Stephen Few left a comment in my post “Is Data Visualization Useful? You’ll Have to Prove it“. We all have much to learn with Steve, so instead of leaving the discussion buried in an old post, I thought it would be interesting to make it more visible. Please read the comment then come here and join the discussion. Here is my answer.
Steve, sorry if I sound provocative, that’s not my intention. You are the leading expert in data visualization for business, you are doing a remarkable work with your books, with your blog, with your forum, with your patience to answer posts like mine. I have to be thankful for that. And I do agree with 95% of what you write. But you don’t want to be surrounded by people who fully agree with you, do you?
The Effectiveness of Data Visualization
You say “the effectiveness of data visualization is well established by a large body of empirical evidence”. I want to believe that too. However in this study Jarvenpaa writes:
“Graphical charts are generally thought to be a superior reporting technique compared to more traditional tabular representations in organizational decision making. The experimental literature, however, demonstrates only partial support for this hypothesis.”
And J.-A. Mayer adds:
“This study refutes the general superiority of visual information in improving the decision quality (‘naive superiority hypothesis’). The choice and design of visual presentation is determined by information structure, decision environment, the decision-maker and the task decision. (…) The successful use of visual information depends substantially on its acceptance by the manager and the environment.”
What do these authors tell us? First, we cannot be 100% sure about the effectiveness of data visualization. Second, there are many other variables at play. And third, managers must accept it. This is a critical factor. Managers love impression management, and making a good impression using the dreaded “professional-looking charts” is the path of least resistance.
Data Visualization Success Stories
I have no doubts that you could share with us many success stories. When I write about an “admission of impotence” I am not questioning your ability to create/lead/mentor successful data visualization projects. But if you want to use those projects to inspire the average person I think you’ll fail most of the time, unfortunately.
Let me tell you how the layman looks like in my part of the world. He makes charts like this:
He believes that a 3D pie chart “looks more precise” and he doesn’t know that Excel chart defaults can be changed (more advanced laymen are able to switch to more “impactful” colors like reds, yellows and bright greens). In my part of the world, a layman doesn’t even know what “data visualization” is about (and they don’t even care). (Here are some more profiles.)
If you are preaching to the choir your conversion rate may be high. But the layman is not easily impressed. You must convert one at a time, and that’s something many of us can’t afford. Can you? He’ll keep making those pie charts because that’s what his manager requires him to do, he doesn’t know better, he’s lazy or you fail to convince him of a causality effect between better charts and better results.
The Layman Must Like Your Charts
In a business environment, charts don’t have to be memorable, only results do. But if you want to change behaviors, your audience must like the new behavior and accept the unavoidable pain. Likable charts help conversion.
You say “I do not discount people’s emotions”. I don’t see it, I’m sorry. The way I see it, you sacrifice everything to the altar of “chart effectiveness”. I don’t find a single one of your charts where the use of color is not purely functional. You say “you should support your claim with concrete examples”. I do have lots of examples: all your charts!
Let me reemphasized this: I agree with you. Chart effectiveness is what we should aim at. But I’m part of the choir. I’m not the layman. I don’t use pie charts.
Pie Charts Again
Unlike most people, I don’t think pie chart addiction is a disease. It is a symptom of a much more serious problem: low numeracy and poor data management skills. Address this problem and pie charts will virtually disappear.
How do you address this problem? “I don’t use pie charts, and I strongly recommend that you abandon them as well.” Researchers like Ian Spence and Stephen Kosslyn don’t think pie charts are as bad as you paint them. Even if they are, it’s very hard to talk people out of an addiction with purely rational arguments.
Perhaps this is my European soul speaking, but I do prefer a gradual approach (“this is acceptable, for the time being”) whereby people (hopefully) start to develop a sensibility to the perceptual issues.
By the way, how come we keep telling people that charts are about trends and patterns, not about the precise figures and then we argue that pie charts are bad because we can’t tell the difference between a 13% slice and a 14% slice? It doesn’t make sense (I’m exaggerating).
We must find more compelling arguments. I don’t like pie charts just because they are a waste of space (low data density) and can only answer very basic questions, better answered using a table. These arguments are good enough for me. I don’t care if we humans are bad at calculating areas and angles. That’s an academic argument that is irrelevant in the real world (I’m being provocative now…).
To Sum Up
You have a very consistent approach to data visualization and you practice what you preach. You believe that you can convince people using rational arguments.
Mine is a much more comfortable place. I know that eye-candy is a can of worms that shouldn’t be opened. I know that we should protect the layman from himself. I know that simple rules with no exceptions work better than complex rules no one bothers to learn or understand.
But I like the gray areas. I like to protect the poor and the oppressed pies and I try to find their small role in the world of data visualization. The same with eye-candy. The same with emotions. The right amount can get your foot in the door. What is “the right amount”? I don’t know. I’m still searching.