Creating an Engaging Story for Data

Data is often presented in a no-nonsense manner, providing lines of text (and graphical information in some instances) that provide factual information based on thorough research and studies. But while this no-nonsense approach has its advantages, the downside is that data is presented in what can be described as “uninteresting,” often leaving its audience confused and unable to appreciate the information presented.

If a business aims to become a data-driven enterprise, it is crucial that the data it presents will be comprehensible and appreciated by its audience. One way to ensure these goals are met is to create compelling stories built around this data.

This is known as data storytelling, which conveys data-driven insights using narratives and visualizations that engage audiences and help them better understand key conclusions and trends. The objective is to create greater engagement with and understanding of the data so the organization can make sound decisions and policies based on such data.

The elements of data storytelling

Data storytelling is comprised of three key elements:

Data visualization – these are the graphical and other visual elements that illustrate the information of the data

Narrative – the who, what, where, and why found in the data

Context – the premise behind the data

Narrative and context are the more crucial elements in the data as they should blend together in order to be able to tell a cohesive and comprehensible story with the data.

“The way that we think about stories, if we remove the data term, it needs a plot that you care about, it needs characters that you root for, and it requires a destination or an outcome that you believe in and aspires to,” shares Grace Lee, chief data and analytics officer at The Bank of Nova Scotia as quoted in the CIO.

As such, being able to put the data into context in the form of a narrative allows people to care more and to understand what the action is that comes out of it.

The challenges of data storytelling

Data storytelling is not as simple or straightforward as it seems. Especially if one is unable to present a clear and cohesive narrative and context to the data.

Another challenge is that some presenters have difficulty relating the data to their audience. And that is because there is a disconnect between the data and how the audience could relate to it.

Kathy Rudy, chief data and analytics officer at global technology research and advisory firm ISG, had this to say, “Start with who your main characters are, that is, the audience for your data story. What information is most important to them? Structure your data story so you anticipate the next question the audience will have by thinking like the reader of the story.”

It’s also important to consider the medium various individuals are using to consume information and what times they’re accessing this information.

The third challenge is gaining acceptance for the validity of the data that is being presented. Thus, it is important to hold data validation sessions to get the question of data validity out of the way and address any questions with regard to the