[01:12] Kyle Winterbottom: Hello, and welcome to another LinkedIn live event brought to you by Orbition Group. Today, I am delighted to be joined by three fantastic guests. We're going to be talking all about data literacy, from planning all the way through to impact. As always, please get your questions in. We'll try to get them all answered as we go through the session. And if we don't get to any, we'll try to get those answered at the end if possible. We're going to be here for roughly 45 minutes to an hour depending on how we get on with time. So as I say, please get your questions in for our guests and, yeah, let's bring them on stage. Greg, Kate, Hannah, thank you very much for joining us today.
[02:00] Kyle Winterbottom: I obviously could do an introduction myself, but I won't because I never do that justice. You'll have to put up with me today, as you can tell, very nasally. So back end of last week, I got struck down by a sickness bug from the kids, and then, last night, I spent the majority of the evening shouting at the TV. So I'm a little bit croaky, a foot too. Greg, kick us off, introduction if you would, please.
[02:27] Greg Freeman: Yeah. Hi. My name is Greg Freeman. I'm the CEO of Data Literacy Academy. We help large organisations like Coventry Building Society to roll out data literacy, culture, and upskilling programmes across the wider organisation. Our specialist area tends to be in the non-data people, so we tend to do most of our work with business people and taking them on their data journey, which is the angle and the lens we'll take to today's conversation more than likely.
[03:01] Kyle Winterbottom: Absolutely. Thank you, Greg, for that. Kate?
[03:03] Kate Jones: Yeah. I'm Kate Jones from Coventry Building Society, and I'm the Head of Data Product and Strategy. I've been working with Greg at the Data Literacy Academy to set up our data academy.
[03:17] Kyle Winterbottom: Nice. Thank you for joining us. And Hannah, you've become a serial LinkedIn Live webinar participant, so welcome back.
[03:25] Hannah Davies: Thanks for having me again. I'm not sure I want to carry that title though. Oh, but hi, everyone. I'm Hannah. I am Head of Data Culture and Excellence at Admiral Group, and part of that role is founding and looking after our Data and AI Academy, where we not only do data literacy elements that Greg and Kate have talked about and we'll discuss today, but we also look after training our data professionals.
[03:51] Kyle Winterbottom: Yep. Nice. Well, thank you for agreeing to rejoin us. So I guess where I'd love to start, I guess with Kate and Hannah to start with, is just to lay or set the scene and, again, a lay of the land in terms of understanding what the catalyst was for starting your data literacy programmes. And I guess, you know, was there a point in time? Like, what triggered the awareness that, hang on, we have a need here. We are going to need some kind of programme around this. Kate, if I can come to you first.
[04:28] Kate Jones: So, yeah, I joined Coventry Building Society in September. When I joined Coventry, it was clear that there was executive-level sponsorship for us improving our data culture, and part of that was about making sure that we were managing our risk in relation to data. So data became a principal risk in January of this year, and improving our data culture and literacy was viewed as a key element of making sure that we are at an acceptable level of risk with regards to our data.
[05:09] Kyle Winterbottom: Nice. Makes perfect sense. Hannah, what was the catalyst for the start of the journey at Admiral?
[05:18] Hannah Davies: So I think it was probably a few things. The real standout moment for me was back in 2020 when we were going through our data strategy and really noting that, I guess, data literacy can cover all sections. It can cover those with very little data experience up to our data professionals and our data folk. We really knew that we wanted to do more to support people. But if I cast back to Admiral's beginning, we are an insurance company managing risk, thinking about our prices, understanding our customers. Data is integral to everything that we've done. But what we were seeing was that as we were moving into a more digital age and thinking about how we diversified and set up for the future, whilst we had lots of internal provisions for training our staff, we didn't really focus on data and what that meant. We'd often find our training courses starting to talk about using data to identify a vulnerable customer, for example, but there was no real foundational data knowledge that we were training. So it was almost a series of events and probably something that came much too late, to be honest. And I think we've got a real movement of data culture and data literacy becoming really at the forefront of minds, but I think it's a few years behind where maybe we should have been if I reflect.
[06:39] Kyle Winterbottom: Very interesting. Greg, I'd be keen to get your perspective on this because, similarly to our line of work, you get to see a plethora of different organisations, different sectors, and different sizes. Is there usually a tipping point when these types of programmes become, I guess, more palatable for businesses in terms of now being the time?
