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Data Visualisation Mistakes: Getting the Balance Right Between Clear and Creative Graphics
When you’re sharing data, the means of delivery can make all the difference. Reams of text explaining the data can be easily misinterpreted, but not everyone was born to create charts and graphs that aren’t incredibly dull to look at.
We’ve created some examples of bad graphic designs and common data visualisation mistakes. Whether a graphic has too much data or is trying to be too creative, we’ve curated a careful list based on real-world examples to showcase what not to do when making creative graphic designs.
That’s why it’s important for every online business—whether you're an SEO company, digital PR agency, or a specialised content marketing business—to break any potential graphs or graphics down into three components and weigh each equally in order to deliver information in an awesome way. These three components are data, clarity, and creativity.
Common Data Visualisation Mistakes: Examples of Bad Graphic Designs
1. Colour Choices
Colour can have an interesting effect on perception. Too much colour can be overwhelming, and too wide a contrast in colours can make differences seem more significant than they are. Instead, operating on a simpler colour palette or having realistic changes to the shading can more accurately show data—and it’s more pleasing to the eye.
2. Missing Baseline and Strange Scales
Particularly in the realm of sports and politics, there is a trend to create graphics with a baseline above zero or to use scales that don’t make a lot of sense. This can, intentionally or not, have a huge impact on the interpretation of the results. Small differences can seem huge, and patterns can appear that aren’t statistically significant.
3. Incorrect Format
The format the data is displayed in is vital, and many different kinds of data visualisation exist to do this. You wouldn’t use a Venn diagram to show different categories that have no overlap, and you wouldn’t use a bar chart to demonstrate continuous data. Using the wrong format to display your data can affect how it is interpreted—or even stop it from making sense at all.
4. Inferring Correlation vs. Causation
By pairing otherwise unrelated data, it’s possible to make it seem as though there is a correlation when there isn’t one. The rate of shark attacks seems to increase alongside an increase in ice cream sales—when this is presented in a line graph together it can seem one causes the other.
5. Cherry Picking
There is a tactic called cherry picking, used amongst statisticians without scruples. This is where a single aspect of the data is hyperfocused on, forgoing other relevant data. This can be used to put a positive or negative spin on something which might otherwise be irrelevant, such as an upwards trend in the middle of an overall plummet.
6. Human Interpretations
It’s well-known in marketing circles that human psychology is hugely important when it comes to selling stuff and impacting public opinion. Colour theory, shapes, and emphasis all affect how data is understood and absorbed. When red is compared with green, it’s common that green will be interpreted as good. Blue vs red can lend a political angle. Sometimes this can be useful and appropriate, but it’s important to bear it in mind so you don’t unintentionally affect perception.
Reasons Behind Common Data Visualisation Mistakes
Data
Data is the basis of all infographics. It has to be good data, collected meaningfully, with a solid methodology—otherwise what is the point? Knowing how much of the data should be included per graphic is also a fine art. Too much data and you risk muddying the waters, too little and the graphic is bland and pointless.
Data sets can be large and unwieldy, and it’s easy for anyone to get carried away with the amazing information they can contain. This makes it easy to slip into trying to share too much of that information at once. Graphics with too much information are a nightmare to make heads or tails of. It’s much better to have a graphic that focuses on one or two aspects of the data, rather than everything all at once.
The data should also be compelling and relevant to the campaign. Even though the case may arise where a lot of work has gone into gathering data, if the angle has shifted and it’s no longer relevant, it’s important to know when to cut it out.
In the below graphic, it is difficult to read and retain all the data that they are providing, and it’s made more difficult thanks to a number of the colours being quite similar to each other.
Clarity
It isn’t just the amount or kind of data that can affect a reader’s understanding. The data presentation is vital when creating a clear and creative graphic design. It can be tempting to devise intricate and artistic ways of presenting data, but if this data isn’t clear to understand then it is a wasted effort.
By keeping the focus of the graphic clear and simple, it is much easier for laymen and statisticians alike to read.
The graphic below has too many good ideas going on at once—it's just too creative, and has too much info! The colour has no bearing on the information, and neither does whether the line is continuous or dashed. The information overlaps and blurs, too, making it impossible to read.
Creativity
None of the above is to encourage boring graphics—graphics need to be attention-grabbing to deliver the information they hold. A great graphic can be shared independently of the article it is contained in, and still be exciting and understandable. This is where creativity comes in—to present the data in an exciting way, that gets the point across while still looking great.
Where to be Creative in Graphic Design
Everyone is familiar with the standard graphs and charts we learned about in school. Bar charts, line graphs, pie charts, Venn diagrams—they all have their uses and times when they excel.
But using the same old format over and over can be dull, both for the audience looking at it and for the designers creating it. Instead, consider more artistic ways of creating graphics. This could be through symbols and patterns, the layout or orientation, or by using interactive elements to really get audiences involved.
As in the graphic above, we’ve created a visually appealing graphic that tells a story. Not only does it show how many attacks happen per month, but shows the movement of these attacks over the year.
Different Kinds of Chart
Bar Chart
Bar charts are great for showing comparisons between groups of variables, such as age brackets or different businesses or genres. As they’re generally quite simple to read, there’s lots of room to get creative in how they are formatted.
Line Graph
Line graphs are perfect for showing progression over time—for example, the sales of a product over months or years. It’s also simple to add further lines, denoting different variables.
Pie Charts
Pie charts are best used when you have only a few categories. Lots of sections on a pie chart can easily become muddled and confusing. A pie chart would work well for demonstrating the numbers of men vs women vs nonbinary people working in a profession, but for something more varied such as religious belief or nationality, it would become confusing to look at.
Venn Diagrams
Venn diagrams are designed to show overlap, with usually two distinct circles that share a small section of commonality. They can be somewhat mundane, but their simplicity lends them to creativity. Background images, textures, and shapes can all lead to fun ways to present data that is easy to read.
The Secret to Clear, Creative Graphics
Graphics can be wonderful vehicles for data, but it’s never as simple as putting some numbers into a pretty format. There are many wild and wonderful ways to present the information you’ve worked so hard to gather, but the most important aspects are simple. Make sure the data is good, the information is clear, and then let your creative side flow.
