Which is Better? Chicken or Egg? Stories of data illiteracy

Today I had a conversation that forced me to think again about a subject on which I already had pretty strong views. For some time now, commentators, pundits, bloggers and other associated opinion providers have strongly espoused the idea that we need to make researchers and data scientists into story-tellers and consultants. How else could we ensure that the insights we generate from all the data with which we work really get through to our stakeholders and senior management – and result in action? How else are we going to have real business impact?

On a more sophisticated level, many of us have been arguing that insights departments are going to need a balance of talent in the team that includes methodological and technological specialists, polymaths who can synthesise data and connect the dots, and consultants who can take the story into the C-Suite. What’s more, that story needs to be short, comprehensible to the layman and impactful. As a one-time CMO of Meredith Publishing once put it, “the presentation should last ten minutes, the conversation should go on for hours”.

But what if we looked at the issue from the other end of the telescope? What if, in fact, at least part of the issue is “data illiteracy” on the part of stakeholders and management? Most of the people with whom we as researchers and analysts are dealing are what might be called “domain” experts. That is, they really know the business or, more usually, a part of the business. They may be category specialists (e.g. gum in a confectionary manufacturer) or marketing gurus or sales whizzes. They may be really good at what they do – but they are not data scientists nor are some really data “literate”.

This was the argument put to me by an executive in the pharmaceutical industry – and he was really worried by this gap in executive knowledge. In pharma, he explained, the data are so complex and changing so fast, if you don’t have a good grip on them you won’t make the right decisions.

Lost in mistranslation

In essence, what he was saying was that data scientists / researchers and their stakeholders are speaking two different languages and, even if you are a great story-teller, the risk of your being mistranslated remains high. If you then overlay on this the ubiquity and ease of obtaining data – even through primary research using DIY platforms – the potential consequences of illiteracy become lethal.

This gentleman’s solution was to run executive courses for domain experts in basic data science, the aim being that they would be put back into the world with certified skills where at least they could “get by” in data-driven conversations and understand the means by which stories were being constructed. While at present this would equate to throwing starfish back into the sea one at a time, eventually it perhaps could become a necessary qualification to enable people to hold decision-making positions in major organisations. Maybe it could even become a staple of business courses and business school curricula beyond the cursory attention that it receives in so many seats of learning today.

Inevitably, of course, this becomes not a conversation about chicken or egg, but one about chicken and egg. We need both story-telling, synthesis and consulting skills among the insights functions and a modicum of data literacy among domain experts and in senior management. If major companies really are going to walk the talk of being customer-centric and data-led, then all of this is necessary.

I look forward to the day when executive data literacy courses are de rigeur for aspiring managers – and even more so to the time when all business graduates, at whatever level, emerge from college literate in the data sciences.