The document discusses information overload and how data visualization techniques like infographics can help address this issue. It provides examples of how a simple table of data can be transformed into an engaging infographic through the addition of visual elements like charts, maps, and interactive features. The document also provides some history on the evolution of data visualization and infographics, highlighting some pioneering figures. It emphasizes that good infographics start with clear goals and an understanding of the audience in order to tell an accurate story with the data.

1. Issue # 9 - 2014
Information, good. Too much information, bad.
Why we love infographics, the Godfathers of the genre, something about data journalism and a very
good data visualisation tip – it’s not all about graphs and design … content and story drive the
process!
Data is the lifeblood of the information age. It helps us make smart decisions which improve our
chances of success in all areas of life. But what happens when there is just too much information to
process? Misjudgements easily lead to missteps which in turn can spiral into mishaps. This is where
data visualisation techniques and the increasingly popular infographic come to the rescue. They are
easier to digest, fun to share and more engaging and persuasive.
Today, the average person is exposed to at least five times more information than in the mid-1980s.
Emails, news feeds, blogs, tweets, memos, reports … data bombards us from every direction and
through an ever-growing collection of channels and devices on our desks and in our pockets.
Faced with information overload it is much harder to take in what we read – as low as 20% according
to studies*. This is bad news for those of us in the communications business. How do we approach
audiences or markets with our messages when they are already drowning in them? The silver lining is
that we can recall up to 80% of information that involves ‘seeing’ and ‘doing’. And the majority of us
are more persuaded by presentations accompanied by visuals**. This is where data visualisation
techniques – backed by experience in data journalism and web technologies, especially apps and
dashboards that transform ‘readers’ into active ‘users’ – are so tantalising.
More than data
Take, for example, a table of data about the costs of medication in France. The information is all there
and can be ‘interpreted’ by anyone clever enough or with time on their hands. But if you plot that
information onto a basic X- and Y-axis chart the data immediately assumes more meaning; you can
see without effort the upward trajectory of the arrow and understand that prices rose, say, in the 1990s
and then went down in the 2000s. Questions arise from this, and a story starts to form as answers are
sought. What happened to the pharmaceutical sector in France?
Now add to this chart a map of France and some information, such as the consumption of popular
over-the-counter (OTC) drugs represented by pictographs, and we are a step closer to answering this
“Data visualisation is the graphical display of abstract information for two purposes: sense-making (also
called data analysis) and communication. Important stories live in our data and data visualisation is a
powerful means to discover and understand these stories, and then present them to others.”
(Stephen Few, author of ‘Data visualization for human perception’)
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2. question. The size of the pictograph further develops the story – i.e. the bigger the symbol the higher
the consumption in certain regions or markets.
Include a catchy title, such as ‘Are your drugs costing too much?’, and a small introductory article:
Have you noticed you are paying less for some OTCs but much more for others? And the price for
aspirin can vary depending on where you are in France? It’s not your aching head playing tricks on
you. Here’s how much it can vary in different regions. Ouch!
So, from a plain and hard-to-read table, we now have a chart, a mapped pictogram and a little narrative
about the confusing world of OTC medications – all the makings of an infographic! Despite the
improvement, this is still a rather static, or indeed passive, presentation. But online media has
massively changed this.
Imagine adding a small drop-down menu under the mapped pictogram with the subject; ‘How much
does aspirin cost in your city?’ and with the click of a mouse, the map dynamically changes to display
the most popular OTCs by city and their prices. This is when ‘seeing’ becomes ‘doing’ and the
chances of information retention improve by up to 60% with one click.
A table of data thus becomes an illustrated graph which in turn becomes an infographic and is finally
transformed into an example of enriched or dynamic data visualisation with input from users. With
each step, the reader becomes more of a user who can ‘drill down’ to as much detail as desired. This
follows the Schneiderman visual information-seeking mantra – “overview first, zoom and filter, then
details-on-demand” – published in his 1996 paper, ‘The eyes have it: A task by data type taxonomy for
information visualizations’.
