How to build a transformative Data Academy

When launching a data academy, it's easy to focus on the technical aspects like spreadsheet formulas or dashboard navigation. This ignores the reality that a lot of people are still scared of data and don't yet understand its value.

Phil Boon, interim Chief Data Officer and Head of Digital and Kate Jones, Head of Data Product and Strategy from Coventry Building Society have gained hard-won experience how to build an academy that drives business outcomes (and even won an award!). Their academy doesn't just train people on tools. It transformed an entire organisation's relationship with data, creating confident, curious teams that actually use what they learn.

In just over a year, they've launched seven different academies, with their Data Academy leading the charge. Here's their proven playbook for success.

Why most organisations get data training wrong

Here's where most companies go wrong: they start with advanced analytics and complex tools, forgetting that 80% of their people have never confidently asked a data question in their lives.

Organisations often skip the basics, missing the 80% who are starting from scratch. Coventry did the opposite. They met people where they actually were.

Phil experienced this fear firsthand as a stakeholder: "People shy away from data when they're not confident. That nervousness drove me to move to the data office. The academy fixed this gap."

When Kate joined Coventry in September 2023, she recognised the challenging situation they were in. She saw there was a strong desire to work with data, but low ability to do so effectively. They lacked platforms, skills, and confidence.

Most leaders would wait for better conditions. Kate and Phil used this chaos as fuel.

Creating curiosity before capability

The first challenge wasn't technical. It was cultural. How do you create curiosity about data in an organisation where people feel nervous about asking the wrong questions?

Kate's approach was collaborative from day one: "Data Literacy Academy ran a session with our data leadership and key stakeholders to co-design a plan. We worked with internal partners like communications and L&D to plan launch comms and engagement."

They knew that building momentum and creating demand were key to a successful programme deployment.

How to select your first cohort

The next step might seem counterintuitive to some, but Coventry didn't handpick their most data-savvy people for the first cohort. They invited everyone.

"Everyone wanted their teams involved," Kate explains. "We used persona surveys to identify data skeptics, dreamers, knights, and wizards, then tailored learning for each type."

They used proportional representation based on team size. Every department got spots. This meant they could build influence networks across the entire organisation, not just within data-friendly teams.

How to sell an 8-month programme to busy executives

An 8-month Academy programme is a massive investment of time and money. Getting leadership buy-in required more than enthusiasm.

Kate and her team highlighted three pain points executives already felt:

• Operational inefficiencies caused by poor data use
• Trust issues with existing data
• Missed opportunities for innovation

The pitch was simple: "If you want transformation, nominate your teams."

The results proved the strategy worked. The Data Academy was their first. They now run seven different academies covering software engineering, UX/UI, and other future skills.

Your secret weapon: Partner with L&D early

While data teams understand data, they've not been in the L&D world for years so miss out on key tricks to make learning stick. For Learning and Development, that's their whole reason of being. They understand learner engagement, cohort management, and measuring outcomes.

"L&D brought valuable expertise that we simply didn't have," Kate notes. "We've had strong engagement rates thanks to their support."

This partnership also helped them offer the right intervention for each person. Some people needed the full Academy. Others suited data apprenticeships better.

The perfect conditions don't exist

We hear this all the time: "we need to wait until we deploy Tool X or have right Team Z."

But we know from experience that there's never a perfect time, and so did Coventry Building Society.

Phil cuts through the excuses: "You can sideline these programmes forever or make token efforts. Strategic change requires commitment. There's never a perfect time."

Kate agrees: "Waiting for perfect data tools delays action you need today. Starting creates momentum."

So what happens when you want to launch data training, but your infrastructure is still a mess. How do you train people on tools that are still in development?

Kate's approach focuses on managing expectations upfront: "We told people exactly what was and wasn't available. Even without perfect data, they could still improve their skills in data quality, governance, and communication."

Phil adds: "Sometimes you have to say no, but with complete transparency. We've streamlined our roadmap to build strong foundations first."

This honesty builds trust rather than destroying it. People appreciate knowing the current limitations when they're investing time in development.

Trust and Governance: Build this foundation first

Making data a principal risk category created urgency at Coventry Building Society. Kate explains: "Training is the carrot, but managing risk is the stick."

They implemented Informatica for data governance and formed a steward and owner network focused on governance and risk.

"We trained stewards and owners under the Academy umbrella," Kate notes. "Training clarifies expectations. We also cover governance and quality in Academy training. You can't do advanced analytics if you don't trust your data."

Phil emphasises the human element: "Stewards and owners wear multiple hats. They need crystal-clear expectations. When people are unclear, they avoid responsibility."

How to evolve your Academy based on real results

Coventry Building Society's academy changed dramatically after the first cohort. Instead of broad representation, they now target specific departments.

"In the second cohort, we focused on Commercial and Risk teams rather than having everyone represented," Kate explains.

Why the shift? "As people's data skills improve, demand on the Data Office increases. That's a great problem to have, but still a challenge."

Their 2025 strategy focuses on strategic delivery. They won't train people unless they can deliver solutions that add genuine value.

Align training with what people can actually use

The move toward targeted cohorts came from their data roadmap. "We identify key data products and common datasets coming online. From that, we can see who will be primary users and who needs training most."

This alignment means training has immediate practical application. Kate puts it simply: "To embed learning, people need to put it into practice immediately."

Kate explains their roadmap approach:

• Business-led projects (driven outside the data office)
• Platform investments like Informatica and Azure
• Strategic culture-shifting initiatives

"The roadmap changes constantly, but stays rooted in value and built to adapt."

Phil adds: "We use a staged approach like our digital roadmap: solid foundations, then scale, then future readiness. You can't automate if the data isn't trusted or governed."

What actually makes Data Academies work

Based on Coventry Building Society's experience, here are the elements that separate successful academies from failed training programmes:

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Culture First, tools second: Build curiosity and confidence before diving into technical capabilities. People need psychological safety to ask data questions.

Partner with L&D from day one: Learning professionals understand engagement, cohort management, and measuring outcomes. Data teams typically don't.

Show leaders clear value: Don't just ask for support. Show executives how the academy solves specific business problems they already recognise.

Create networks, not just skills: Use your academy to build steward and owner networks that drive cultural change throughout the organization.

Match training to delivery capacity: Align your training roadmap with your data delivery roadmap so people can immediately apply what they learn.

Be brutally honest about limitations: Transparency about current gaps in tooling or data builds trust and manages expectations effectively.

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Phil's advice cuts to the core: "Be curious. Start small, test and learn. Build relationships and ask questions."

Kate adds: "Step into the unknown. If something scares you, that's probably worth doing. Every organisation should improve it's team's data skills. Start where the impact matters most."

For those just beginning, both leaders stress simplicity. Phil explains: "If you understand something, you should explain it simply to someone else. Start small and build curiosity. Technical depth comes later."

Progress beats perfection

Building a successful data academy requires abandoning perfectionism. You don't need flawless data or the latest tools. You need to meet people where they are, build confidence alongside capability, and create cultural foundations for long-term success.

Coventry Building Society's approach proves that with the right strategy, partnerships, and commitment, you can transform how people think about data. The result goes beyond better dashboards or cleaner spreadsheets. You create a more curious, confident, and genuinely data-driven organisation.