Amidst the chaos of information overload, simplicity becomes a guiding light in data storytelling. At the core of impactful data communication lies the art of simplification. Picture it as a beacon cutting through the fog, guiding us towards clarity.
Just as the timeless KISS acronym advocates (Keep It Simple, Sweetheart), simplicity acts as a catalyst for clearer messages and heightened comprehension. Nowhere is this principle more vital than in the realm of data storytelling.
Your data serves as a treasure trove of invaluable insights, yet without the right approach, these gems risk remaining buried beneath layers of visual clutter and complexity. This article will provide you with a practical technique that is a best practice for eliminating visual clutter in data visualization and storytelling creation. Â
Data Visualization: A Data Storytelling Essential
When it comes to data stories, the aim is to convey insights in a compelling and understandable manner. Data visualization is fundamental to the data storytelling process and is one of the six data storytelling essentials you should know.Â
In previous posts, I’ve provided tools for developing a strategic communication plan and explored the best audience analysis tools to use when creating a data story.Â
There are also helpful posts on crafting compelling narrative and a guide on how to decide on the data story format and a great how-to on the storyboarding process to put it all together.
Between the planning and the development and delivery of the data story comes the creation of the data visualizations.Â
PeriscopeBPA provides a practical guide to data visualization that can be accessed as part of Data Storytelling Essentials training. The program and guide can be used for standalone self-guided learning or as a companion to online or live workshop programs.
Selecting the best data visualization tool is the first step in this process. However, achieving clarity in data visuals requires a deliberate effort to eliminate unnecessary noise.Â
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Simplify to Amplify
The phenomenon of data dumping occurs when a data story becomes overwhelmed with excessive information, graphs, and charting functions. While most recognize the pitfalls of this approach, brevity often takes a back seat to convenience. As Blaise Pascal astutely noted, "If I had more time, I would have written a shorter letter."
To effectively communicate your message, it's crucial to avoid overwhelming your audience with unnecessary information.
Communication transcends mere information exchange; it's about creating shared meaning.
Similarly, data storytelling revolves around helping recipients grasp the significance of insights rather than simply presenting data. To achieve this, it's essential to minimize visual distractions.
Data Storytelling Best Practice for Data Visualization
One effective strategy for eliminating visual noise is the "remove and reduce" approach. Adapted from Cole Nussbaumer Knaflic's work in "Storytelling with Data," this technique offers a practical 2-step method to decluttering analytical narratives. It is my go-to technique for both exploratory and explanatory data visualization. I'll share it here along with an easy to follow video to see it in action.
For illustrative purposes, here is a software generated bar chart comparing sales across gift shop departments and two resultingly different visualizations from the same data set. Each visualization has been reduced and then elements re-introduced to emphasize a very different key takeaway.
Remove and Reduce: A Strategy for Clarity
This simple two step process helps to create the canvas by which the key takeaways can be emphasized.
Step 1 | Remove
Begin by stripping away extraneous chart elements such as axis titles, chart titles, data labels, legends, and grid lines. While these components may offer some context, they often detract from clarity.
Step 2 | Reduce
Next, reduce the remaining lines, shapes, and labels to a neutral shade of gray. Utilize formatting options to adjust the color of each element independently, creating a cleaner and more streamlined visualization.
The resulting simplified visualization serves as a blank canvas, ready to reintroduce design elements with purpose and intention. Emphasizing key takeaways through thoughtful design choices will be your next step in the data visualization creation process.
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A Strategy for Clarity
By eliminating visual noise, you not only improve your audience's comprehension but also enhance your own ability to discern trends and patterns within the data.
With the canvas cleared, the next step will be to evaluate each element critically, reintroducing only those that contribute significantly to your audience’s understanding of the key takeaway.
By minimizing visual distractions, you can enhance the audience's focus on key insights through the introduction of design elements such as color, boldness/line weight, and text and other pre-attentive attributes of visual perception.
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Summary
Simplifying data visualizations is essential for effective communication. The "remove and reduce" strategy offers a practical approach to eliminating visual noise and enhancing signal strength.
Shift the focus from tech to people in your data storytelling. While visuals aid comprehension, it's your empathy for your audience's needs that truly elevates your narrative. Simplify your visuals to amplify your message, ensuring it resonates clearly with your audience.
Remember: keep it simple and let your insights shine.
Roseanna Galindo is Principal at Periscope Business Process Analysis and a champion for data literacy, the human experience in healthcare, and leaders of volunteers everywhere. Learn more about Roseanna and her blog, The Periscope Insighter, by reading the opening post, Venn The Time Is Right
Roseanna is available for training, keynotes, and executive coaching. Visit PeriscopeBPA.com for more information or click on the button below to schedule a time to talk.
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