How many times have you struggled to quickly understand what a chart is presenting? It is something that I often experience in media when reading articles or watch some statistics on TV. Sometimes is extremely hard for me to make sense of what I see, just because I am not the subject matter expert and those data at a glance do not seem familiar. And let face it, I am a data person. What must feel ordinary people, who do not work with data on a daily basis and are not highly data literate?
This post is inspired by data visualisations in the article that I have read recently about the employment situation in the UK. You can find the link to the paper at the bottom of the post.
We are going to focus on three easy to introduce improvements to make any chart more readable, impactful, and thoughtful:
- Additional Axis labelling
- Annotation
- Preattentive Attributes
As an example, we will improve the below chart that presents changes over years of staff availability index.
Additional Axis Labelling
I am not familiar with the staff availability index. From the title and footer of the chart, I understand that the higher, the better. However, that information could be served on the plate. Based on my experience, I can see an easy fix for such a case that speed up the cognitive work of my brain. Most of the time, when some charts are presented, they present some changes over time or comparisons between two or more phenomena.
In this case, adding small arrows to the Y-axis and additional words describing axis directions give much more sense to the chart and improve the audience experience. Now the chart presents not only changes over time but informs the expected direction of change.
Annotation
There is a common myth that “Data speaks for itself”. No data can speak because it does not have a tongue. The responsibility of proper understanding of the message lies on the messenger side. Another quick win is adding more text to the chart itself. Additional description or insight help people to process information more effectively and, thanks to visual presentation, make it easier to remember.
I have added a sentence from the article next to the point that I have wanted to emphasise. The rich text pays attention to the audience eyes, and the soft grey line directs to the specific point on the chart.
Preattentive attributes
Each object on Earth has properties like shape, colour, size, position. This is what we notice without using conscious effort, and because we do not involve too much conscious effort, we must take advantage of it to decoding information faster. Thanks to them, we can guide the audience eyes through our data visualisation and point them exactly where we want.
Introducing a small red dot is a true game-changer for presenting information on the below chart. We can get this effect by taking off the line chart colour and add to the chart another object with a different shape (circle), size (the circle is significantly thicker than the line), and by adding contrasting colour (the red one). At the final stage, let us analyse our eyes movement. First of all, our eyes start looking at the chart with the title (that is why do not forget about titles! Never!). Then they go straight to the red dot. Just next to the red dot is an insight that explains that point. Next, they track the line chart and finally look at additional Y-axis labelling. Now, our brain, after collecting all this information, can process them and make sense of those data.
I would recommend those three easy to remember and use tricks to uplift any data visualisation that will improve your audience experience.
The link to the article:
Convince Me with Data 