[00:12] Tolu Adebekun: Good afternoon, everyone. Thank you so much for joining us. We’re just going to wait a couple of minutes to let people join since, as we all know, everyone’s back-to-back these days—thanks to COVID—and meetings often overrun. Let’s give people a moment, and then we’ll get started.
[00:31] Katy Gooblar: Tolu, are you going to sing us a song while we wait? A bit of hold music, maybe?
[00:40] Tolu Adebekun: [Laughs] Give me a second—though I can assure you, you wouldn’t want that.
[01:06] Tolu Adebekun: Right, let’s just give it another minute. How are you both doing today?
[01:10] Helen Blaikie: Yes, good.
[01:14] Katy Gooblar: Same here. Though, as you mentioned, it’s all back-to-back-to-back, which is always fun.
[01:19] Tolu Adebekun: Exactly. Thank you, COVID, for creating this dynamic—it didn’t used to be like this, but here we are.
[01:30] Helen Blaikie: And in a lunchtime slot too.
[01:33] Tolu Adebekun: I know! Hopefully, people have brought their lunch along with them.
[01:44] Katy Gooblar: Unlike us.
[01:48] Tolu Adebekun: Right. Shall we get started?
[01:48] Katy Gooblar: Perfect. Let’s go.
[01:50] Tolu Adebekun: Welcome, everyone, to our LinkedIn Live session. We’ll introduce ourselves in just a moment, but first, a bit of housekeeping. We’d love to hear your questions. You should see a chat function available, so feel free to drop your questions in as we go along, and we’ll pick them up during the Q&A session at the end. Don’t be shy—there’s nothing we’re unwilling to discuss.
[02:23] Katy Gooblar: Just to clarify, Sarah, our aide working behind the scenes, is not imaginary. Thank you, Sarah!
[02:29] Tolu Adebekun: Thanks, Sarah. So, today we’re discussing how the education sector can become more data-driven and data-guided. I’m joined by Helen Blaikie, Chief Data and Analytics Officer at Aston University. Let’s start with introductions. Helen, over to you.
[02:45] Helen Blaikie: Thanks, Tolu. Hi, everyone. I’m Helen Blaikie, Chief Data and Analytics Officer at Aston University. I’ve been at Aston for about four years now, following a career spanning data, finance, and commercial roles across multiple sectors—from the tyre industry to oil, financial services, and retail.
[03:18] Katy Gooblar: I’ll go next. I’m Katy Gooblar, Director of Education and Data at the Data Literacy Academy. I had the privilege of being part of Helen’s journey with us as an educator on the programme we’ll discuss today. Before this, I worked in industry, most recently at the Royal College of Nursing as their first-generation CDO.
[03:47] Tolu Adebekun: Thanks, Katy. I’m Tolu Adebekun, a Senior Strategic Adviser at the Data Literacy Academy. My background is in commercial roles; I studied business but fell in love with data during a six-week analytics rotation as part of a graduate scheme at Sky. I spent over a decade there, eventually becoming Head of Data Visualisation, responsible for Tableau across the group. At Data Literacy Academy, we help large organisations transform through data literacy education programmes, which we’ll be exploring today.
[04:51] Tolu Adebekun: The objectives for today’s session are threefold: to recognise the importance of data in higher education, to share our proven approach for fostering a thriving data culture, and to explore actionable strategies for driving leadership buy-in as well as engagement across institutions. Helen, could you tell us more about Aston University?
[05:20] Helen Blaikie: Of course. Aston University is a medium-sized institution located in Birmingham, in the heart of England. We currently have around 18,000 students and 2,000 staff across both academic and professional services roles. While we focus on teaching, we’re also a research university, with a strong emphasis on social mobility and adding value for our students.
We’re proud of accolades like being named the Daily Mail University of the Year for Student Success and ranking second in England for social mobility. This is one of the reasons I joined the higher education sector—you can truly see the impact we’re making on communities and students.
[06:35] Helen Blaikie: However, like many universities, we face significant challenges. The government’s funding model for home students has been frozen at £9,250 per year since 2008, despite rising costs. International student visa fees and healthcare surcharges have also increased significantly, creating additional hurdles.
The sector is navigating evolving markets, particularly in countries like Nigeria, India, and China, which pose recruitment challenges. Additionally, like other industries, we struggle with talent recruitment and retention, particularly given the high competition for skilled professionals.
[08:47] Helen Blaikie: Recognising these challenges, Aston embarked on its 2030 strategy. This ambitious vision focuses on three themes: our students, our people, and our impact. Underpinning this is a robust performance measurement framework. We identified 54 key measures of success to track our progress and promote accountability across the organisation.
