On a late September evening, I joined Ortecha’s Data Culture Club at The Swan pub by the Globe Theatre – a fitting setting for a night dedicated entirely to storytelling. With the Thames just outside and Shakespeare’s playhouse next door, the backdrop couldn’t have been more appropriate. Stories have always been the way we make sense of complexity, and this evening reminded me why they’re just as essential in data culture today.
The event began with a fireside chat between Andy Cotgreave, data storytelling evangelist, and Suzanne Evans, storytelling consultant. What followed was a set of round tables exploring how to embed storytelling capability across teams and organisations. The focus was not on whether storytelling matters — that was taken as read – but how to build it into practice, scale, and culture.
Storytelling isn’t performance, it’s connection
One of the strongest messages of the evening was that storytelling is not about being loud, funny, or ‘entertaining’. Many people assume they’re not natural storytellers because they’re introverted or don’t see themselves as performers. But stories aren’t about performance. They’re about connection.
We all tell stories naturally with friends and family. Bringing that same authenticity into the workplace is what makes the difference. As one panellist put it: “You want to create a transformation in the people you’re telling the story to.” That transformation doesn’t require theatrics, only clarity and honesty.
The importance of listening
Good storytellers don’t just broadcast. They listen. One theme that came through strongly in the round tables was that ‘change professionals’ often focus on persuasion through facts and figures. But persuasion rarely lands that way. Change is far more likely when you listen, ask questions, and adapt.
That requires bravery. Listening means you might hear things that are uncomfortable. But as several participants pointed out, it’s when you surface what hasn’t worked that you can adapt, refine, and ultimately make change stick.
Exploratory vs explanatory
Another distinction I found useful was between exploratory storytelling and explanatory storytelling. Exploratory is about finding the story — digging into the data, asking questions, surfacing patterns. Explanatory is about telling the story — structuring it clearly, with a beginning, middle, and end, to help others act.
Too often, analysts stay in exploratory mode and then try to present their findings without reframing them for their audience. Explanatory storytelling requires stepping back and thinking: what does my audience need to know, and how do I take them there? The better we get at making that switch, the more impact our data work has.
The role of emotion
Leaders, in particular, often shy away from using emotion in business storytelling. They worry that highlighting jeopardy, setbacks, or customer frustrations might feel too risky. Yet emotion is precisely what makes a story memorable. Without it, data points fade. With it, they stick.
One of my favourite reminders of the evening was that storytelling helps people see themselves in the dataset. When we contextualise insights – “this is what it means for you, here’s where you sit in the story” – we turn abstract information into something personal and actionable.
Even governance needs stories
Not everything about data culture feels easy to ‘storytell’. Governance, for instance, is usually avoided in conversations like these. But one analogy shared really landed: governance is like the beach safety flags. When you swim between the flags, you don’t need to worry – safeguards are in place. Venture outside, and you risk drowning. It’s not about stifling action, but about creating safety so people can get on with what matters.
That simple analogy brought governance to life in a way that policy documents rarely do. It’s a good reminder that there’s always a way to frame data practices through story.
Practising the craft
A practical tip I loved: when presenting, try experimenting in just five minutes of your talk. Change your tone, structure, or framing in small ways. Over time, these experiments build confidence and help you find your own storytelling style. Storytelling is a skill like any other – built through practice, not innate talent.
Measuring culture through stories
Finally, the question of measuring data culture came up. Quantitative measures often fall short. Instead, qualitative signals – the stories people share, the small shifts in behaviour, the narratives circulating in corridors and team chats – may be the most powerful indicators of cultural change.
In a hybrid world, those small stories can be harder to surface. But they’re still there. Leaders and enablers need to pay attention to the unofficial narratives as much as the official ones, because they reveal how culture is really shifting.
Walking out of The Swan that evening, I was reminded that storytelling is not a ‘nice to have’ – it’s the bridge between data and action. It’s how we get past the adoption gap, how we make governance real, and how we embed data into culture in ways that stick.
Whether exploratory or explanatory, quiet or bold, every one of us has the capacity to tell stories that matter. And if we want our data culture efforts to succeed, we can’t afford not to.
The Data Front 
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