Who will win the next election? How many people really have long Covid? Which age group has the most money? Is our welfare system fair? In these fractured and polarised times, responsible use of data can help us cut through political spin and give balanced, considered answers to questions like these.
I’ve been in data journalism for nearly seven years, and I’ve loved seeing it grow from a niche expertise on the periphery of the newsroom to one of journalism’s most important skills.
I started my career at Which? magazine and BBC News. Now, as Data Editor at The Times and The Sunday Times, I co-manage a team of journalists covering everything from daily charts to bespoke interactive projects. I also write weekly data features for the Sunday paper, some of which I’ve submitted below.
Like most journalists, 2020 and 2021 were largely spent researching, visualising and writing about Covid, yet I am a generalist at heart: last year I was lucky enough to write about everything from intra-age wealth inequality to the threat foreign states pose to our network of undersea cables. Whatever the topic, succinct use of data can provide our readers with insight, context and balance. Our efforts are rewarded: our data-led pieces are often the most well-engaged with each week.
The late Sir Harold Evans, editor of the Sunday Times, said of his journalism, “all I tried to do… was to shed a little light.” The skills may have changed, but the aim remains the same: data shines a spotlight on the world by revealing patterns that some would rather be kept hidden.
My team and I are lucky to have the backing of some of Fleet Street’s best editors – many of them who have been in journalism for decades – who have helped data journalism at The Times and The Sunday Times to flourish.
Description of portfolio:
Each of these data-led features do slightly different things, which hopefully speaks to many of the different ways that data journalism is integral to the modern newsroom.
One way is holding the powerful to account. When the then home secretary said that too many people were on benefits when they could be working, I wrote a data-led feature showing how more than 40 per cent of those on benefits were actually in-work; pay in Britain, at the lower end, is simply too low to live without support.
Another use of data journalism is explaining difficult concepts. Using vaccine efficacy data from various sources, I used data on deaths to reverse-engineer a model for how many people could have died if Covid vaccines had not been discovered and we had behaved as we did. The results showed that more than 200,000 extra people could have been killed.
Data journalism can be a powerful weapon in calling our inaccuracies. When a misleading claim circulated on social media that just 17,000 people in Britain had died of Covid, I used data to robustly refute the misleading claims – but also explain the challenges of counting Covid deaths to begin with. There are some things that data cannot measure accurately.
Data can also harness the power of visualisation to teach readers something new. When the Nord Stream pipeline was mysteriously severed, attention turned to whether foreign states could sabotage Britain’s network of undersea cables and pipelines. Working with three other members of the team, we produced a map-based scrollable interactive to explore the UK’s subterranean threats.
Data journalism is about the reader – quite literally, in this case. Teaming up with our developer Michael Keith, we built an inflation calculator where the reader could enter their own personal situation – whether they drove, drank alcohol, had children – and get an approximate personalised inflation rate.
And finally, it can also answer challenging questions. Whether about the state of our health system – my feature on GPs made the front of the Sunday Times last Summer – or the nature of modern politics, data gives us the tools to keep tabs on the seismic shifts that have happened to our society over the past three years.