Your Data Storytelling needs less data and more stories (part 1 of 2)

Building on the previous content that we have shared on data visualisation, let’s focus on the storytelling aspect. Within my 9-step model of Softer Skills needed by analysts, step 8 is visual storytelling. This includes both effective data visualisation & storytelling skills.

Although there is plenty of content shared on generic storytelling by leaders, for analysts or data leaders the focus tends to be on technical data viz. So, I’m glad to make the data storytelling skill our topic for a few blog posts shared here. Starting with one from a very experienced analytics leader.

Guest blogger Martin Squires has created & led effective analytics teams for businesses as diverse as Boots, M&S & Homeserve. He is now Director of Advanced Analytics for Pets at Home. Readers may recall that Martin has shared with us before on topics including Business Partners and the tools an analyst needs. So, over to Martin to kick us off on thinking about data storytelling with this two-part series…

We’ve know the need of visual storytelling skills for decades

The Last Great Time War between the Time Lords and the Daleks “for the sake of all creation” lasted for at least 400 years. Fought throughout countless alternate timelines you can easily argue it more accurately lasted an eternity. Both sides fought across space and time, opening up new fronts as the Daleks invaded different epochs. This means it lasted slightly less time than the debate on what skills do you need to be a good data scientist and how do you find and train the (mythical) data science unicorn.

Although the war still rages there does seem to be a few areas of consensus and one is that data storytelling is definitely important. William Eisner described a story as “a vehicle for conveying information in an easily absorbed manner“. Surely data storytelling is a skill that every good analyst should master.

This shouldn’t really be a big surprise. After all the idea has been around for a while. It’s over twenty years since cartographer Mark Monmonier wrote a book called “How To Lie With Maps”. In it, he argued that “any educated adult should possess a good level of not just literacy and articulacy but also numeracy and graphicacy”. It wasn’t even that it was a new concept twenty years ago either. William G.V. Balchin had previously presented something very similar at the 1972 Geographical Association Conference: “If literacy is the ability to read and write, articulacy is the ability to speak well and numeracy the ability to manipulate numerical evidence, then graphicacy is the ability to interpret visuals”.

So, we’d expect lots of resources on how to master this skill

Monmonier and Balchin made the point that the ability to understand and interpret data visualisations was going to be vital long before the concept of “fake news” hit the headlines. Rightly predicting that this would form an essential skill for everyone in the workplace. Spin that coin around though and it’s easy to see that this also means analysts need to ensure they have the requisite literacy and articulacy skills in their toolkit. They can’t just rely on their numeracy and graphicacy strong suits. 

You’d think if we’ve known that this stuff is really, really important for that long we’d have found a great way to do it by now. Maybe. But try to find great training & development materials and it doesn’t always feel that way.

Yes, there is some great stuff out there. I’d happily recommend reading Cole Nussbaumer Knaflic and Alberto Cairo in particular. But a quick search on the internet and you’ll find far more technical courses on the mechanics of how to use different visualisations and data analysis tools. Much less on storytelling itself. For example, it’s easier to find how to build an immersive GeoBubble map with Plotly, or how to choose a Python plotting library. As a slight aside, there’s also a massive amount of stuff on how to write better Powerpoint presentations. But none of them seems to ask the question upfront “why are you doing this in Powerpoint in the first place”?

Knowing all the notes doesn’t mean you can write great songs. 

I’m drawn back to quoting Will Eisner again but feel I may need a little exposition here. For anyone not into comic books/graphic novels, Eisner was one of the pioneers. The Eisner Awards, given for creative achievement in American comic books, are often referred to as the comics industry’s equivalent of the Oscars. Interestingly, he also taught graphic storytelling at the School of Visual Arts in New York. In his book “Graphic Storytelling & Visual Narrative” he talked about how advances in technology had in some ways made storytelling in graphic novels easier. But warned these were often used as a crutch, so could get in the way of actually delivering a great story. 

“The result is often a preoccupation with graphic elements. Page layout, high impact effects, startling rendering techniques and mind-blowing colour can monopolise the creator’s attention. The effect of this is that the writer/artist is deflected from the discipline of storytelling construction and become absorbed in a packaging effort. The graphics then control the writing and the product descends into little more than literary junk food.”

“Graphic Storytelling & Visual Narrative” by Will Eisner

If you’ve ever spent time looking at very flashy BI dashboards and been left confused you see what he means. Eisner’s critique has clear parallels in the data storytelling and visualisation world.

So, what is the answer? Find out in the next thrilling instalment of…

What if we take our lessons in how to tell great stories from great storytellers instead? Rather than expecting to find the answers in technical manuals or graphic designers. In part two of this series, I will share examples of the art of the possible in storytelling. I’ll draw on examples from two TV shows with expert writers behind their success, South Park and Game of Thrones.

Thanks to Martin for sharing his challenge. From my own experience in training analysts in the people skills that they need, I agree with his diagnosis. Above and beyond my successful Data Visualisation training course, analysts need to master narrative skills. It is a separate but complementary skill with much to learn from novels, TV & films.

So, I’m looking forward to sharing part two with our readers soon. In the meantime, do you have any greater examples of effective data storytelling? If you or your team have mastered this narrative skill, what has helped you? I look forward to hearing & sharing the stories of your success or lessons learnt in your quest.