[07:01] Greg Freeman: Yeah, I think there is. And I mentioned this on a DAMA webinar that I did a couple of weeks ago. I think if your business is still at a point where it doesn't buy into data, then you're probably not at the right point for a data literacy programme. It needs to be assumed that data is valued and understood to a point where it's seen as valuable before you get going. That would be a prerequisite. Because if you're trying to sell data literacy to the C-suite and they don't care about data, you've got a long journey to go on. But, typically, we would see data literacy and culture most effectively aligned to things like change transformation programmes. So if there's a particular change transformation programme going on across the whole organisation or across a specific department, that can be a really good way to align data literacy and culture and, most importantly, get budget for it. If you're rolling out new data products and you want to align people and take them on the journey with that, I think that can be a really good time. And then, if you've got a data governance—this is the one that I'm probably the most like a broken record about. If you're doing a data governance programme, which, obviously, Hannah and Kate have both alluded to the risk of data and the need for it to be done in the right way, if you don't take the people on the journey with you, they ultimately won't care about things like data quality and data risk. If data is not valuable to them, if it isn't viewed as valuable, which according to Google, about 80% of the business probably doesn't see data as valuable today, just to scare everyone, they're not going to referee it. They won't do the right things with it. You have to take them on the carrot journey, which we would see as literacy, AI, data culture, as well as doing the data governance piece. So anyone who's thinking about all of those things, which most organisations are, I think it's a good time to build literacy and culture in and get the buy-in from the people that matter, who'll spend the money and take you on a bit of a journey with it.
[08:46] Kyle Winterbottom: Yeah, 100%. I mean, obviously, buy-in as a topic is something that always comes up in these things. I think it's really interesting that you talk about that being a prerequisite—that they've got to be bought into data before you even think about, you know, some of this type of stuff. Kate, I want to come back to you because you talked about there was already buy-in there, or that's the perception that you had. Who was that driven by, I guess, and why did it unravel the way it did?
[09:31] Kate Jones: So, as part of our data strategy, we had three pillars—every great strategy always needs three pillars—and data culture and literacy was a core element of that third pillar that underpins what we want to do with our data ecosystem and our data governance and risk. So, ultimately, when I joined the organisation, the data strategy had been taken to the exec and approved, and we had funding. My role was to basically make it happen and get the Data Academy up and running.
[10:13] Kyle Winterbottom: Nice. So it was already kind of the wheels were in motion. You were the person that they chose to execute. That makes sense. Hannah, from an Admiral perspective, who drove that initial piece around, "Let's do something here"?
[10:39] Hannah Davies: I think it's a really similar story to Kate's in that we had gone through the motions of our data strategy and focused on data culture and excellence there. We talked about that movement of training the business and supporting people by equipping them with skills for the future. That was very much driven by our UK Insurance Deputy CEO. He was the sponsor, and we were closely aligned to the business, particularly the data teams who were seeing value.
At the time, we weren't as aligned with our data governance function within technology. But there was a strong sense of, "This is how we move the needle. This is how we bring some of this data scale across our business."
We were close to those in our product areas, customer-facing teams, and others, which gave us the leverage to do something great and have buy-in from the start. There's probably not a board meeting or conversation at exec level today without data being referenced in some shape or form, which I think we’re lucky to be a part of. That’s not always the way people get to go on this journey, and it's not something we take for granted.
[12:06] Kyle Winterbottom: Really interesting. Greg, keen to get your perspective here. With the breadth of the different organisations you work with—and obviously, you work closely with Kate at Coventry Building Society—do you tend to find a common key stakeholder that status leaders listening to this should be thinking about schmoozing, for want of a better phrase, to implement a literacy programme?
[12:30] Greg Freeman: Schmooze—good word. Let's go schmooze with some commercial leaders because that’s what it really comes down to. What we don’t see is that you have to have the entire executive bought in, and that can help. If anyone gets that, it’s obviously a win, and I’d never say it’s not.
But people often see that as too much of a blocker. They think, "If the 8 to 10 people running the business don’t support this, how will we ever make it work?" Actually, you don’t need that many people. You do need commercial leaders and executive sponsors outside of technology.
We always aim to get an executive sponsor in technology, probably the CDO in most cases, but also one or two commercial executive sponsors. You need access to people. A lot of the people you’ll be working with are in departments, so you need a couple of places where you can say, "This will be successful here because I know I’ve got buy-in from this leader."