A critical realisation was that for this strategy to succeed, everyone needed to understand and feel confident using data—not just me. As I often say, data is a team sport. It’s not something one person can handle alone; it requires collaboration and shared responsibility across the institution.
[12:27] Katy Gooblar: Thanks, Helen. Your point about data being a team sport resonates strongly with me. One of the biggest challenges we see is bridging the communication gap between academic experts and operational data teams.
In higher education, this divide can be particularly stark. Academics, policymakers, and executives may lack the technical knowledge, while data and planning teams often don’t fully understand the academic perspective. Addressing this gap requires bringing everyone on the same journey and building mutual understanding.
[13:55] Katy Gooblar: Another issue we often encounter is what’s known as “learned fear.” People frequently avoid areas like maths or data because of past negative experiences. This fear can lead to disengagement, even in highly educated environments like universities.
For example, even individuals working with data daily may feel intimidated if they’re asked to discuss maths or statistics, fearing they’ll be “found out.” This mindset can be a real barrier, even within academic institutions. Would you agree, Helen?
[15:27] Helen Blaikie: Yes, definitely. I think it can sometimes be even worse in academia. Academics are highly intelligent and incredibly skilled in their fields, so it can feel harder for them to admit discomfort or lack of confidence in another area like data. It’s not necessarily anyone’s fault—many simply haven’t had the tools or access to data before, and you can only build confidence by practising regularly.
[16:05] Katy Gooblar: Absolutely. When we first started working with you, Helen, our focus was on narrowing the gap—bringing the two sides of knowledge closer together so that everyone could communicate in a shared language and work together to solve problems. That’s ultimately what it’s all about: making sure the investment in your strategy translates into real impact by ensuring everyone pulls in the same direction.
At the Data Literacy Academy, our purpose was to help you and your team bridge that gap effectively, creating a common foundation for collaboration and progress.
[16:51] Tolu Adebekun: A fun fact that no one asked for—my greatest fear is swimming! The first time I got into a pool, I sank straight to the bottom. In my panic, I grabbed onto someone’s shorts and accidentally pulled them down! For years, I convinced myself I couldn’t swim or float. It wasn’t until about two years ago that I finally learned how to swim in the ocean. Taught fear is so real, and it shows up in all kinds of areas, including data.
[17:22] Katy Gooblar: That’s quite the anecdote, Tolu—perhaps a little too much information! But I’ve seen firsthand that you’ve conquered that fear.
[17:33] Katy Gooblar: When it comes to taking people on this data literacy journey, what does it look like in practice? Often, organisations start at the top of the maturity curve, focusing on making their data professionals even more skilled and capable. While that’s important, it can inadvertently widen the gap between those who are already data-savvy and others who aren’t there yet.
[17:44] Katy Gooblar: If you don’t bring those outside the data team along on the journey, you end up with people who feel disconnected or unsure about how to engage with data. This creates challenges in adopting new technologies, embracing dashboards, or integrating data-driven ways of working.
[18:08] Katy Gooblar: At Aston, we committed to building a baseline that everyone in the organisation could access. The strategy was clear: every employee would have the opportunity to learn, upskill, and develop their data capabilities. This universal approach was both ambitious and exciting—it’s not something we often see on such a scale.
[19:11] Helen Blaikie: Absolutely, Katie. When we started this journey, data literacy at Aston existed, but it was siloed. Some people had access to data and others didn’t. Some had prior experience in data-focused environments, while others hadn’t encountered data as part of their roles.
Our goal was to create a common baseline—a shared language for everyone, from academics specialising in AI and analytics to operational staff. It was about putting data into context for Aston and making decisions using data a natural part of our processes, rather than something people found intimidating or challenging.
[20:28] Helen Blaikie: Initially, my idea was to “think big, start small.” I wanted to pilot this with a small, focused group—maybe a specific team. We had some great data products already, and my thought was to integrate training into their use, helping people build confidence as they worked.
[20:57] Katy Gooblar: But that’s not how it played out, is it?
[20:59] Helen Blaikie: No, it certainly didn’t! Our ambitious Vice-Chancellor liked what we were doing and insisted the entire senior leadership team participate. I went from planning a small proof-of-concept to delivering a programme for over 100 of our most senior leaders.
[21:28] Helen Blaikie: It was daunting, but it turned out to be the perfect move. These leaders were already using our strategic measures of success dashboard, so the training was timely and directly relevant. We also received valuable feedback from them, which helped refine the programme.
