Interview with highlights from when I was Data Editor of The Times and Sunday Times and how I got there.
Hailing from a tiny Californian town, where the main mode of transport takes the literal measurement of horse power, Megan Lucero is quite the outlier. The energetic 27-year-old – who was remarkably promoted from intern to data editor at The Times and The Sunday Times in just four years – would certainly stand out if you found her in a spreadsheet. At their shimmering Thames-side offices, Lucero talked to Peter Yeung about the importance of open data, the inherent plurality in data teams, and how her paper was the only one to correctly reject the polling data about the UK’s 2015 General Election.
Can you talk about your rise through the ranks at The Times?
I was interning for a week on the foreign desk, and I was just finishing up my MA in International Journalism at City University. It was my first time in a massive newsroom, which is funny to look back on now. Towards the end of that, I started taking a lot more on for the desk, and suggesting a lot more we could be doing digitally. I was very fortunate that at the time Richard Beeston – who unfortunately passed away a couple of years ago – was very on board with this and gave me a lot of free reign to do that. But at the end of that, they were cutting researchers and my job came up for the axe. I went up to the editor and deputy editor at the time, James Harding and Keith Blackmore, and I pitched a job to them, which we later called a “story producer”. I invented the job and they said: “Let’s see what you can do”. It was a one-woman show for a year. I taught myself a bit of coding, built some interactives, I started our first Soundcloud account doing podcasts, I was running live-blogs and finding stories online. But another review came up. They asked me to apply as a data journalist, and at the time I didn’t feel qualified by any means. But once I took on the role, I wanted to own what data journalism meant, so I just started teaching myself. I was trying to learn as fast as I possibly could because I saw this as a massive opportunity – the future of journalism. After a while, I basically running the team, so I became data editor.
What role will data journalism play in future newsrooms?
One day data journalism won’t be data journalism – it’s just going to be journalism. This sexy term that everybody throws around will disappear. Every single journalist should and will be digging into all of the digitisation and data around their beat, finding their own exclusives. I think there will always be a specialised team that will need to help with really advanced machine learning, perhaps algorithms that look at modelling, but I really think that data journalism as we know it now won’t exist.
Do you ever need to convince others about the value of data journalism?
I’ve worked pretty hard to make sure that other journalists understand the value of it. We had a front page exclusive out about charities’ expenses recently, and every journalist knew exactly that the story was a combination of a data journalism approach and an investigative approach. Everyone recognises the value of data, but it’s a matter of whether they’d be equipped to do it themselves. Sure, there is a gap with what other journalists can currently do, but they still recognise that data is important and valuable.
Does the paywall affect The Times‘ approach to data journalism?
If there was a paywall, or there wasn’t, we would be approaching it as we do. If anything, there’s much more of an argument for what we do at The Times, because our business model is that we produce news worth paying for. You’re trying to give your audience and your reader something exclusive, something they can’t get anywhere else, something that is worth subscriptions. A lot of people are willing to pay to support foreign correspondents around the world, advanced sports coverage, access to premiere clips. And I think that there’s a value in someone who’s looking out for accountability in public interest reporting, by advancing data manipulation and data analysis. I think every journalist should be thinking about how they can tell the full picture, looking at all of the information available. If you shut the door on data journalism, or limit yourself on how to access data, you’re really limiting the depth of what your story can tell.
Are there ever clashes between the editorial stances of a paper and what the data says?
I think your question doesn’t even necessarily need to apply to journalism. If you look at academics, if you look at anyone who analyses data, they can tell you that it’s possible to torture a data set to tell you whatever you want it to say. You’ll read one study that says drinking red wine helps you, you’ll read another that says it will kill you. This is because people twist numbers and they will twist it to tell you want they want. But I think we’ve never been pressured to deliver a certain angle, or to intentionally twist the data.The great thing about having a data team is that you’re not relying solely on a single individual – a team requires, for us, a peer review. Each of us check each other’s processes, we really do make a moral and ethical decision whenever we’re looking at it. We try to be open and challenge each other if we find ourselves if we going down a certain angle, or not doing something as robust as it should be. The classic example is how we treated the 2015 General Election – we rejected the polling data that was in front of us – no other paper did that. It wasn’t robust, the margins were too wide, the data was skewed. That couldn’t have happened if it was just individual people going after a story.
What is more valuable, open data or freedom of information?
If there was truly open data, you wouldn’t need FOIs. If truly every government body and every organisation that is public, opened their data, you wouldn’t need to do that to begin with. The fact that FOI is under threat is a travesty, and it’s absolutely unacceptable, because this is an affront to a public service. This is a right being taken away from citizens. But if you look at the source of the problem, it is that the data isn’t open. It’s the fact that public information should be easily accessible and it should be able to be accessed. My argument would be that open data is more important, because it is the bigger picture that encompasses FOI issues. But, of course, I wouldn’t say that FOI doesn’t matter – it matters a lot. It was created because of the lack of transparency and the lack of openness. But hopefully we can get to a space where that won’t really be necessary.
Is it difficult working for both The Times and The Sunday Times, which are competing papers?
We’re the only editorial team that does this. There’s no one else who has a data team that works across two titles. It’s kind of like contracting, in that sense, but it doesn’t feel like that here, it definitely feels like two separate titles. We’re quite lucky that there’s very different focusses on what we do for each title – what we can bring to them. But at times, there’s obviously data that both titles will want, and it would be quite silly to replicate our work. But I think we’ve been finding a good balance in how we share that. Luckily, the way that data journalism works across the board is that it’s quite an open space and an open community – The Guardian, The FT – I know the editorial teams across the board here. Most of all try to open up our data. If I did something for The Times, it would be quite natural for us to open up our FOI requests and the data on that story. That’s what is quite unique about the data community. But it is challenging.
What do you want The Times data team be known for?
I’d love to expand my team even more as I get more resources, and as that’s allocated to us. Basically: I want our team to continually be breaking really great stories, and we want to be doing it in a way in which you couldn’t be doing without computing. Our team is really is brought in to be an investigative team, and we find our best use is when we are doing advanced algorithms, machine learning, modelling – when we’re handling big data, doing things that a human really couldn’t do without computing. That what I want to be known for. We’re still kind of working in an area in which we’re doing some journalism that other journalists could do, so I’d like it to really move further along that line. Doping is one of the biggest examples, but obviously we’ve done a lot of stuff on charity finances, on footballers’ accounts. I’d like to continue that, and I’d like us to get more into visualisation – our team doesn’t do enough due to resources – and I want to focus on stories. But also I’d like to help contribute to the data community and to this paper about creating those journalists that are empowered to be data journalists themselves.
This interview has been edited for clarity and brevity.