In Defense of Infographics


This morning, I was stunned to read an article by Erin Everhart of 352 Media Group alleging infographics 1) display data that sucks; 2) dumb us down more than reality television; 3) are abysmally designed; and 4) have a tarnished reputation because of those that are unsuccessful (Source).


Let’s first examine this argument: “Infographics display data that sucks – even in picture form […] They expect that people won’t understand even the simplest data and put it in picture form that just complicates it even further” (Source).  According to statisticians, putting data in “picture form” actually helps people understand the data more clearly because people can read the story in the data.  David McCandless argues that visualizing data helps us “see the patterns and connections that matter” (Source).

Most data isn’t simple.  When we hear that Americans donate over $300 billion a year to charity, our minds cannot grasp how much money that is unless we can visualize it.  David McCandless lets us see how much money $300 billion is… by making it an infographic and comparing that amount to other amounts:


When we can visualize $300 billion, we can understand the data.  Without the visualization, $300 billion is just a number – a really, really big number.  The data doesn’t suck; it’s actually extremely important – as it most data.  But we don’t understand the data until we see the visualization.

Everhart says, “I blame infographics for dumbing us down even more than reality television” (Source).  Reality television is 100% consumption.  We sit on our couches, shut off our brains, and decay.  Infographics, on the other hand, require actual mental activity.  Infographics help us process information, so when we view one, we learn and grow; our minds are working.  According to Edward R. Tufte, author of Envisioning Information and The Visual Display of Quantitative Information, “Often the most effective way to describe, explore, and summarize a set of numbers – even a very large set – is to look at pictures of those numbers” (Source).

So let’s do some TV watching to test Everhart’s theory, shall we?  If infographics “dumb us down even more than reality television,” let’s watch the TED Talk below.  It will take you as much time as an episode of a reality TV show:


I can 100% guarantee you weren’t “dumbed down” by watching David McCandless.  Quite the opposite: I guarantee you learned more from one of his infographics than you have from any episode of The Real Housewives of Beverly Hills (or from all of RHOBH episodes put together).

The third argument is that infographics are “abysmal.” Everhart says, “If your infographic contains clip art, pie charts, bar graphs, or an abundance of typography, go back to the drawing board” (Source).  I agree with 2 components of her argument,  First, clip art should not be used for an infographic (or for visualization of any kind, for that matter).  Secondly, pie charts can be retooled into something greater.  John Tukey was responsible for infographics and data visualization as we know it today.  Tukey does argue that data displayed using a pie chart can be reworked and displayed better using another visualization format.  Similarly, Edward Tufte writes, “Given their low data-density and failure to order numbers along a visual dimension, pie charts should never be used” (Source).

However, bar graphs and typography are essential parts of data visualization that help us better understand complex data.  Need proof?  Consider both in the TED Talk “Hans Rosling shows the best stats you’ve ever seen.”  Watch Rosling’s beautiful and exciting bar graph here:


Rosling proves that bar graphs work, and he proves at the 4:00 mark that infographics are far from dull, boring, and lifeless.  According to Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, Nathan Yau, self-proclaimed “data junkie” and PhD candidate in statistics, explains, “Charts and graphs have also evolved into not just tools but also as vehicles to communicate ideas” (Source).  We understand from reading Yau’s book and seeing over 300 pages of examples that “different visualization tools use different data formats, and the structure you use varies by the story you want to tell” (Source).

Typography refers to “the art and technique of arranging type in order to make language visible” (Source).  Obviously, without visible language, understanding most infographics would be impossible.

Everhart’s final argument is that, “Infographics aren’t all bad but enough of them have been done so blatantly bad that it has tarnished their reputation” (Source).  I haven’t seen too many bad infographics, but even if I’d seen 99 bad ones, this one by David McCandless would convince me that no, infographics’ reputations are not tarnished:


Do you think infographics are dead?  What other arguments can you think of to support data visualization? 

*Thank you to Erin who corrected my misspelling of her name!  It is “Erin Everhart”


8 thoughts on “In Defense of Infographics

  1. Nice rebuttal, Alex. Always love hearing other marketers’ thoughts, especially about infographics because they’re such a hot topic in digital marketing nowadays.

