When you type “Data science is the new …” into Google, although the search engine doesn’t return “rock ‘n’ roll”, its top two suggestions are “oil” and “investment banking”, two of the most desirable, profit-making enterprises in the history of advanced capitalism. In 2012, a landmark article in the Harvard Business Review dubbed data science “the sexiest job of the 21st century”.

If data science is one of the keys that a business can use to unlock untapped potential of all the information that flows around modern organisations, it is data storytelling that enables them to move from “So what?” to “Now what?” and outflank the competition. Google offers up a single suggestion when you type “Data storytelling is the new …” and that’s “… language of corporations”. That’s a pretty single-minded response from the ever-evolving algorithm.

At the start of last year, the HBR published another important viewpoint on data science, updated with more of a focus on data storytelling. Scott Berinato’s article mapped out a smart approach for building a model team to span the talent requirements in this area, including: project management, data wrangling, data analysis, subject matter expertise, design, and storytelling. Despite rapid advances in organisations understanding the what and the how of the teams they need to build to make the most of data, Berinato’s article opens up with the memorable observation that: “Efforts fall short in the last mile, when it comes time to explain the stuff to decision makers.” Ah! The last mile problem. So long has it dogged us! It’s a topic addressed in depth in a new white paper on data storytelling from digital marketing sector association I-COM, produced by I-COM’s Data Storytelling Council (which I just happen to chair).

Last week, it was my pleasure to be one of three panellists on a webinar titled “Thrive & Survive”, run by the University of Sussex’s innovation centre. Our topic – very much a topic du jour, particularly for businesses looking for bouncebackability in the wake of coronavirus – was data storytelling. One of the other panellists – Australian AI and data visualisation guru, Darrell Berry of Significance Systems – posed a great rhetorical question that went something like this: “If you’re looking to recruit a good data storyteller, would you go for a recent graduate in data science, an astrophysicist, or a successful professional gambler?”

The answer – which Darrell immediately provided – may be counter-intuitive. Look straight past the data science graduate – even one with several years’ experience – and go for either the astrophysicist or the gambler. The reason is simple, and it’s all to do with the fact that they’re both able to detect incredibly weak signals among the huge quantities of confusing and distracting noise in their respective fields. If you can locate a black hole in the cacophonous maelstrom of space – if you can develop a way of beating the bank at Monte Carlo, reliably and sustainably – then the challenges of corporate data storytelling are likely to be a relative cakewalk.

I have every confidence that Nate Silver, the foxy founder of the 538 blog and author of the seminal 2013 book The Signal and the Noise would approve. With masters of black holes and blackjack on your side, you’re very much less like to founder in Scott Berinato’s last mile. You’re therefore also very much more likely to become an organisation much more adept at telling powerful and purposeful stories with data.