That doesn’t mean you need 8 to 10 executive leaders bought in right away. Those will come downstream as the programme proves itself. The better the PR becomes for the programme and the data office, the more of those leaders will get on board over time. It’s about finding those first two—those early adopters, those innovators.
If we think about that adoption curve, this works exactly the same way.
[14:08] The other thing I’ll say—because Kate made a great point—is that all data strategies have three pillars: people, process, and technology. A pain point for us is that when these three pillars are put out there, most organisations will get a consultancy to write a 74-page cloud infrastructure document, and it’ll take 7 to 9 months to get your technology designed. Then you build your processes and automations. But in a lot of cases, the "people" bit gets kicked down the road and forgotten about.
If I think about one of our most successful programmes, the Bentley Data Dojo with Andy Moore, why it worked so well was because Andy took literacy and culture on from day one. He said, "I’ve got a technology plan. I’ve got a process and automation plan. I’ve got an AI plan. Literacy will enable all of this, as will culture." That’s why it’s been so successful.
It’s not impossible without that, but if you’re building a new strategy, taking it as seriously at the start as everything else is a massive differentiator.
[15:30] Kyle Winterbottom: Interesting. Kate, I’d like to come back to you. Can you share some practical tips and tricks for getting that buy-in and taking people on that journey?
[15:53] Kate Jones: Sure. I worked closely with our internal comms team and L&D team. We set up a project team to launch the Data Academy. We created an internal survey around four learning personas: data skeptic, data dreamer, data knight, and data wizard.
We launched the Data Academy with quite a lot of fanfare, sent out the survey, and got over 700 responses across the organisation, which has 3,000 people. It was a great response rate.
We directed people to online learning based on their persona, but we also used the survey to identify participants for the first cohort in the Data Literacy Academy. We targeted the data dreamers and data knights. From that, we identified a functional leader—someone at a senior level we could engage with. Greg and the team met them to understand their data challenges, where they wanted to get to, and what they needed from data to deliver their strategy.
We worked with these individuals to identify who from the survey should be in the first cohort of 100 learners. We launched the survey and Data Academy in November 2023 and started the first cohort in spring 2024.
[17:47] Kyle Winterbottom: Perfect. I mean, 700 responses—that's pretty impressive to get that level of engagement from the start. Hannah, I'll come to you. In terms of taking people on that journey, getting them bought in, and ensuring adoption, is there anything specific that you felt worked?
[18:06] Hannah Davies: I think it's really about never underestimating the amount of work that goes into this type of program. I've heard it referred to in lots of different ways, but often people talk about rolling a stone up a hill. Once you've got that momentum, you've got to keep it going.
There’s a big piece where we often think of this activity as a side-of-desk task. Much like Greg mentioned, it’s seen as something optional rather than the game changer it truly is. But I think we’re now seeing a movement that understands how much value this unlocks.
When we started, it was just me for a long time. The first role we hired was an internal comms role, which is a similar journey to Kate's. The first six to eight weeks weren't just about building a business case but also building that internal network. To Greg's earlier point about finding places to hang your hat, we spent a lot of time thinking about how to make a difference, what behaviours we wanted to change, and what we wanted people to be able to do differently.
That could be reducing data risk, encouraging data-driven decision-making over gut instinct, or getting people to use dashboards instead of asking a data person every question. Self-service was another big focus. We spent significant time considering these behavioural elements.
The key difference in our approach was the decision to build the program in-house. I focused a lot on engaging the right people to make it successful. One of the biggest takeaways for me is that it’s not about one big moment where you say, “Yes, it’s done. I’ve accomplished this.” It’s a continuous journey. It’s lots of little things that collectively create change.
Keeping momentum and prioritising this work is the biggest tip I’d share. You can't let the momentum stop; it has to remain a focus.
[20:32] Kyle Winterbottom: Yeah, 100%. The general theme here is that this needs to be taken seriously as a priority from the start. It’s not something to be relegated to side-of-desk work or tackled when you get to it. By then, you’ve likely lost people.
We have a couple of questions, so I’ll get those answered. Matt’s asked for more context about SMEs, which I’m presuming means small and midsize enterprises. Hopefully, Hannah can clarify that for us.
[20:58] Matt asked: For someone who is selling this service to other organisations, what is usually the typical response? Is the objection mostly budgetary or something else?