    I think my main point of the article wasn’t articulated: I don’t think infographics are terrible. And my points really only apply to those that have failed and why they failed. And more likely than not, they fail because they don’t have good data to back them up, they’re poorly designed, and people don’t properly promote them. There are some seriously fantastic infographics. David McCandless and Edward Tufte are among those. But there’s no denying that there is an infographic about everything, even if it doesn’t make sense to visualize it.

    And if we want to get technical, it’s not really the infographics fault. It’s the people who do them half-assed. The Black Hat and lazy marketers who don’t put in the time to make the infographic properly. A better title for the article would have been Why People Fail at Using Infographics for Link Building.

    Also, it’s Everhart (no e) :)

  2. NB.

    Visual displays of information are not all terrible, of course that is ridiculous. But if we narrow the definition ‘infographics’ to the current fad for either:

    —using what is nominally data to create pretty patterns (see the site ‘Visual Complexity’, ever reliable source for this junk) or,

    —for ‘the single PNG file that tells you everything you need to know about the oil industry/tax spending/voting habits etcetera with bar charts made of wood type fonts pointing at coloured maps that that will go viral on Facebook and get me a job at the NY Times’

    then Erin has a good point. McCandless’ idiotic Billion thing is a prime example. That bloated, ink and pixel hungry monster is nothing more than a list of costs! His idiotic claim that ‘people struggle to conceive of big numbers’, while true, is not served by his graphic solution whatsoever. People may well struggle to conceive of what a billion dollars is, but there aren’t many that will struggle to conceive that $5 billion is five times more than $1 billion. So the graphic is worthless in that regard.

    The graphic only shows data in one dimension, that of cost. It does not show cost over time or easily allow for interdata comparison as a bar chart can, nor does it cost as a proportion of a total amount (it could conceivably do that, but then it would be reinventing the pie chart). For this reason the data would be much more effective and easily understood as a list of numbers—there simply isn’t enough data there to warrant the graphic, and the data that is there is more easily understandable and comparable in pure number form.

    Bar and Pie charts do indeed suck—the answer on this stuff does and always will come down to ‘what would Tufte do?’—but even they are more capable forms of datagraphic than McCandless’ junk.

    • Hey Adam! Thanks for your comment.

      Nancy Duarte really sheds a great light on the discussion of data visualization, and her ideas about what works are ideas shared by David McCandless. Duarte tells us that our goal is to show the meaning of the data. We can do that in 5 ways: 1) tell the truth, 2) get to the point, 3) pick the right tool for the job, 4) highlight what’s important, and 5) keep it simple. McCandless believes in these same principles, and his goal isn’t to create “pretty patterns” or to create something for the sole purpose of going viral and getting a job. Check out his idea of what makes effective data visualization at the bottom of the post: “What Makes Good Information Design?” By his own admission, data visualization is about form, function, interestingness, and, importantly, integrity. I’d say this is far from idiotic; in fact, he is designing for how people learn.

      I most certainly don’t think the “Billion Dollar Gram” is idiotic or worthless, and I would completely disagree that a list of numbers could convey the data better than this particular visualization.

      Personally, I don’t know the difference between $1 and $5 billion because those numbers are so high that both are merely abstract concepts to me. Most people cannot understand a billion dollars because it is an amount of money only 1,250 actually have (Source: The goal of a good data visualization is to show relationships between the data; I can definitely see the relationships in the “Billion Dollar Gram.” For example, saying “Google is worth $175 billion” is not understandable at all for me (or for most people who don’t have a concept of that kind of money) until I see the relationship between that amount and other amounts. Seeing the relationships does allow me to form a more clear idea of the amount because I can compare and contrast… something I definitely couldn’t do with a list of numbers. And whether it’s $1 billion or $5 billion… it’s exactly the same to a person who can’t conceptually grasp the sheer volume of that kind of money. We may logically know $7 is more than $5 is more than $1 billion, but that’s all totally abstract when we’re talking about billions of dollars. David McCandless’s goal is to make the abstract concrete by showing those relationships. Again, the goal isn’t to show us the money; the goal is to show the meaning of the data.

      Again, I have no idea how someone might find David McCandless’s infographics “worthless” or “idiotic” or “junk” if the understood goal of data visualization is to show relationships… Can you help me better understand your perspective?

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