Have you ever looked at a data presentation and felt completely lost? How can you transform complex numbers into visuals that tell a clear, compelling story?
Learning how to present data visually is a skill that combines design principles with an understanding of human perception. In Storytelling With Data, Cole Nussbaumer Knaflic offers practical strategies for making information both accessible and impactful through thoughtful visualization techniques.
Keep reading to discover simple yet powerful methods that will transform your data from confusing to crystal clear.
Presenting Data Visually
Knaflic says that, beyond guiding attention to specific elements, your design should help audiences understand how different pieces of information relate to each other. She explains how to present data visually by implementing three strategies.
1. Choose the Right Orientation: Horizontal bar charts work particularly well for categorical data, as they follow natural left-to-right reading patterns and provide ample space for labels. This reduces cognitive load (the difficulty of processing information) by working with, rather than against, how we naturally process information.
(Shortform note: While Knaflic’s advice about horizontal charts following left-to-right reading patterns works well for Western audiences, it raises questions for data visualization elsewhere in the world. In languages like Arabic, Hebrew, and Persian, which read from right to left, the “natural” direction isn’t so straightforward. Many Arabic-language publications maintain left-to-right data visualizations, while others flip their charts to match their reading direction. Effective data visualization must balance universal cognitive principles with cultural context. Some patterns, like the tendency to associate “up” with “more,” appear to be nearly universal, while others, like directional flow, might be more culturally influenced.)
2. Use Space Thoughtfully: Spacing is a design element that allows you to organize information in digestible chunks. Like paragraphs in writing, strategic spacing helps readers process information in meaningful chunks and understand relationships between different elements. (Shortform note: You can make data easier to digest for your audience by using consistent spacing, which helps your audience to see patterns in your data with minimal cognitive effort.)
3. Use Text Sparingly but Strategically: While visuals are the heart of data storytelling, well-chosen text enhances their impact. Use clear, informative titles that convey key messages (like “West Coast Sales Drove Q4 Growth” rather than “Sales Data 2023”). Add labels and annotations only where they illuminate key points—think of them as spotlight operators, directing attention to what matters most.
(Shortform note: Data journalist Amanda Cox’s work at The New York Times exemplifies how using annotations and text, rather than simply presenting raw data, helps audiences more easily understand data visualizations. Cox’s visualizations use words and annotations to highlight relevant patterns and expert interpretations of the data, rather than leaving the interpretation up to the audience. This makes it easier for audiences to identify and grasp the key takeaways from the data.)
Keep It Clear
Knaflic emphasizes that every element in your visualization should earn its place. Question whether each gridline, label, or decimal place truly adds value. When dealing with complex data, consider breaking it into smaller, focused views rather than creating overwhelming graphs where multiple lines tangle together. The goal isn’t to oversimplify but to help your audience see the signal through the noise.
(Shortform note: We can see Knaflic’s principles applied—and sometimes challenged—in data journalism. FiveThirtyEight, the news site founded by Nate Silver (The Signal and the Noise), is known for making complex political polling and statistical analysis accessible to general audiences. It prioritizes clarity over complexity, uses standard charts readers can easily parse, and uses scale to highlight insights. But FiveThirtyEight diverges from Knaflic’s advice to remove all non-essential information by often including context and methodological explanations to build trust with readers. This suggests that which information qualifies as “essential” might depend not just on the data itself, but on your audience’s relationship with that data.)
