The last few years have seen an explosion in new ways of visualizing data. There are new classes, consultants, startups, and competitions. Some of these new and more “daring” visualizations are great. Some are not so great – many “infographics” are more like infauxgraphics.
In everyday business intelligence (the “real world”), the focus isn’t on visualizing information, it’s on solving problems, and I’ve found that upwards of 95% of problems can be addressed using one of three visualizations:
- When you want to show how something has changed over time, use a line chart.
- When you want to show how something is distributed, use a histogram.
- When you want to display summary information, use a table.
These are all relatively “safe” displays of information, and some will criticize me as resistant to change and fearful of experimentation. It’s not fear that keeps me coming back to these charts time and time again: it’s for three very real and practical reasons.
1. Spend your energy on selling the message, not the medium
One of the primary points of a visualization, as opposed to dumping raw data, is to distill a message for an audience that’s less familiar with both the content and the methodology involved. People have a limited ability to ingest information in a given window of time – would you rather they focus on the story you’re trying to tell with the visualization, or the substance of the visualization itself?
Most people intuitively understand line charts and tables – you can safely put a well-constructed (with legends, labels, etc) timeseries or summary table in front of most people and not have to worry too much about whether or not they understand the medium.
Many people are familiar with the notion of a histogram as well, but sometimes more explanation is required. It gets a little complicated, because a histogram becomes much more powerful when you pair it with an understanding of normal distributions, standard deviation, etc. Still, it’s not a hugely complex thing to tackle – you can explain the visualization and the underlying concepts to a layperson in five or ten minutes.
Almost anything more complicated than these three takes some explanation. If it’s a really great chart, it should take less explanation and be worth it; my experience, however, is that in the vast majority of cases it’s not worth the mental “tax” of new visualizations.
2. Your job is to solve a problem, not make a picture
The job of the New York Times graphics department is to tell a story using graphics, and they turn out some great work in pursuit of that goal. On the other hand, the job of an analyst for a business is to solve a problem and move on to the next one.
You can spend days, weeks, or even months working on visualizations of data, but does that benefit the business most? In most cases, a simple visualization will get the job done and free you up to solve the next most pressing problem that the business has.
3. Safe doesn’t mean boring
Just because these tools are well-worn doesn’t make them boring – you can do incredibly innovative things just with line charts and histograms.
One of my favorite charts that has been published here on Signal vs. Noise was a set of histograms comparing the time of git commits across the various people at 37signals (The rhythms of 37signals). This is nothing more than a stack of identically structured histograms, and it didn’t take a long time to make or require much explanation.
What three charts would you take with you on a desert island?