[21:58] Helen Blaikie: Additionally, involving senior leaders meant they could act as role models for their teams. They understand their teams better than anyone else and could advocate for the programme. One of our measures of success is to ensure every staff member at Aston is data-confident by 2030. To achieve that, we needed input from every level of the organisation.
[22:41] Katy Gooblar: That senior-level engagement was a game-changer. Some leaders openly admitted they needed this training, which created a culture of vulnerability and openness. It was a fantastic example of role-modelling, showing that it’s okay to learn and grow, no matter your position.
[23:01] Tolu Adebekun: That’s such an important point. Data literacy journeys are deeply personal. As Helen mentioned, there were pockets of data-literate individuals at Aston, but the overall levels weren’t uniform. Everyone starts from a different place, and it’s crucial to meet them where they are.
Katy, can you talk us through the behavioural personas and how they help tailor the journey for different individuals?
[23:28] Katy Gooblar: Certainly. One of the hidden gems we regularly discuss with clients—and which was especially beneficial at Aston—is the move away from job-based personas or role-aligned personas. Often, organisations group individuals by role and assume that everyone in the same role has the same data literacy needs. That simply doesn’t work in practice.
At Aston, for example, even within a cohort like senior leaders, you had people with vastly different personal journeys. Some were highly engaged and excited—professors and deans who might even teach data-related subjects. Others had never encountered dashboards in their discipline and had minimal interaction with data in their responsibilities.
We approached this by categorising people based on behaviours, relationships with data, and confidence levels, rather than job titles. This allowed us to tailor learning paths that suited each person’s starting point and professional needs. Not everyone needs to be at the highest level of data fluency; the goal is to bring them to a level where they can effectively do their jobs, work efficiently, and contribute to the strategy.
[25:11] For example, there’s often a large group, like what we call the “Toms,” who are new to data and just starting to engage with it. These individuals haven’t had exposure to data in their work and may even avoid conversations about it due to fear. In contrast, we also encounter personas like “Tolu,” who are already working independently with data, often in tools like Excel, but lack awareness of how their work fits into the broader organisational context or how to leverage advanced tools effectively.
[26:13] On the other end, we have data professionals who require less technical training but need more support in developing business acumen—understanding strategic challenges, communicating value, and engaging meaningfully with stakeholders. Addressing this broad spectrum is critical for narrowing the communication and knowledge gaps across the organisation.
[27:03] Tolu Adebekun: I think what’s particularly interesting about the “Tom” persona is that they often represent the silent majority. As data teams, we tend to focus on engaging with individuals like the “Tolus,” who are already active and visible. But the “Toms” are a massive group, and while they may not engage much initially, getting them on board can have a transformative impact across the organisation.
[28:01] Katy Gooblar: Exactly. The “Toms” are often hesitant to speak up, especially if they’re unsure about data. Removing that fear and building their confidence is essential. This is why change management is just as critical as education. It’s about unlocking people’s thinking, making the journey approachable, and helping them feel excited about data rather than intimidated by it.
[28:55] Tolu Adebekun: So, Helen, let’s delve into the beginning of Aston’s journey. How did you approach the initial stages, and how did you get early engagement from the organisation?
[29:13] Helen Blaikie: Rewinding a couple of years, the data literacy programme was just one part of our broader effort to create a data-driven culture at Aston. For us, being data-driven—or what I prefer to call “data-guided”—means using data to support informed decisions without losing the intuition and experience that leaders bring to the table.
To get started, we needed a foundation: tools, platforms, and governance. While I’m not a tech person—I can’t code—I knew we needed reliable systems for easy access to data. Equally important was ensuring the data was trusted and credible. Without that trust, even the best training would be undermined.
We adopted a phased approach, embedding data governance into each product we built. This incremental strategy allowed us to demonstrate value early on, build advocates, and continue expanding.
[31:23] Katy Gooblar: We aligned that approach with the education journey, tailoring content to Aston’s needs and ensuring each session built on the last. This context-driven method reinforced the strategic goals behind the training, making the sessions practical and relevant.
[31:51] Helen Blaikie: Exactly. Early on, we rejected the idea of traditional computer-based training—it’s disengaging, and completion rates are often low. Instead, we focused on live learning and active participation, combined with change management. Training equips people with skills, but it’s the change management process that shifts mindsets and behaviours.
[32:54] Katy Gooblar: The live learning sessions were particularly impactful. For the initial cohort of senior leaders, we set a tone of active engagement by starting with in-person sessions, which fostered open discussions. We also used follow-up actions, like lunch-and-learns and dashboard reviews, to sustain the momentum.
[35:08] Helen Blaikie: When deciding on who to involve initially, I focused on finding our “cheerleaders”—people who understood the strategic value of data and could act as early champions. We also targeted teams with compelling use cases, like Admissions, which is central to so many of our processes.