A step up in the information (r)evolution:
The Godfather
Sometimes called the ‘Godfather of infographics’, in the 1920s and 30s the German Fritz Kahn
understood how metaphor and visual imagery could make an abstract concept clearer. But data
visualisation techniques were documented well before Kahn’s time. The Flemish astronomer Michael
Florent Van Langren is credited with the first visual representation of statistical data in the 17th
century. The Scot William Playfair developed graphical displays in the 18th century that we recognise
and use today, such as line, bar, circle and pie charts. By the 19th century, statistical graphics entered a
reported ‘Golden Age’, including the now famous map by John Snow of London’s 1854 cholera
outbreak, which helped to pinpoint the cause of the disease.
In the 20th century, as computers became powerful enough to process vast amounts of information,
data visualisation also blossomed. In 1977, the US professor John Tukey took the field to a new level
with his ‘exploratory data analysis’ approach to data visualisation. Today, names like Edward Tufte
and Stephen Few are often cited in this fast-evolving field. Tufte’s book ‘The visual display of
quantitative information’ basically showed that there was such a thing as bad or unnecessary attempts
at ‘improving’ how data is presented, while Few’s books include ‘Show me the numbers’ and ‘Data
visualization for human perception’.
Table of
data
Illustrated
chart
Infograph
story
Dynamic
data
visualisation

3. A communication tool
While the medium has been around for centuries, advances in digital technology have clearly played a
part in the growing popularity of modern infographics. Graphic design tools and platforms are now
cheaper and easier to access and use thanks to the internet, which doubles as a prolific channel for
displaying the resulting infographics to audiences who have less time to wade through masses of
information.
But there is a problem. “Since the turn of the 21st century, data visualisation has been popularised, too
often in tragically ineffective ways as it has reached the masses through commercial software
products,” notes Few on the Interaction Design Foundation portal. But there are some gems out there
which value “data exploration, sense-making and communication” over “superficially appealing
aesthetics”, he continues.
Good infographics are more than the sum of their parts. They begin life with a desire to marry the data
and responsible story-telling – a story that respects basic tenets of data journalism by being accurate,
verifiable, visual, unbiased, connected and coherent.
For a communications agency, this means the graphics team must work hand-in-hand with the
editorial team, and sometimes for ‘big data visualisation’ jobs consult information architects who
specialise in structuring mountains of information into bite-sized parts.
Good infographics thus start with an excellent briefing
from the client or project manager. The briefing must
include a clear description of the aims of the infographic,
the audience and the expected dissemination channels.
Supporting information, such as a mood board or
benchmarks of other work that the client or project leader
likes, is also useful input at the kick-off stage.
The ‘story’ that the infographic tells reveals itself from the clear briefing, and starts with a set of key
words and messages which help to establish the plot points. What are we trying to tell, to whom, and
why? By this stage, the information or other ‘hard’ content to be included in the infographic should
have been provided by the client or researched by the journalist and organised into structured data,
capable of being graphed or plotted.
A simple ‘storyboard’ is also a useful way of mapping out the stages of the infographic and can be
provided to the client as a more developed package of key words and messages alongside basic
sketches, photos or graphical features. The storyboard helps to distil complex information into simple,
self-contained visual presentations in a flowing narrative.
Once the briefing and editorial framework (concept, key words and messages) is established, the
graphic artist can take over, guided along the way by the editorial team and/or project manager, if
needed. Together, this infographic ‘team’ ensures the story gets told in the right way, respecting the
client’s initial briefing, and that the end product is not only beautiful but also effective and accurate.
Interested in these insights? If you would like to discuss how to improve your communications
efforts, ESN’s Consultancy Department would be glad to help. Drop us a line! www.esn.eu/contact
*Lester, P.M. (2006) ‘Systematic Theory of Visual Communication’
**Wharton School of Business, ‘Effectiveness of Visual Language’
“GOOD INFOGRAPHICS START WITH
AN EXCELLENT BRIEFING…”