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As part of our work on statistical leadership, we are hosting a series of guest blogs. This blog is from Robert Cuffe, Head of Statistics at the BBC.

It’s not all rush, rush, rush in news. One colleague, helping me with my transition from the months-away-deadlines of clinical research to the five-minute-deadlines of breaking news, revealed that when he worked on the evening TV news he had often had the luxury to go away and “just think about a story for ages, like, easily 15 minutes”. It didn’t help much.

Does it need to be so frenetic? And, if so, what does that mean for departments or statisticians trying to get their data covered broadly and correctly?

We can debate about five minutes versus fifteen, but the news machine does need to work very quickly. Editors are the last line of defence between everything that happened in the world recently and your news feed.

Every select committee, every ministerial pronouncement or opposition line, every report from a charity, think tank or government statistician, every freak goal from any team anywhere in the world, every man who bit a dog, every new collection, every sleb indiscretion and for quite some time almost every major number about the pandemic gets reviewed and someone has to decide “does this make”?

If it does, do we need to send a video crew to capture footage and interview bystanders, how quickly can we get 400 words up online to summarise this, who are good voices to put this into context, does the final script or writeup need to be run by the duty lawyer? And so on.

And, if not, what else can we put in the paper or in the bulletin? Because the program is happening at 6pm (or the print run starts at 7pm) whether or not we’re ready.

So decisions have to be made pretty quickly. And fast, good decisions about data need a prominent, clear and succinct summary of what the data can or can’t say.

As statisticians, we understand better than anyone else what the data can say. But our deep understanding of and intuition for the principles of our specialism do not always help with the prominent, simple summary. There are professionals who specialise in that translation: journalists or communications officers.

Here are some good guidelines given to me by an excellent journalist, who wanted me to help editors understand (in reverse order)

  • What are the caveats?
  • How prominently do we need to alert the reader/listener/viewer to them?
  • Can we run the story with this top line (or a different top line that the caveats don’t undermine)?

I’ve learnt to choose my caveats carefully: pushing hard on some and forgetting completely about others. Almost every number comes with a margin of error, but not every number story needs to include a confidence interval at the top. If the CI contains the null, why run the story? And if the bottom of the CI is miles away from the null, who cares that the truth could be a teeny bit higher or lower?

Equally, getting a key caveat, say “the time series jumps suddenly because the data definitions have changed” on page 28 won’t do when decisions or press releases are based on the executive summary.

So getting in the room for the painful discussion of final sign-off on a report or a press release, when much of the meeting feels like it’s about where the semi-colon goes, can be the most valuable contribution a statistician can make to the public understanding of their data. The day before the rush, there’s more time for discussion. Prepping the ground by explaining in advance to journalists or trusted intermediaries which questions the data can and can’t answer (rather than talking about specifically what answers the data contain) is also enormously valuable. Communication should be right first time. Statisticians can help make that happen.

PS –Delivering data during the pandemic is no mean feat. Trying out improvements to the service or data collection, as many have done, is remarkable. Thank you to all those producing statistics for all the work you have done in what has been an awful year for so many.