In 1989, during my first internship (don’t even dare asking), I discovered and toyed for days with a mind-blowing machine: an plotting table. It was like a printer, except that it was moving a dozen of color pencils over the paper, and it was meant to draw… graphs, as it was called in the 80’s.
Then in the early 90’s, hipsters of that time decided that graphs weren’t cool enough, and called them charts. On an unrelated note, charts started being printed on regular printers, and boredom killed millions of interns.
Then in the mid-00’s, the art of plotting/graphing/charting data was re-named… data visualization. The course of mankind was changed forever, or at least for the next decade. On the same unrelated note, as data visualizations went online, surfing the web dramatically decreased the interns mortality rate.
So here it is: ‘data visualization’ is the new cool name for ‘chart’. And that’s what we do at qunb: we help people tell compelling stories with their own data by instantly letting them create simple, meaningful, interactive charts.
But in the early 10’s, infographics emerged, and the man in the street started getting confused: “Well, he said, is infographics the new new new name for charts“?
Infographic is not another name for Data Visualization
An infographic is a picture, it’s made with a graphical design package like Illustrator, not with a data analysis package. It’s usually embedding several sub-images, aiming at delivering a specific message. But a picture is worth a thousand words, right? So here is an infographic… about infographics:
Next time, be prepared for the infographic of infographics of infographics
The 4 Reasons To Hate Infographics
#4. Most of them focus on form rather than substance
Infography is the art of replacing the dusty old line chart representing a population size with those guys:
One guy means ‘not many’, while 10 guys means “many many”. How cool is that? Well it is, really, it’s self-explanatory, and it’s bringing illustration and concepts into the data visualization.
Yet, it has been totally overused and misused by most of the infographics designers, who systematically started replacing any simple data visualization with symbols found on The Noun Project. Not only for the best…
So today a shitload of infographics look like an art project done by a 6-year old. Like this one:
“Honey, look what our little Kevin did at kindergarten today!”
#3. One page to tell a story? Really?
I’m a repented consultant. Long story short, my job was to create and tell data stories for my clients. And the slideware 101 rules to make any story intelligible are the same in any consulting firm: one page, one message. No exception. Can’t make it? Means you haven’t worked enough. Still can’t make it? Die in fire.
“To hell with it“, said Mister Infographer, “it’s way cooler to put everything on the same page“. OK then, that must be true, as it comes from someone wearing thick-rimmed glasses. And here is the result: 90% of the infographics out there are baroque, non-selective compositions of facts.
“To hell with the story arc as well“, also barked Mister Infographer, “let the reader decide by himself what he could take away from my undirected one-pager“.
“Oh shit, Illustrator got drunk again.”
#2. Infographics ask too much to your brain
Look at this infographic for 10 seconds:
“I somewhat feel much smarter and very dumb at the same time.”
Now, tell me: what’s the takeaway? None. Your brain CPU got high for 1 second, then you dropped. There’s nothing in this representation that’s catching your eye. Mister Infographer decided to present all the information, rather than select one noticeable fact and present it to you.
Most infographics are just an experimentation to condense a whole set of information into one single page, rather than performing the difficult task of selecting the useful facts, simplify them, and sort them into a meaningful sequence.
#1. Infographics are not DIY
Not a Adobe Suite master? Die in fire.
Of course, we DO love SOME infographics
Take that one for instance, that’s been published the day when Microsoft bought Nokia.
No baroque composition, a simple message, a sober-minded use of icons, and a clear takeaway. Good food for thought. Faultless and to the point…
Now, The 4 Things We Believe In
We believe in simple charts, like bars, lines, pie charts, or maps. The ones that anyone immediately understands. We believe there are some patterns in the way any specific analysis should be presented, and we are working on automating those patterns to make data storytelling accessible to anyone.
This sounds like the perfect introduction for a shameless plug…
But if you want to take the long road and read about what we believe in:
#4. You should talk to my eye, NOT to my brain
As amazingly described, information processing in the human’s brain is divided into 2 systems, poetically named System 1 and System 2.
In System 1, the processing of information is performed by our sub-concious. It’s uncontrolled, always-on, and effortless. In System 2, information processing is performed by our conscious mind. It’s controlled, but requires efforts to engage.
System 1 is “the eye”, and System 2 is “the brain”. Every data visualization should talk only to System 1. To that extent, the perception of values should only involve decoding lengths and 2D positions. While the perception of relationships should only be based on visual representations of items enclosure, connections, proximity or – at most – shape.
Representing object of different sizes is NOT the most efficient way to give perception of values.
#3. Simplify, simplify, simplify
Ever heard of the data-to-ink ratio? If so, skip this. Otherwise, take 10 seconds to look this animated gif. Trust me, it will change your life.
“And now I see”, thanks to DarkHorse Analytics
#2. Data storytelling is about simple messages, one at a time
Don’t overload me with too much information. Give me one simple message at a time. A simple message is just an assertion. And make sure I got it before walking me the the next message.
This is why at qunb we let you build data stories as a sequence of charts, and we make help you to squeeze each of them to extract a simple message as a takeaway for the reader.
#1. Data storytelling should be accessible to anyone
Anyone – not only experts – should be able to tell compelling stories based on their data. Turning to someone who knows should soon be history. That’s our mission at qunb.
Data storytelling for beginners, starting with Google Analytics
Right now we are focused on addressing the Heads of Marketing and Sales having trouble with their weekley reports, not “everyone with a data storytelling problem”.
Our very simple value proposition right now: “Make Google Analytics reports simple and understandable for everyone”. But this is just a start! We want to open next a SalesForce 1-click report, and in 2014 we want to visualize and understand any Excel files.
Right now we’re still collecting feedback on the problem our Google Analytics data story solves, and would love you to try it out and shout at us.