The three key elements of data storytelling

In life, stories help us make experiences more meaningful. If delivered in an engaging way, they can also inspire us to take action. Stories provoke reflection and contemplation, often bringing out insights that may not have been easily understood or explained.

Storytelling, however, may be avoided by your data analysts; perhaps they believe it’s less important than the data, or an unnecessary or uncomfortable task.

Did you know, however, that many analysts acknowledge that data insights are integral to their business’ long-term strategy according to Survey Gizmo? But almost half say they are only sometimes able to communicate these data findings to their key stakeholders.

The more digestible and engaging your analysts’ data ‘story’, the more their audience will value it. When data is coupled with narrative, it explains what’s happening and why. It can lead business stakeholders to valuable conclusions, and elevates the value of your team within the business.

“To tell a story, you have to be able to aggregate and assimilate a lot of different types of data.”
Jeffrey Belanger, Lead HR Business Partner and Head of Organizational Performance, Pandora.

 So, aside from data science that underpins all data analyses, what are the three key elements of data storytelling?

1. Storyboarding

Firstly, when your analysts start planning their data story, storyboarding should be an essential part of the process. It follows the principle of a flowchart; mapping out the direction and flow that data insights will follow, from start to conclusion.

Approaching data in this way forces your analysts to think about it creatively. It helps them identify how insights should best be presented to guide their audience to a meaningful and valuable conclusion.

2. Data visualisation

Next, you want your analysts to share their data insights to the wider business. In a raw format, however, these can be visually indigestible.

Data visualisation is at the heart of data analytics, it is the representation of data in a pictorial or graphical format. Data visualisation gives stakeholders the ability to use information intuitively, without deep technical expertise.

As viewers, our eyes are drawn to colours, patterns and shapes. Transforming analyses into graphs, charts and graphics, therefore, allows your analysts’ audience to access this information, and see it in context.

Data visualisation alone, however, also has limitations. It requires context to explain why and how conclusions are drawn. This is why the third element of data storytelling exists.

3. Data narrative

Arguably, the most essential part of data storytelling is the commentary that accompanies it—the story itself. It is a key vehicle to convey meaningful insights, with visualisations and data being the ‘proof’.

By blending narrative and visuals, analysts can target both sides of their audience’s brains, cementing the information. The best way for your analysts to start this process is with a storyboard, outlining their objectives and goals.

Ideally, analysts should aim to only include elements that contribute to the message, keep to one point per slide and ensure that there is a logical progression from one slide to the next.

Unfortunately, the visualisation and narrative elements of data storytelling can be daunting for your data analysts. They may require additional soft skills that do not always come naturally to such technical experts. But, if your team members prefer to stay out of sight, they may be missing the opportunity to contribute more value to the business.

Storytelling with Data by Demarq Academy is a workshop that encourages data analysts to develop their soft skill set. They will learn to carefully consider their data visualisations and narratives. Skills like these will help your analysts give more engaging presentations, and vastly improve your team’s chances of delivering greater business value.