A couple days ago, I ran into this post on the Freakonomics blog. Funny, interesting, engaging… I love it. I now refer to the song from #7 as “People the club can handle right now, with the exclusion of me.”
But it’s also wrong.
These song titles were most clearly explained in their original form: text. When they were turned into graphs, they became brain teasers similar to the ones we did in elementary school. Heck, they now require an answer key!
You wouldn’t believe it to look at the graphs that exist in countless presentations, books, etc. but a graph is not a way to misrepresent data, add color to a presentation, or take up space. It is not a redundant presentation of information that was already explained in extreme detail earlier in the information. It really shouldn’t be seen as a complex form of torture invented by nerdy bosses who want to get back at you for the holiday party fiasco, either. Graphs exist to make data easy to understand. Period.
Don’t believe me?
For my next trick, I will turn a ridiculously complex set of information into 3 simple graphs. The social dynamics involved in the love life of a single, extroverted 22-year-old girl, living and working in a large city:
Now let’s compare. This is a discussion that would last 5 good paragraphs in text, or an hour and two cocktails in conversation. After both methods, we would probably need to loop back at some point to refine a point of information.
Explained through graphs, I’m betting it took a maximum of three minutes. Even better, the data is there as a fully thought-out presentation, with no need for the audience to go on a word journey with us. This is what charts and graphs were made to do, and keeping that in mind makes it a lot easier (and sometimes fun) to create ones that are actually useful.
A quick checklist to keep your future graphs on-track:
- Have you already said this somewhere?
- Could your graph be simpler (without losing relevant data)?
- Did it take more time to make the graph than to write the text accompanying it?
- Will you have to spend more time explaining the graph than you spent making it?
- Are there more colors in your graphs combined than there are data sets?
If you answer yes to any of these questions, you’re graphing it wrong. Keep trying and don’t despair! Getting it right when it really matters is something people will notice, and honestly appreciate.