Infauxgraphics & Vanity Viz: What they are and how to avoid them
Published: 2021-10-25 07:02:56

This article by Brooke Jamieson [originally appeared on startupdaily.net](https://www.startupdaily.net/2020/10/infauxgraphics-vanity-viz-what-they-are-and-how-to-avoid-them/).

If the pandemic has taught me anything, it’s that we need to rely on quality data that communicates clear and concise information, especially in stressful and uncertain times.
If done well, data visualisation can be a reassuring sense of logic and reason in a chaotic world. However, 2020 has also shown me how damaging poor visualisations of data can be. 

_**Infauxgraphics**_ – infographics that aren’t genuine – are one of my pet hates.

They’re often so close, yet so far from an accurate representation of data. This is especially disappointing when the designer isn’t being malicious, just misguided.

I think many people don’t even mean to make some of these simple errors, but they just see them so frequently that they seem like best practice because they’re so common. 

_**Vanity Viz**_ extend this idea.

On the surface, they look appealing and visually powerful, but they lack any substance.

It’s like seeing a really beautifully plated meal that looks wonderful on the plate, but then doesn’t taste like anything at all.

Unfortunately, these are also super common! Perhaps lots of these started as portfolio builders for graphic designers, but then have served as inspiration for other visualisations where the content and data insights are much more important to communicate. 

From experience, people who create Infauxgraphics or Vanity Viz either create them accidentally, or maliciously. They seem to be very polarising and never in between. 


##Too much information – or not enough?
When accidentally bad visualisations or infographics have too much information, it dilutes the value of each key point.

Viewers have finite attention and focus, and superfluous information just prevents people from being able to engage with key information.

Extra text or charts on a page also sometimes prevents people from seeing a clear path between the data story points, preventing the data storytelling to happen at all, so even if people see the key points, they’re unlikely to remember them. 

Malicious designers can use too much information to throw viewers off course, or to hide the fact there’s no key information in the first place. This is a key symptom of Vanity Viz! The irrelevant information just masks the lack of insights or thorough analysis, or distracts users from negative (but much more important points) that may have been diluted to the point they’re not noticed. 

Another key trait of a Vanity Viz is not enough information! To achieve a clean, minimal and portfolio-ready look, designers might leave off axis scales, units, captions, references or any other key contextual information which can help viewers to interpret the results, and as a result, the insights can’t be interpreted at all! As with all lean design, function needs to take priority over form, even though the look and feel is important. 

##Phoney Patterns
I’ve ranted at length about the difference between correlation and causation before, and one of the big reasons behind this is the prevalence of phoney patterns in bad data communication. When you’re presenting multiple charts on a page as part of a slide or infographic, it’s important to note what is sitting next to what. Human brains want to see patterns in everything, so simply changing the arrangement of charts on a page can really change how viewers interpret them. 

When designers do this accidentally it’s one thing, but doing this maliciously is very common! When you’re arranging elements on a page, make sure you’re not doing so in a way that ruins the integrity of the insights you’re trying to convey. 

 

## The True Colours
COVID-19 has truly brought out the worst in some people! Just as humans rely on pattern recognition, we rely on memories and simple rules of thumb. Always double check ‘Traffic light colours’ when you see them on infographics! Sure, green normally means go (or good!) but malicious designers can use this as an easy opportunity to camouflage poor results or values, by hiding them in plain sight with a nice little green upwards pointing arrow next to them!

On this note, if you are using red and green as status or quality indicators, make sure they’re visibly different to people with all types of vision, especially different types of colour blindness. Lack of accessibility isn’t often malicious, even though it’s never constructive. Put some effort into planning a colour scheme at the start of a design to make sure that you can communicate to everyone who views it. Colour contrast makes a vast difference, and there are so many helpful tools to guide you! 

Overall, there’s no point spending time making an infographic or data visualisation if it can’t communicate the data insights it needs to. Instead, spend time working towards thorough analysis and insights that can lead to action – and you won’t need to cover up anything with cosmetic changes.