Six Important Lessons from Storytelling with Data by Nussbaumer Knaflic-Part-2
In this series of articles, I will be sharing a summary of the book Storytelling with Data by Nussbaumer Knaflic. All of the content is taken from her book but I have tried to summarise the content by explaining the six important lessons taught in the book regarding the subject matter. I hope these six lessons would go a long way in improving your visualization expertise and hence in the art of better storytelling from Data. This would be a series of articles, in each article I would be summarising one or two lessons. In this part, I will be summarising the third key lessons.
What is Clutter?
In the third chapter, Knaflic elaborates upon clutter and how to avoid it in your own visualization. According, Knaflic clutter is, “these are visual elements that take up space but don’t increase understanding”[1]. The reason she believes clutter is an enemy of your visualization is that it does not convey any information to your audience while increasing the “cognitive load” which is basically, “processing that takes up mental resources but doesn’t help the audience understand the information”.
Gestalt principles of visual perception
Afterwards, she describes 5 key elements that make up common visual perception. She then uses this as a basis to further explain main issues related to clutter and then lays down detailed steps as to how to one can avoid it. The first element is, “Proximity”[1] which is that human tendency to think physically close object as belonging to the same group. The second element is “Similarity”[1] which means that, “Objects that are of similar colour, shape, size, or orientation are perceived as related or belonging to part of a group”[1]
The third element is “Enclosure”[1] which is, “We think of objects that are physically enclosed together as belonging to part of a group”[1]. Further, the fourth element is “Closure”[1] which means human likes simplicity rather than complexity:
The final key element is “Continuity”[1], which is the human tendency to seek the most smooth path and even create one even if explicitly no such continuity exists.
Main Causes of Clutter
The author then uses these five key elements to elaborate upon what is actually clutter for human and how to avoid. The first cause that she mentions is the lack of visual order. This is basically no specific ordering and emphasising of the visualisation where everything is just spread white and grey:
Clearly, the visualisation has no clear structuring and order which makes the conveying of information difficult to the user because it adds more complexity for the audience and also does not emphasis any sort of continuity for the audience. The author then improves this graph to improve its’ visual order and therefore reduce the clutter:
Moreover, the above example also shows that a lack of alignment in any visualisation also adds to the clutter. Note as to how, in figure-4, the graph is centrally aligned which makes the visual interpretation smoother and hence easier. The author also talks about as to how many novices add data just for sake of adding data while leaving no leverage for “White Space”[1]. She mentions as to how “White space in visual communication is as important as pauses in public speaking”[1] & “Can be used strategically to draw attention to the parts of the page that are not white space”[1].
Further, she elaborates that people use contrast randomly rather than strategically. Contrast can be used as a signal to the audience:
Decluttering Example
Finally, she mentions six steps to avoid decluttering before finishing the chapter. The initial cluttered graph is as follow:
After applying the six-steps which uses the five elements of visual perception and avoid the main causes of clutter:
1- Remove chart border
2- Remove chart border
3- Remove data markers
4- Clean up axis labels
5- Label data directly
6- Leverage consistent colour
The final graph is as follow:
Conclusion
In conclusion, this article summaries the third chapter in the book which is all about the causes of clutter and how to avoid it. I have tried to summaries the key ideas which capture the gist of the chapter so that you can easily apply the learning of the chapter and avoid the greatest enemy of any visualization.
In part three of this series of articles, I will discuss the fourth key lesson of the book.
References
[1] Knaflic, Nussbaumer. Storytelling with Data.
