fundamentals, terms, and concepts?
• How effectively do people communicate? Do they always understand each other?

Let's flip these questions:

• How frequently do you misunderstand each other when working with data?
• How frequently do communication issues influence results?
• Is Data Literacy a competency that your organisation has mastered?

Data Literacy is so fundamental and foundational, but often overlooked.

Tackling Data Debt and Data Quality

I recently faced a problem with my laptop and couldn't believe the ‘data debt’ I had built up over just two years. Get your own house in order!

Building the Data Triangle

We examined the vital importance of Data Stewards and the need for Data Owners and Data Stewards to truly collaborate, rather than operate separately. The Data Triangle remains incomplete without the cooperation connecting these two essential roles.

• Are your Data Owners and Data Stewards collaborating effectively, or working separately?

Have you established the necessary bridges to make this partnership succeed?

The Role of Data Stewardship in the world of AI

The marvellous ‘Data Diva’ Lisel Engelbrecht joined me earlier this year for a webinar to share her views on the evolving role of Data Stewards in the age of Artificial Intelligence. It reminded me that we must embrace change, why be threatened by change? Surely, we have always adapted to it.

This session motivated me to really understand AI and its potential in data environments. WOW! What can I say? I experimented, explored, and made friends with many AI tools. I created templates to remind me to include context, questions, and audience details. I improved my approach and learned to work alongside AI.

Wow again! Working alone at home, I suddenly felt as if I had a colleague in the room with me. 'We' could explore, debate, agree and disagree. I'd propose an approach, AI would challenge it or suggest refinements, and together we'd arrive at something better than either of us could have created alone. It's an example of collaboration in its truest sense, building on one another’s strengths.

• Are you seeing AI as a threat to your role, or as a tool to improve it?
• What would change in your Data Management Approach if you had a tireless assistant who was always available?

The Power of Education

When you train a team, they experience together and leave with a shared understanding of what to apply on the job. You gain so much more than just knowledge. This simple yet highly effective training method makes a real difference.

I am currently training a team, and what has been especially rewarding this time is that the delegates now view their data from varied perspectives – not just their own. They now recognise how their colleagues rely on and utilise the data they generate. A true AHA moment for the team😊

• Are you still sending individuals off to courses, or have you started training as a team?

When you train together, you establish alignment, develop a shared language, and ensure everyone starts from the same baseline. Additionally, you make the problem and solution everyone's responsibility. Training as a team isn't just more cost-effective; it also fosters a collaborative culture and the shared accountability you need.

Wrapping up this year

Looking back, I find it interesting to see how many things we can do that are simple.

When we started with 'Back to Basics' earlier this year, I wasn’t considering myself; I didn't realise it would apply to me too. Once I did, everything changed.

As this year draws to a close, I am pleased with the progress I have made. I faced the challenges directly; yes, I struggled, but I am now ready to enter the new year with new skills and a fresh mindset. Just as those Greenland icebergs reminded me to look beneath the surface, 2026 will focus on going deeper but not more complicated - more fundamental.

Let's make next year the one where 'back to basics' finally becomes a habit.

A message to All Managers especially those in Learning and Development positions:

Why your organisation's success depends on everyone speaking the same data language

What does every job in your organisation have in common? Yes, of course - it's data!

From HR records and employee surveys to finance and operational reports, from customer sales and performance metrics to risk analysis and compliance reporting, data underpins everything we do.

However, the truth is that while we've become increasingly dependent on data to drive decisions, most of our workforce lacks the fundamental skills to work efficiently with it or communicate effectively about it.

The problem isn't that people aren't capable enough – it is simply that no one has taught them the data language and the basics they need to work effectively with data.

This is fixable through appropriate and effective education.

What People Need to Know

The fundamentals are straightforward but rarely taught:

• Knowing what data means and how it's used - not becoming a statistician, but understanding its context and purpose for the organisation
• Understanding upstream and downstream effects - knowing who produces and uses data, and how it impacts the business as it flows through the systems
• Appreciating quality data – being able to recognise complete, accurate, and timely information whilst identifying potential issues before they become problems.

If people understood these fundamentals, they would perform their jobs more effectively, make fewer errors, become more productive, face fewer challenges, and make a greater impact on the organisation.

When you build a foundation of Data Literacy, you achieve results on three levels:

• Individual transformation - Employees understand the impact of their work, become more confident working with data, and begin to drive data-driven operations
• Cultural transformation - Data Quality becomes everyone's responsibility rather than just IT's problem, ensuring a collaborative approach
• Organisational transformation - Decision-making becomes evidence-based, it is easier to embed compliance into operations, and innovation initiatives can gain the necessary traction.