**[37:07] As we’ve moved to later cohorts, the requirements have shifted. Further into the organisation, there’s often less exposure to data and more “what’s in it for me” questions. Tailoring the messaging and continually linking it to strategic objectives has been critical in maintaining engagement.
[38:43] Tolu Adebekun: Thank you for sharing that, Helen. Let’s move to the practical side of change management. What specific measures did you put in place to support this transformation?
[39:58] Helen Blaikie: One of the most rewarding outcomes has been seeing leaders advocate for data themselves. At a recent away day, our Chief People Officer presented an HR analytics solution without any involvement from my team. Moments like that show we’re building a self-sustaining data culture.
[42:57] Tolu Adebekun: That’s fantastic. Any final thoughts or advice for those embarking on similar journeys?
[46:00] Helen Blaikie: Make sure your data strategy is tied directly to your business strategy. Start with foundational governance and tools, but don’t lose sight of the people element—building confidence and engagement is what drives lasting cultural change.
[38:44] Katy Gooblar:
So you touched there, Helen, and it got me thinking about two different points. When we talk about change management, people might not know what that actually looks like when we mention onboarding.
Part of that was creating high-value recorded content that could be integrated and used in different environments, but really having key influential people in the business buy into the purpose and why you’re doing it.
That’s hugely impactful to support any type of educational learning. We use it in our online hub, so people can access it asynchronously. If they miss a class, they can follow up or access customised use cases from within Aston.
Hearing your own team discussing challenges specific to your business adds so much more value than an off-the-shelf product.
[39:20] Katy Gooblar:
You touched earlier on the success measures. You mentioned the value it’s adding to key people on this journey. So what other success measures have you seen? I know you’ve got some great examples of people using things differently since the programme started.
[39:58] Helen Blaikie:
That’s a really important point, Katy. Understanding what good looks like and identifying success measures is critical.
We have a variety of measures, starting with adoption—who is using our dashboards and when. We even have dashboards to track dashboard usage, which is really helpful. We split that usage data by data literacy cohorts, so we can see how cohort one is using it compared to cohort two.
We’ve done some interesting things with that data because, of course, we should lead with data.
[40:31] Helen Blaikie:
Another key measure is how data is being used in decision-making. As part of our senior leadership strategy management system, we have quarterly reviews with our executive team, including the Vice Chancellor. During these reviews, we track progress against our measures of success.
The conversation in these meetings is now a lot more data-informed. When someone brings up a problem or a solution, it’s backed by data.
[41:20] Helen Blaikie:
One example I shared with you recently happened during our senior leadership away day. We hold these quarterly, along with town halls to communicate and celebrate success. For the first year, I was the one presenting about data at every event.
Now, I don’t need to do that anymore because others are championing it. On Monday, our Chief People Officer and her team gave a 15-minute demonstration of the HR analytics solution we built for them—not me, not the data team, but them. That’s what building a data culture looks like to me.
[42:25] Katy Gooblar:
Massive shoutout to the team at Aston for achieving that. That’s what success looks like.
[42:33] Helen Blaikie:
Absolutely. It’s something I always say—if I had a team of 100 people in my data team, I’d be doing something wrong. I need at least 100 people across the organisation who can do some of what my team does. That’s what democratising data is all about.
[42:57] Tolu Adebekun:
Absolutely. One thing I was wondering about, Helen, is what apprehensions you had going into this. I’m sure there are people listening now with similar concerns. How did you work through those apprehensions to get to such great outcomes?
[43:14] Helen Blaikie:
That’s an interesting question, Tolu.
[43:17] Tolu Adebekun:
Good interesting or bad interesting?
[43:20] Helen Blaikie:
Good interesting! So, I think one apprehension was around trying to be all things to all people with the course content and training materials. Ensuring we pitched it at the right level was a big concern.
We started with a strawman framework, didn’t we, Katy?
[43:46] Katy Gooblar:
Yeah.
[43:51] Helen Blaikie:
It’s fair to say it evolved significantly between cohorts one, two, and now three. Each cohort has shifted focus based on feedback and learnings. Working closely with you, Katy, and leveraging your industry experience ensured the content was applicable to Aston.
We tailored it effectively because of the similarities between a university and organisations like the Royal College of Nursing. That was key to overcoming those initial concerns.
[44:49] Katy Gooblar:
One thing I observed was the apprehension around getting it right. Helen, you were clear from the start that this wasn’t just about skills training. This was about aligning everything to the strategy—front and center.