[21:16] Kyle Winterbottom: Greg, I’ll come to you because you probably have the most visibility in these conversations.
[21:22] Greg Freeman: We do sell this service to organisations, so this is a perfect question for me. It’s difficult to say definitively, Matt, because it’s different everywhere.
One thing Hannah has done really well internally is to ensure this is viewed as important by the most influential people in the organisation. When that happens, things like budget stop being questions.
The projects and programmes that fail to get off the ground are often those where middle management tries to do everything themselves without involving senior leaders or external partners. They want to be seen as delivering it themselves, but the most successful programmes—like Hannah’s—are those with major champions at the highest level.
When senior leaders understand how this initiative aligns with their goals and scorecards, the budget opens up, and so does access. Programmes where external partners are also used often succeed because they can bring additional expertise and credibility to these conversations.
It’s really about overcoming objections rather than focusing on them. People will always cite time, money, and access as barriers. But if you strategically align the right people to the value of this programme, those barriers largely disappear.
[23:20] Kyle Winterbottom: Yeah, that makes perfect sense. Let me ask that slightly differently to Hannah and Kate. Were there any objections you came up against when going through this process? What did you need to demonstrate to make this a priority for stakeholders? Hannah, I’ll come to you first.
[23:42] Hannah Davies: It’s about understanding what’s important and why you’re doing this. Many of us could say, “We need a data literacy programme,” but for us, it was about tying it to our business values. We value doing the right thing, looking after our employees, and supporting our customers.
We focused on how this would benefit our customers and employees. When challenged on the business case, we were pushed to think broadly about behaviour changes and the measurable impacts of those changes.
For example, would this reduce data risk? Would it help people make data-driven decisions instead of relying on gut feel? Would it encourage the use of dashboards or self-service tools?
The emphasis was on fundamentally changing behaviours, equipping people with confidence in data, and changing the mindset of our organisation to think about data first—whether in creation, management, or usage.
It wasn’t about ticking a regulatory box or copying what others were doing. It was about creating meaningful change and articulating why data literacy was essential to that.
[25:30] Kyle Winterbottom: Interesting. Kate, how about your experience? Were there similar challenges or objections you needed to address?
[25:33] Kyle Winterbottom: Interesting. Kate, how about in your environment? You mentioned earlier that sponsorship and buy-in were already there. But were there things you needed to prove or lay out to get people more interested and engaged?
[25:51] Kate Jones: I think we needed to demonstrate that the syllabus from the Data Literacy Academy would meet our learning needs. I worked closely with our L&D team to identify the groups we wanted to train and to validate that the course content would cover those needs.
One of the great things about the Data Literacy Academy was their ability to tailor content to make it relevant for our organisation. Beyond that, we've also focused on upskilling our data professionals through apprenticeship programmes. While it’s not entirely free—since it takes up 20% of someone's time—it’s been a way to ensure we’re delivering the right learning interventions for the right people with clear learning outcomes.
[26:55] Kyle Winterbottom: That’s really interesting. It’s a good point because, from my experience, these initiatives sometimes get treated as blanket solutions. The bespoke nature of addressing an organisation’s specific context is hugely important. That brings me to the next question.
Greg, given the different sizes and scales of organisations you’ve worked with, does the structure of these programmes look the same? Or does it need to differ, say, between an organisation like Hannah’s with thousands of people and a smaller business?
[27:38] Greg Freeman: Yeah, I’ll be totally honest—structured learning programmes like this fit better in larger organisations. In big companies, even key stakeholders are often time-poor, which makes them a difficult audience to engage with. The more people a leader has reporting to them, the harder it is to secure their time. For example, a CEO in a large organisation responsible for 20,000 people is likely being pulled in every direction, making it almost impossible for them to sit down regularly for structured learning.
In SMEs, the dynamic is different. People wear many hats, often putting out fires, and everything tends to be reactive rather than proactive. This makes it harder to launch a formal structured programme. It’s also worth noting that implementing these programmes isn’t cheap, and budget constraints in SMEs are typically more pressing than in larger organisations.
That said, SMEs have opportunities to approach this differently. Smaller settings allow for more personalised, one-on-one coaching, small group sessions, and lunch-and-learn formats. Instead of asking people to dedicate eight or twelve months to a programme, you can focus on incremental knowledge shifts and behavioural changes that add value immediately.
