Data Visualization - enabling action

I'll be speaking next week at the Supply Chain Management Research Center Conference at the University of Arkansas on how data-visualization enables action.

The basic premise (and one I firmly believe) is that the hardest part of any analytic project is not defining the problem, doing the analytics or finding the "solution", it's enabling action. Far too many otherwise excellent analytic projects, tools and reports go unused because the results are presented in a way that is somewhere between difficult-to-understand and incomprehensible.

Manager's typically do not have the time to just figure it out or double check their understanding, or re-work the results to something they can work with.

By making your analytics easy to consume (through good visualization practice) you make it possible for decision-makers to find what is important, understand it correctly and make good decisions, quickly.

Frankly many analytics providers don't try very hard to make their results easy to consume and their outputs are confusing, hard to use, easy to misunderstand and a long, long way from enabling decisions.

For those that do try, there is a tension between making things look "cool" or "interesting" and having them function well. Ideally we want both, but very few examples deliver well on both fronts. Indeed, a lot of the attempts to provide interest seem to be designed to obfuscate or distort meaning.

Here are some examples I plucked from a leading visualization vendor's web site. Each and every one of these charts is difficult to read because of limitations in our visual perception. We'll talk more about that in the conference next week.

And trying to make charts more interesting/attractive/eye-catching typically makes things worse. This "Funnel Chart" (below) is hilarious !. It's being terribly misused and gets almost everything wrong. I defy use to use this and make sensible decisions.

• Color serves no purpose
• It's very unclear whether values are represented by length, area or volume (thank goodness they included numbers)
• The top value is (visually) about 100 times bigger than the bottom one but actually less than 5 times bigger in value.
• I need another legend to tell me where all these regions are
• Why, exactly, is it a funnel ? What does that imply? The NorthEast feeds the South which feeds into Central...
• It has no contextual information. Perhaps Northwest is the smallest because that is our smallest market ?

Here's an example we will be working with in the conference . It's very hard to read, slow to use, easy to make mistakes withand distinctly over-dressed.

And exactly the same data once it's been stripped bare (below). It's now easy/quick to read, practically error-proof, has no distracting "chart junk" and has contextual data (budget) to understand what "good" is.

My interest in visualization is in enabling action from my analytic work. As a consultant, you may think that I get paid whether a client implements my work or not. That may be true, but I like to get paid more than once by the same client.

If you're going to be at the conference next week, drop by and see me: Supply Chain, Analytics and Visualization are among my favorite discussion topics.

I'll be posting more on this over the next few months but if you're looking for more right now, here are some excellent resources:

Stephew Few's blog, Visual Business Intelligence

Kaiser Fung's blog, Junk Charts

Nathan Yau's blog, Flowing Data