We often talk about how a data strategy should be an enabler for the business strategy, and you were very strict about keeping that alignment. It was a bit different from what many organisations are used to, but it made all the difference.
[45:45] Helen Blaikie:
Absolutely. I’ve delivered data strategies across multiple organisations, and one thing I’ve learned is that it must be linked to the business strategy.
It’s all about finding that golden thread—ensuring everything ties back to the strategic goals. That’s how it truly lands and makes an impact.
[53:30] Tolu Adebekun:
Let’s go to Aidan’s question. Hey, Aidan.
[53:34] Tolu Adebekun:
“How did you address the different needs or diversity of data across differing departments in a large organisation?”
[53:42] Helen Blaikie:
Okay. I think that’s a challenge for many organisations, isn’t it?
We’re a very small team. When I started years ago, it was just me and a whiteboard. Now, we’re a team of seven, and I honestly don’t think we’ll grow much more. We deal with very diverse datasets.
[54:00] Helen Blaikie:
The way we manage this is through a hub-and-spoke operating model. My team acts as the centre of excellence, but we have spokes embedded in various functions. My team doesn’t own all the data—we’re not the experts on every dataset.
For example, we have research, HR, finance, and student spokes. These spokes are the experts within their specific areas, and we collaborate closely with them to identify strategic requirements for bringing data together.
[54:36] Helen Blaikie:
There’s also a prioritisation process, which could be an entire session on its own. We use two-by-two matrices to evaluate complexity and value, among other methods. This helps us decide where to start and where we can get the biggest bang for our buck. It’s all about having conversations and setting clear priorities with the executive team.
[55:17] Tolu Adebekun:
Yeah, love that. Thank you.
Katie, do you want to pick the next question?
[55:23] Katy Gooblar:
Sure. This one will resonate with a lot of people—it’s about data governance.
[55:28] Katy Gooblar:
The question is: “What were the major challenges in setting up the data governance (DG) framework and golden record data?”
I’ve got some thoughts from an educational perspective, having worked with your team, Helen, but would you like to start?
[55:51] Helen Blaikie:
Feel free to kick off, Katie.
[55:52] Katy Gooblar:
Okay. I’d say that Helen’s team, led by Kevin—big shout-out to Kevin—did a fantastic job of setting up the requirements and aligning services.
Part of what we discuss when it comes to data governance is the data value chain. This focuses on the people element—bringing individuals along the journey from data collection to data management.
[56:19] Katy Gooblar:
Often, people don’t realise their role in the chain. For example, someone inputting data at the start might not know how it’s being used downstream, and vice versa. That disconnect often leads to poor data quality or multiple versions of the truth.
What we’ve done at Aston is bring people together to have conversations in a shared language, so they understand their roles and feel heard. Kevin even implemented a sort of “data amnesty.” Instead of taking away their spreadsheets, he asked, “Just tell me what you’re using, why, and how.” This built trust and collaboration.
[57:31] Helen Blaikie:
Yes, definitely. What we didn’t want was a top-down governance framework. Yes, you need a framework, policies, and processes, and people need to understand their roles and responsibilities. But we also wanted to acknowledge what they’re already doing as part of their day jobs and align that with governance practices.
[57:55] Helen Blaikie:
For instance, we have data stewards and data owners, but the governance framework had to integrate with their existing work. If governance feels like an extra job, people won’t engage.
It’s still a challenge, though. Data governance is hard work. Sometimes you need both a carrot and a stick—audits can be particularly useful for getting things moving.
[58:57] Helen Blaikie:
We’ve also framed governance in a business context. For example, during a demo for our Deputy Vice Chancellor, they noticed an issue in the data—a school name that didn’t exist. That opened a conversation about data quality. When they realised it was someone on their team responsible for inputting that data, it clicked.
We added the issue to our data quality resolution log and educated them on the importance of accurate inputs. Showing the issues through outputs, rather than enforcing a “big programme,” made all the difference.
[59:49] Katy Gooblar:
The exciting part is creating a pipeline for people to get involved in governance. If they’re interested, we encourage them to join the community and explore roles like data steward or data owner, while providing opportunities to grow their skills. That’s the next phase we’re working on.
[1:00:14] Tolu Adebekun:
Amazing. We’re at time. Thank you, Helen and Katie, for joining and sharing your insights.
Thank you to everyone who joined and asked questions. If we didn’t get to yours, feel free to reach out to me or Katie—and Helen, if she’s okay with it!
[1:00:33] Helen Blaikie:
Absolutely. Please feel free to reach out.
[1:00:36] Tolu Adebekun:
Great. Thank you for spending your lunchtime with us. We’ll see you at the next live session.
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