For example, in our business—which is an SME with about 80 people—we don’t run formal programmes like this, apart from apprenticeships. However, we’ve implemented quarterly learning initiatives that include lunch-and-learns, team training sessions, curated reading materials, and even distributing books on relevant topics. Data literacy could easily be a focus of one of these initiatives without needing to be a massive programme.
[30:35] Kyle Winterbottom: From a people perspective—and this is me thinking out loud—it seems like larger organisations tend to do this in a structured way, hiring dedicated people like culture and comms specialists. In SMEs, we don’t often see roles like data comms specialists. Does that difference affect the effectiveness of these programmes?
[31:19] Greg Freeman: Exactly. That definitely plays a role. Using Kate’s example at Coventry Building Society, she has a lot of support from people who excel in their respective roles. For instance, one of her key contacts is an L&D expert who played a vital part in laying the programme’s foundation.
Having dedicated project managers or programme managers makes running such initiatives much more manageable on a day-to-day basis. Without those components, it’s tough to run a programme effectively. This is why structured programmes work better in organisations with 1,000 or more employees.
We do work with some businesses below that threshold, but only when they have strong champions—whether it’s a CEO or a head of data—driving the initiative. But typically, structured programmes of learning and change are more effective in larger organisations.
[32:31] Kyle Winterbottom: Interesting. Kate, could you expand on how you built your Data Academy and why you chose that approach?
[32:51] Kate Jones: We used the Data Academy as a template for other key skills we wanted to build out, like digital and software engineering academies. It was important to avoid reinventing the wheel.
We created a space on our internal platform, Engage, which is like a workplace version of Facebook. This became a community hub. We also added a dedicated section for the Data Academy on our Learn platform, where employees access mandatory training, and created a presence on the company intranet.
While these virtual spaces were helpful, having in-person conversations was equally important. We ensured data stewards and data owners were appointed and regularly briefed our executive board on how the academy was improving engagement and learning around data.
[34:09] Kyle Winterbottom: Hannah, I know we’ve spoken about this in different contexts before, but could you share how you set up your academy and why you approached it that way?
[34:21] Hannah Davies: Our academy encompasses multiple elements, and I often feel calling it an academy doesn’t fully capture what it does. We focus on training data professionals, fostering literacy and mindset (though we don’t call it literacy internally), and building a strong data community.
To Greg’s earlier point, community can alleviate the burden on a single person to drive everything. It’s still crucial to prioritise, but steering committees and active communities help spread the responsibility.
We started with pilots, focusing initially on data professionals to retain talented individuals while helping the wider business. From there, we integrated the academy into our central L&D systems, so it felt seamless for users. Using existing platforms also reinforced consistency—employees didn’t feel like they were engaging with something separate from other training.
Having a strong L&D team was key to fostering curiosity and building an active learning culture. We’ve emphasised ongoing conversations rather than a “take the course and move on” approach. For instance, we engage leaders to think about how they approach data conversations, what they need to learn, and how they motivate their teams to use data differently.
Ultimately, the blueprint for data academies looks quite similar across organisations, which should reassure people on this call. The objectives are consistent, but there are many ways to tailor the approach.
[37:14] Kyle Winterbottom: Really interesting. I want to come back to the communication piece—specifically, how you get people into that space so it doesn’t just become a “tick the box” exercise where they take the course but carry on as they did before. But before I do, someone has raised a question about using the term "literacy."
Greg, I imagine you face this regularly. It reminds me of when I named our podcast Driven by Data and then had an influx of people saying they didn’t like the term "data-driven." I thought, well, that’s great—could have used that feedback before naming it! Anyway, I digress. What’s your opinion on this topic around terms like literacy or fluency?
[37:59] Greg Freeman: I do have an opinion, but not because I’m particularly tied to the name of our business. I’ll be clear: we’re totally adaptable to this. Hannah has a slightly different perspective than me, but as Kate mentioned earlier, we tailor our programmes to the organisation's needs.
We’ve run programmes under names like "Data Fluency," "Data Confidence," "Data Coach," and "Data Literacy." The key is that the people in rooms like this—data professionals and leaders—care about these distinctions. But frontline users and learners? They usually don’t care what it’s called. Most of them are probably thinking, “Oh no, someone’s here to talk about data—how do I escape this conversation?” They’re not overly concerned with whether the programme is called literacy, fluency, or something else.
