It surprised me. And it shouldn’t.
You see, there is nothing wrong in using data for the sole purpose of creating aesthetically pleasing visual objects. On the other hand, if you want to make sense of the data, and communicate your findings, it’s easy to argue that effectiveness should be your primary goal. This is the general model. Too black & white.
When you remove the fog of gratuitous effects (3D is the usual suspect) and you start actually thinking about the data and seeing it more clearly, something bizarre happens. Suddenly the client, who was so enthusiastic about applying more effective data visualization practices, now is not so sure if the charts should be published at all. Suddenly, the data turns dangerous, and it must be managed politically at a higher level.
Suddenly, the colorful lollipop turns into a potentially dangerous match.
Depending on the rules and the context, data should be managed politically. We do it all the time at the personal level. What is interesting (and surprised me when I experienced this for the first time) is to see the client’s reaction, now becoming aware that he was caught off guard. It’s easy to get careless when you use your data to make lollipops.
Then comes the damage control stage. What should we do, what should we do? The knee jerk reaction is to replace the indicator or lie (bad idea), change the way it is presented/calculated (still bad), keep the indicator and add context (better), keep the indicator, add context and explain with annotations (much better).
The politics of data management in an organization says a lot about its culture. If something doesn’t make sense to you, an outsider, you’re probably not aware of it’s political dimension.
Do you find many lollipops-turned matches in your work? Share them in the comments below.
Image credits: I merged two images from the Wikipedia, this one, by Matthias Kabel, and this one, by Bbxxayay.
