Why you need your analysts to be storytellers and how to develop them

I wonder how many of you value being a storyteller, as one of the most valuable skills in your analysts or data scientists. Do you?

Even writing that it seems a strange thing to say, almost an oxymoron for such quantitative roles. Surely you can’t expect these specialists to also master the humanities?

However, as I look back over the pieces of analysis which have driven most change in the businesses I’ve served, it is those which told the most compelling story that made the biggest difference.

The power of storytellers

This of course is not really surprising at all. Our researchers and all those with any social science background will tell us that storytelling is deeply embedded in human societies.  Over millennia we see examples of the most important truths for one generation to pass onto another being encoded in stories.

Even right up to the present day, the success of TV series which now rival movies for quality and acclaim, is often put down to one consistent writing team and a well crafted story. Plus we have surely all experienced the difference between a yawn inducing marathon of PowerPoint slides, and a clear engaging narrative which captures our attention.

So, how does this human trait relate to the hard-nosed business world of analytics to improve commercial results? From having seen some analysts develop real skills in this area, I will call out two ways storytelling improves analysis…

Benefit 1: Converging the evidence

The first benefit is the discipline of converging the multiple facts discovered during an analytical project/task into a few key points that can be communicated as one consistent narrative.

Of course appropriate methodologies for high quality analysis, like CRISP-DM or SEMMA (summarised well by Jess Hampton), do matter. However, the discipline of thinking in terms of pulling together what you find into a compelling “story” can help avoid distraction and going off on too may tangents.

The framework of a story reminds the analyst of the need to be clear about the challenge (business need/issue), the characters (what is happening for customers and colleagues), the tragedy (cost or risk of what is really happening) and the heroic triumph (how this can be overcome with clear next steps).

In fact, thinking in terms of a story can mean that on such a simple framework narrative can be hung those interesting little details you discover during thorough data analysis. If done skilfully, these enrich the story and bring the problem to life, rather than distracting from the point.

Benefit two: structured communication

The second benefit of storytelling skill comes more from the world of print journalism. Tabloid papers in particular are well skilled in hierarchies of communication.

Using the classic marketing theory of AIDA (Attention, Interest,  Desire & Action), levels of headlines, text and images are designed to draw in the reader to the key content.

Similarly, an analyst who can reduce weeks of analysis into one punchy headline, action-orientated sub-headings and an engaging executive summary is worth their weight in gold. I know this can see soul-destroying to some analysts (and even researchers), to see all the work they put into a 50 slide PowerPoint deck reduced down to one single slide with an effective visualisation.

However, try to encourage them to see this as a process of refinement. Doing this is not about discarding the detail, rather distilling or refining to a precious simplicity.

Are your analysts storytellers?

I could share more, but let’s leave it as just chapter one on this topic for now.

If you’d like to read more on storytelling in business, then I recommend this book review.

Please do share below your experience of storytelling through analysis and any tips you have for doing this well. Thanks.