Elephant In The Room: Data Storytelling Is More Than Just Data Visualization

As data storytelling has grown in popularity, it has become increasingly synonymous with data visualization. This viewpoint is understandable because data charts are often heavily featured in data stories. However, this prevailing perspective is also problematic. When visualization receives most of the attention or emphasis, the other critical components of data storytelling are then ignored or underdeveloped. Unfortunately, this perspective has caused great confusion about what data stories are and how to best craft and deliver them.

The overemphasis placed on the visualization element of data stories reminds me of the ancient Buddhist parable of the Elephant and the Blind Men. When a group of blind men encountered an elephant for the first time, they were brought forward to touch the strange creature to better understand what it was. However, each blind man touched a different part of the animal and came away with a different interpretation of what an elephant is: a thick snake (trunk), a tree trunk (leg), a wall (backside), a spear (tusk), a rope (tail), and a fan (ear).

Similarly, when data storytelling first emerged most of the focus was exclusively on the visualization aspects. For early adopters, the unique differences between the exploratory and explanatory approaches for data charts brought this aspect to the forefront. Many then assumed it was the defining attribute of data storytelling. Unfortunately, this enduring stance has undermined data storytelling’s true value and misrepresented what it means to tell compelling stories with data.

Data storytelling is much more than just data visualization

When data visualization is the primary focus of data storytelling, it has led to a couple of common misconceptions. First, some people believe every data chart tells a story. Yet, if there is something interesting or notable in a specific data chart, you are only sharing a piece of the puzzle (a data scene), not a complete data story. Often, you’re going to need more than one chart or visual aid to explain why something is happening and how to best address it.

Second, some people treat data stories as simply a collection of interesting but loosely related observations (data points). However, unless the charts are tied together with a compelling narrative, you’re not telling a story. The puzzle pieces must fit together and create a cohesive whole.

In my training courses, I’m often asked whether dashboards tell stories, and in most cases, they don’t. While automated dashboards help us to monitor business performance, they rarely tell a targeted, cohesive data story. From a storytelling perspective, they often resemble a mixture of puzzle pieces that don’t always neatly fit together or may originate from entirely different puzzle sets. I view the role of dashboards as being focused more on data exploration than explanation.

Rather than viewing data storytelling through a narrow lens of data visualization, a more balanced perspective is needed that is centered on communication. The real purpose of data storytelling is to communicate insights more effectively, which requires a skillful combination of all three key elements: data, narrative, and visuals. While all three of these elements are important to data storytelling, two are crucial and one is dependent. Let’s take a closer look at the role each element plays in a data story:

• ‍Data. Facts or information must form the underlying foundation of your story. Some level of analysis should always be behind each data story or else you just have a work of fiction even if you sprinkle in a few statistics for good measure. While you can form a story from your imagination to fit any desired narrative, that doesn’t apply to data stories, which must always be based on analysis and interpretation of data. ‍
• Narrative. It’s common for people to view this aspect of a data story as just the commentary or annotations that accompany the data charts to add meaning to the numbers. However, how the story is assembled and how it follows a specific structure is equally important to how the insight is communicated. Without the narrative arc, you just have a detailed report—not a storyline that has been crafted to guide an audience through the meaning and impact of a key insight.‍
• Visuals. Raw data can often be complex and difficult to interpret. Visualizations can help your audience quickly make sense of the numbers and see things that would be difficult to observe without charts. However, as many informational podcasts have shown (e.g., NYT The Daily), visuals aren’t always needed to tell stories with data. In addition, strong visuals will not fill the void created by a weak message (narrative). Even weak visuals can be passable if the overall message is strong.

In summary, you can’t have a data story without facts (data) or a storyline (narrative). While visuals may not always be necessary, they can often enhance your storytelling and help you explain your insights more clearly. Using visuals is a means to an end that assist in communicating your messages more clearly. Unfortunately, this dependent element has received most of the attention instead of the other two crucial elements, especially the narrative aspect.

A shift in focus for data storytelling is needed

Recently, data expert Bernard Marr predicted one of the top technical skills to learn in 2023 would be data storytelling. To support this prediction, he cited a Forrester report that showed 70 percent of people will be working heavily with data by 2025. As data continues to be more prevalent in different roles and functions, the need to communicate data and insights effectively increases in importance. However, as organizations seek to develop these skills in their employees, many may still approach it with the misguided belief that data storytelling is primarily about data visualization and reporting. Regrettably, these training investments will only lead to a partial and incomplete understanding of what true data storytelling entails.

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If the blind men in the parable had touched only the elephant’s ear, they would incorrectly envision the creature as a way of keeping their homes cool in the summertime (as a smelly, oversized fan). Without a more comprehensive understanding and full appreciation of this animal, these villagers would misinterpret its purpose and fail to recognize how it could contribute in more meaningful ways to their village.

Data visualization plays a prominent role in data storytelling—just as it does in exploratory analysis, dashboards, reports, and many other applications. However, a data story is more than just a collection of well-designed data charts—it’s about communicating insights effectively. Until more organizations recognize data storytelling is more than just data visualizations, companies will be operating under the false belief that their people have everything they need to be successful at telling stories with data if they've received some data visualization training.

However, without the right approach to data and narrative beyond the visuals, you will fall into a trap that George Bernard Shaw identified: “The single biggest problem in communication is the illusion that it has taken place.” While you may have visualized your data clearly or compellingly, it doesn’t mean you have told a story. If you don’t want to put your insights at risk of being misunderstood or overlooked, data storytelling must be firmly centered on effective communication using all three key elements of data, narrative, and visualizations in a balanced approach.

If your organization is ready to strengthen its data storytelling capabilities with a balanced approach, I’d love to schedule a call to discuss your team's training needs in more detail.

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