We called our business "Data Literacy Academy" because that's the widely recognised term in this field—used by Gartner and others. But, as someone mentioned in their question, the comparison to learning a second language is apt. Most people don’t need to be fluent in data; they need just enough to use it effectively in their roles. If someone knew everything about data infrastructure, architecture, analysis, and engineering, they’d likely be a data professional, not a business professional.
Ultimately, the success of a programme doesn’t hinge on its name but on its quality. Call it literacy, fluency, confidence, or culture—what matters is the impact it delivers.
[39:50] Kyle Winterbottom: Mhmm. Yeah, it seems like this conversation is primarily internal to the data analytics community. When you speak to people outside of it, they’re usually not that bothered.
Kate, I want to circle back to the communication piece. Greg mentioned you have great people helping with this. Specifically, how do you avoid the trap of having your programme become just another intranet resource where people take a course and move on without changing behaviour? How do you communicate the benefits and drive behaviour change?
[40:47] Kate Jones: Working with our internal comms team has been invaluable. They help ensure our messages don’t get crowded out. For instance, when we launched our data apprenticeships, we timed it to coincide with National Apprenticeship Week to maximise visibility.
As much as I think I’m decent at communicating, I’m not a professional. The comms team takes what I write and adapts it into the tone and voice we use at Coventry Building Society, making it more accessible and engaging. I understand data and our strategy, but they’re the experts in delivering messages effectively.
On the topic of data literacy, we haven’t encountered significant resistance. Even with personas like "data skeptic," which you might think could deter people, we found that participants were proud of their persona and engaged with it.
[42:20] Kyle Winterbottom: Interesting. How do you define those personas—skeptic, dreamer, knight, wizard?
[42:32] Kate Jones: We used a survey with multiple-choice questions to identify personas. Here’s how we defined them:
- Data Skeptic: Someone uncomfortable with data or unsure how to use it in their role.
- Data Dreamer: Someone who sees the benefits of data but isn’t sure how to move forward.
- Data Knight: Someone confident in data activities but eager to learn more and upskill.
- Data Wizard: Someone with high data skills, comfortable across all aspects of data.
The survey was actually designed by our data graduates, which was a fantastic opportunity for them.
[43:40] Kyle Winterbottom: Very good. Hannah, how did you approach the comms piece to get the message out and drive attitude changes?
[43:52] Hannah Davies: When we started the academy, we quickly realised the importance of maintaining momentum. It’s not just about launching initiatives but keeping them alive while introducing new ones.
One of the first roles we added to the academy was a culture and engagement officer. We worked closely with our comms team, who helped us with things like managing the calendar, crafting the right messaging, and ensuring it aligned with Admiral’s tone. Often, as data professionals, we write messaging that makes sense to us but might not resonate with others.
We focused on small, frequent touchpoints—newsletters, updates on Viva Engage (our workplace platform), and sharing stories people cared about. Our Viva Engage space is one of the most engaged platforms in the company, which speaks to the community we’re building.
Branding was also key. Like how you recognise Google presentations by their design, we wanted our communications to be visually and thematically consistent. It helps build trust and familiarity with the academy.
Finally, we leaned on specialists where needed. I can write an essay, but I’m not great at designing infographics or creating event flyers. The comms team filled those gaps, allowing us to focus on what we do best. That’s been instrumental in building a phenomenal team that delivers great results.
[46:59] Kyle Winterbottom: The key message I’m hearing from both of you is that you provide the content, but the comms team shapes the message—how it looks, where it lands, and how it resonates. That’s critical and highlights the importance of having the right people in the right roles.
Greg, we’ve got another question for you. You mentioned that full-scale data literacy programmes work best for larger organisations. What’s your approach for smaller organisations?
[48:02] Greg Freeman: Like I mentioned earlier, it’s about adapting the approach. For smaller organisations, one-to-one coaching, small group sessions, and lunch-and-learn formats can work well. Initiatives like quarterly learning sessions are also effective.
These aren’t as large-scale or formal as what Kate and Hannah described, where senior execs champion the programme and L&D teams are heavily involved. For an SME, the scale and budget often don’t allow for that. But these smaller, more flexible methods can still be impactful and are often more cost-effective.
[49:06] Kyle Winterbottom: Nice. Let’s tackle another common question: ROI.
Kate, how are you measuring success? Are you being asked to demonstrate ROI, or is it more about reporting progress?
