Tennis recently joined the growing league of sports that are (allegedly) riddled with corruption. Whether any tennis players are actually at fault remains to be seen. However, the investigation by Buzzfeed and the BBC was notable for serving up some tasty data science. Buzzfeed’s John Templon wrote algorithms that mined betting data to identify unusual patterns and possible fixes. This could be a game-changer for PRs for a few reasons.
Buzzfeed has cemented its place as a new media publication with a penchant for serious journalism. If you or your clients still consider Buzzfeed and its ilk as the purveyors of clickbait and ‘listicles’ (horrible term), you’re far behind the curve.
It’s no secret that fewer and fewer journalists are being asked to write more and more copy. Only the most short-sighted PR would say this is a good thing. Press releases and comments may get less scrutiny and more column inches from time-pressed journalists, however, the scope to pitch more complex stories or research, contribute to long tail features or investigatory series is greatly reduced. So too is the amount of patience journalists can afford a PR desperately trying to ascertain and explain the facts during a ‘crisis comms’ situation.
More data science driven reporting could resuscitate investigatory journalism by creating a very powerful and fast research tool. Using algorithms and other techniques to quickly analyse huge tranches of data can uncover hidden trends, such as corruption, and create more interesting story angles. It can also be used for fact-checking and better statistical stories. Potentially spelling the end of ‘50% of people get tails on first coin flip’-style God-awful ‘research’ stories.
In short, more journalists could write better, well-researched stories, faster.
For PR professionals this is a challenge and an opportunity. First, it may mean less blasé use of statistics – which is a good thing. Second, as journalists become more data savvy, it opens the door to contributing information beyond straight-forward comments or ready-made reports to a story. Try pitching a data set for a journalist to analyse? Third, it could free up more time for journalists. This may mean that more pitches are assessed on content rather than the order they appear in a reporter’s inbox. Fourth, it may mean PRs have to generally raise their game. It’s harder to hide a company’s bad practice or communications ‘spin’ if a reporter, aided by data scientists, can examine open data to verify claims.
Of course, this scenario is still a way off. Buzzfeed’s investigation took over a year, not exactly speedy. There are also only a handful of journalists with the required knowledge of data analysis to properly scrutinise and use findings obtained by data science. It’s easy to make the facts and figures fit the story, rather than the other way round. However, this is going to change. Data is growing in power and reach, as are the tools to understand it. It is a window to our digital world and the only way to fully understand how people and organisations operate. Journalism in the next decade will become data science driven and PRs should embrace the opportunities this offers.