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  • Writer's pictureCarolyn Röhm

Mastering Data Communication: Expert Tips for Impactful Visualisation and Infographics

Updated: Dec 7, 2023

As analysts, if we’re going to be effective and drive change, then one of the things we need to do is communicate well.


#TopTips for communicating data well:

  • Be mindful of your audience – some people like pictures and colour, others prefer words, facts and figures. Use both.

  • One size does not fit all; data visualisations come in many guises. Use a variety of techniques for maximum impact.

  • Use colour and data-point formats to convey additional information and detail.


Often, we’re communicating with people who aren’t analysts. They’re also busy and have multiple competing priorities. We must communicate as effectively and efficiently as possible to cut through the proverbial noise.


Data visualization and infographics enhance research communication by providing new insights and changing the way researchers, media outlets, and policy-makers interact with data­.

Dunleavy, D. (2015). Data Visualization and Infographics. Visual Communication Quarterly, 22, 68 - 68. https://doi.org/10.1080/15551393.2015.1029070.


Don’t you just love academic papers? I know they are filled with valuable and new information, but sometimes, they are just so difficult to digest. Bottom-line, this author’s work shows what many excellent analytical communicators know – how we present our data matters. Insights can be and are more readily understood when we use great visualisations and infographics.


But isn’t data visualisation the same thing as a chart?


The short answer is no, they’re not the same thing. Charts are a form of data visualisation. Data visualisations could be plots (and I’m sure that there are people who will say that a plot is a chart). Visualisations could also be animations or infographics. Visualisations involve the use of colour, and believe it or not, the choice of colours matters.


The (humble) Pie Chart

Full disclosure: I have a very strong aversion to pie charts and an even stronger aversion to 3D pie charts. In fact, I thought I would demonstrate my feelings regarding pie charts in this handy infographic!

And this brings me to another point, some people are all about the images, metaphors, and stories. Other people are all about facts, figures and the detail. When analysts communicate with others, especially others outside our teams, we need to remember that we’re communicating with all sorts of people. Some people will look at the pie chart infographic and just ‘get it’. They might feel that I’m being a bit too over the top with that last image (but then they clearly don’t appreciate the extent of my dislike of pie charts).


Other people need words, numbers and facts or figures. When we’re communicating, it’s helpful to cover all our bases.


This article discusses pie charts specifically; the author discusses many of the weaknesses of pie charts and shows alternative options, all of which better show the story the data tells

.

Pie charts aside, there are many more things to consider when we want to communicate our findings.


This article lists several things that friends don't let friends do regarding data visualisations!


The use of an Executive Summary

I’ve seen many reports that start with an introduction and then proceed to work through everything that was done, including the detail of the results. Finally, one of the last pieces of work summarises the key findings or recommendations.


Turn that on its head.


Start with the most important information – what were the key findings? What are the next steps? If this report goes to senior leaders, keep it concise and keep only to the pertinent facts. Include an infographic where it makes sense to do so. Senior leaders are busy – well, we’re all busy, so ensure you convey the most critical information right at the beginning. That way, they can read the rest of your report if they want more detail. They can save time if they’re comfortable with the findings, next steps and recommendations.


Did you notice the summary at the top of this blog? It’s a few sentences that concisely convey key information.


A note on the use of Colour

There is a plethora of information available regarding the use of colour. Whenever I think about the use of colour in charts or slides, I’m reminded of a friend of mine from my university days. He studied computer science and attended a lecture on binary code, 0s and 1s.


They were watching a video depicting binary code, and the authors (in their wisdom) had chosen to represent the 0s and 1s with red and green blocks...


For many people, this would not have been an issue; after all, red and green are very different colours. Except that my friend is red-green colour blind. There are a number of different types of colour blindness, with red-green colour blindness being the most common.


If you want to check whether your data visualisations make sense to people who are colour blind (in all its forms), I have found this website to be a handy resource.


You may be wondering whether we really need to be concerned about colour blindness. Colour blindness impacts approximately 8% of the population. I always think of my mate giving up on the lecture because he could either focus on trying to see the different colour squares or pay attention to what they were saying, but he couldn’t do both.


The image below gives you an idea of what people affected by colour blindness see as compared to people with normal vision.


In summary

There are no hard and fast rules; there are guidelines. And there are as many opinions on how to do this well as there are people sharing them. Perhaps think about how you’re presented data historically.

  • Did you get a “yes, go ahead” type answer?

  • Were you asked many questions before your initiative was green-lit?

  • Perhaps there was a deathly silence, followed by no real progress?

If you’re in the latter categories – I suggest looking at how you share your insights. Who is your audience? Did you communicate with them in a way that makes sense to them? Try a few experiments and see what happens.


I’d love to hear what you think about this. Have you seen any truly great (or spectacular fails) when it comes to communicating data through visualisations?

 

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