[49:40] Kate Jones: I haven’t been asked to demonstrate ROI directly, but I do update regularly on our progress. We measure success by tracking the number of participants completing programmes, evidence of them applying new skills, and tangible value from new data products.
We also track how the programme supports career growth. For example, I recently presented an update to our board about how our initiatives are enabling the data culture we want. It’s about showing progress rather than calculating a strict ROI figure.
[50:53] Kyle Winterbottom: Hannah, how about at Admiral? What does success look like for your data literacy programme?
[51:08] Hannah Davies: This is probably the question I always dread because measuring ROI in a people-change function is incredibly hard. A lot of the expectation is that we know we have to do this, and we know it’s going to set us up for the future. It’s less about a strict ROI number and more about what behaviors we’re changing and what we’re noticing.
All of Kate’s points resonate—those are things we replicate as well. It’s about understanding behaviors: are we seeing fewer requests into our data teams? More self-service? Reduced risk across our data landscape? Are projects being set up with data people involved from the start? Often, problems arise when data professionals are brought in too late.
We also look at engagement—are people actually participating, and is it making a tangible difference in their daily work? It’s not enough to have senior-level buy-in; if employees aren’t showing up or engaging, then you’ve got a problem.
Looking ahead, I think this will evolve as we think about future needs, such as digital fluency, AI fluency, and data fluency working hand-in-hand. We’re laying the groundwork now, but it’s definitely a juggling act, and I haven’t found the magic formula yet. If anyone has one, please share it in the comments!
Ultimately, it’s about defining the needle you want to move from the outset and measuring that. Trying to shoehorn a measurement in afterward just doesn’t work.
[53:08] Kyle Winterbottom: That’s fascinating. Measuring ROI for a data literacy programme is already a step removed because you’re tracking behavior changes that impact projects, which is even harder.
Greg, I imagine when you’re out speaking to potential customers, exec sponsors are asking these types of questions. How do you respond when they ask, “What do we get out of this?”
[53:41] Greg Freeman: Absolutely—it’s a common and fair question. The key is aligning measurements to strategic outcomes that matter to people outside of data. Are we identifying cost-saving opportunities? Growth initiatives?
To Kate’s point about tangible use cases, those are often the most compelling for businesses. I’ll share a perspective from Richard Baker at BAE Systems, who said something insightful: “Nobody necessarily speaks data, but everybody speaks pounds and pence.”
One example comes from a manufacturing client. Someone who didn’t see themselves as a "data person" identified an issue causing frequent and costly pauses on the manufacturing line. The problem wasn’t mechanical as they initially thought—it was a data issue upstream. Fixing it became a seven-figure win for the business.
When you can show use cases like that, it’s easier to secure buy-in for future initiatives. If you deliver 10 more of those over a few years, the ROI becomes undeniable.
Other metrics, like adoption of tools (Power BI, Tableau), are also helpful because they demonstrate engagement. But use cases tied to pounds and pence tend to resonate most.
One warning: if you’re surfacing use cases, you need a team to deliver on them. Nothing kills momentum faster than identifying problems without fixing them. Whether it’s an internal team or external consultants, you need a plan to act on those insights quickly.
[56:40] Kyle Winterbottom: So, the more literate your organisation becomes, the more use cases you uncover, which can directly impact the bottom line. Interesting.
Kate, let’s circle back to you. As your data culture matures, do you anticipate the way you measure success will evolve?
[59:32] Kate Jones: We’re still early in our journey, so our focus right now is on gathering data to show progress on the measures we initially set. But I’m sure those metrics will evolve over time as we move forward.
[1:00:03] Kyle Winterbottom: Greg, how do you see culture maturity impacting what gets measured?
[1:00:03] Greg Freeman: It’s definitely a journey. If you lead with ROI tied to pounds and pence, you avoid many tough questions. The key is picking the right metrics at the start. Show that a use case has delivered measurable value, and it becomes easier to maintain buy-in. When people see tangible results, they’re less likely to question the programme’s value.
[1:00:50] Kyle Winterbottom: Perfect. Right on time—4 PM. Thank you all for joining us today. I hope everyone tuning in found the conversation valuable and took something away from it. We look forward to welcoming you back soon.
[1:01:13] Greg Freeman: Thanks! See you soon.
[1:01:14] Hannah Davies: Bye!
[1:01:14] Kate Jones: Bye!
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