The Hidden Cost of Data Illiteracy

Appreciating the importance of Data Literacy is a good start, but knowing how to translate this awareness into concrete action that transforms your organisation's data capabilities is the key. Understanding the effects of the problem will help you formulate an effective action plan that addresses your specific needs.

Data Debt is the hidden burden created when people fail to manage data effectively. Data Debt manifests as missing data, duplicate records, incomplete datasets, and inaccurate information flowing through your systems.

It arises when shortcuts are taken to quickly access or create data, leading to poor quality and inconsistencies, which in turn result in further unreliable information, eroding trust in analytics, hindering productivity, and stifling innovation.

Poor data quality and incomplete information require manual data management, which increases costs and decreases efficiency. Data Debt significantly impacts generative AI initiatives, making Data Literacy both a current necessity & future competitive requirement.

When your people lack a sufficient understanding of the data they are working with, they create more problems than they solve. When they don't speak the same data language:

• Terms are understood inconsistently
• Outcomes are unpredictable
• Decision-Making is impacted
• Compliance becomes a nightmare
• Innovation stalls due to issues with data fundamentals.

What’s Next?

The question isn't whether your organisation needs better Data Literacy, but how quickly you can implement training that makes a real difference. The time for action is now. Your data - and your organisation's future success - depends on it.

If you are a Learning & Development Manager, an HR Manager, or in a Data Management role, you should assess the level of Data Literacy in your organisation and decide where change is needed. Organisations investing in Data Literacy today will succeed tomorrow. 

With data underpinning everything your organisation does, you cannot afford not to invest in Data Literacy Training.

Making the Business Case

If you need to motivate for funding for the training, ensure that the decision-makers understand the consequences of the current situation. Explain the problem and effects when people across your organisation are not data literate.

When presenting to senior leadership, focus on these arguments:

• Risk mitigation - data breaches, compliance failures, and poor decision-making result from inadequate Data Literacy. Training acts as insurance against costly mistakes.
• Efficiency gains occur when people understand data properly; they spend less time correcting errors, searching for information, and resolving conflicts.
• Innovation enablement - AI and digital transformation initiatives rely on data and on people who understand data quality, data governance, and ethical handling.
• Competitive advantage - organisations with high Data Literacy make better and quicker decisions than their competitors.

If you are facing budget constraints, remember that by doing more with your current team and existing data, you can enhance knowledge and skills, improve existing business processes and support systems, and enable other initiatives to benefit from better data.

At a fraction of the cost of major transformation initiatives, you can optimise resources and create new opportunities through training. Education is especially valuable when budgets are tight. Train your staff, and your data improves. Improve your data, and your business improves. When you do, you'll realise that enhancing Data Literacy isn't just about teaching technical skills, it's about unlocking potential already within your workforce.

What you do with data depends on the job you do and how you do it.

What job do you do?

• Is it your job to respond to customer queries or complaints?
• Is it your job to prepare reports?
• Is it your job to increase sales?
• Is it your job to put out fires?
• Is it your job to  <<fill in the blank>>?

What does every job in your organisation have in common?

Have a guess. It's easy - it's data!!

Data is central to performing our jobs, yet no one teaches us enough about the data we use and produce daily, or why its quality is important.

What do you need to know about the data to do your job better? 

You need to know:

• What the data means and how it is used
• Who produces this data and who uses it
• That the data is correct and of good quality
• The data is up to date and trustworthy.

If you knew this stuff:

• You would do your job better and make less errors
• You would you be able to be more productive
• You would face less challenges and enjoy your job more
• You would be more valuable to the organisation.

So, we go back to the question, what are you doing to the data?

Let's improve our data skills, data literacy, and data quality awareness, and grow your data culture.

I remember when Data was …

Way back in 1968 when I started my career as a junior programmer – our Data was easy! We had text and numbers. That was it! No images, no videos, no audio clips. Just text and numbers.

All those years ago, we communicated with our Data in a very different way. Punch Cards, Paper Tape, enormous Magnetic Tapes and huge Disk Drives. Can you believe it was even more exciting? We could read the Data in its internal format. We all spoke hexadecimal. (You may have to google what this is). Hexadecimal was just one of many languages we had to learn to process and understand our Data.

In those early days of computing, we had 3 priorities – Requirements, Data, and our Programs.

I remember when Data was easy. I remember when Data was cherished, I remember when we were all responsible and accountable for the Data.

What's changed in the last almost 60 years? Well, I have got a lot older and we have lost or forgotten some of the key principles of managing our Data. Those key principles were; understanding the meaning of our Data, understanding the importance of our Data, identifying all the rules around the Data and validating against those rules before we stored the Data.

I remember when Data was understood consistently. I remember when Data Rules were defined. I remember when we made no compromises.

Have I got you thinking? Do you think we can recover some of the good stuff we used to do and combine it with the smart stuff we are now able to do? Let’s all remember the right stuff we should be doing.