If there was one overall theme, it would be persuasiveness. In fact, this was presented as self-evident — an almost inherent quality of any great infographic — so the interview primarily focused on what makes an infographic persuasive.
“First, I’d say, they all have a clear focus. The designer has gone in and removed all the extraneous details so you see just what you need to understand the message behind it.”
I couldn’t agree more. In my own graphics, I am constantly trying to simplify and boil them down to the essential elements — from the text and layout to the colors and icons — that help make the point of the graphic clear.
But in the process of simplifying my graphics, I have sometimes found myself approaching a line — and it’s one that you do not want to cross — after which the graphic is too simple, lacks sufficient context, and loses all its weight. For example, I’ve simplified the pie chart below and used color to help emphasize the point of the graphic.
When you’re creating content — whether it’s a film, a sales presentation, or an article on maximizing your Thanksgiving leftovers — it’s always important to consider who your audience is; this also holds true for data visualization. I’ve touched upon this in my previous blog posts, but let‘s take a closer look at the audience spectrum specific to data visualization.
In my previous post, I covered the increasing popularity of "infographics" — both the term and the wide range of examples. I cautioned against unthinking imitation; like most trendy things, their surface shine can distract from their bad qualities, and it’s easy to lose sight of basic principles and objectives. And this distraction is partly to blame for the currently polarized perception of bar charts, which are seen as both antiquated and ideal.
Both Forrester clients and internal colleagues often tell me “We want something better than bar charts” when describing how they would like to see their data visualized. At the same time, I also hear from others, jaded by the onslaught of overdesigned data graphics, who insist there is nothing better or more accurate than bar charts when it comes to visualizing and comparing data points. They don’t need all the “bells and whistles.” “Edward Tufte!” they cry.
So, what’s causing this divide? How can a chart type be so polarizing? I think the answer lies in both the implied perception of bar charts as this basic, limited chart and the array of bad examples of both alternative visualization methods and bar charts themselves.
As the newest blogger for the Data Insights blog, please allow me to introduce myself. My name is Ryan Morrill, and I am a senior data visualization specialist at Forrester. In that role, I’m responsible for creating insightful and engaging graphical stories by exploring the most effective ways to visually represent data and information. I’m really looking forward to sharing my thoughts and lessons learned about data visualization through this blog.
Infographics are popular —or at least the idea of them is popular — and everyone wants to know if, how, and when they should jump on board. Most of the questions I receive from Forrester clients about data visualization relate to "infographics": Should we be using them? How effective are they? What are infographics exactly? How do we make them ourselves?
In a recent media interview I was asked about whether the requirements for data visualization had changed. The questions were focused around whether users are still satisfied with dashboards, graphs and charts or do they have new needs, demands and expectations.
Arguably, Ancient Egyptian hieroglyphics were probably the first real "commercial" examples of data visualization (though many people before the Egyptians also used the same approach — but more often as a general communications tool). Since then, visualization of data has certainly always been both a popular and important topic. For example, Florence Nightingale changed the course of healthcare with a single compelling polar area chart on the causes of death during the Crimean War.
In looking at this question of how and why data visualization might be changing, I identified at least 5 major triggers. Namely:
Increasing volumes of data. It's no surprise that we now have to process much larger volumes of data. But this also impacts the ways we need to represent it. The volume of data stimulates new forms of visualization tools. While not all of these tools are new (strictly speaking), they have at least begun to find a much broader audience as we find the need to communicate much more information much more rapidly. Time walling and infographics are just two approaches that are not necessarily all that new but they have attracted much greater usage as a direct result of the increasing volume of data.
Lately, there are so many cool Infographics popping up, with lots of global information. Yesterday I shared a link to an infographic from the World Bank. Today, you'll find a link to a tool from the United Nations Development Programme.
By now, most of you know my love for infographics. A colleague recently pointed me to this great tool of the world bank: The World Bank Data Visualizer.
It has it all: data for 209 different countries, trending, and customizable axes. This is a great tool for everyone who's doing global research and wants to know more about the countries researched, and how they relate to each other.
When you regularly have conversations with your colleagues about social media activities, the platforms, and the impact on consumers you might find this 'Conversation Prism' graphic useful. Brian Solis and Jesse Thomas of JESS3 build this helpful chart that shows the activities and the networks that make the Social Web.
This is a follow-up video to the one I posted last week about how technology has changed the world. This video shows how consumers' use of these new technologies affects traditional media channels and communication patterns.