This past summer our beloved daughter, Annie, was married to our new, very favorite son-in-law, Douglas. There were bubbles blown by the guests as the bride and groom finalized their vows, and flowing Champagne (lots and lots of Champagne). It was everything we hoped for in every way imaginable. Quite simply, in the words of our sweet girl, “the day was perfect.” Indeed it was.
Now, dear reader, you know where this is going… all those bubbles got me thinking about the bubble charts I see in my work with clients. Alas, unlike Annie and Doug’s wedding, they’re not so perfect.
Consider the following example that was on a Hospital Report Card I recently received:
My initial reaction upon viewing this display was “WHYYYY???? (imagine my whining tone for emphasis).
Why would anyone display data in this manner?
I have a couple of guesses: it’s eye catching and “fun.” The software lets you do it, so it must be right. While those may be real factors governing the creation of this display,
that doesn’t mean they’re acceptable, or in accordance with data visualization best practices. Here are a few reasons why:
- Not all of the bubbles are clearly labeled with the category of data being displayed, nor could they be, given the size and spacing of each one.
- Even if the first problem could be remedied by the addition of a color-coded key, the key would be so long that no mere human could ever hold all of its information in short-term memory while viewing the display.
- The colors are certainly bright and shiny, but they’re also distracting, and add no value to the viewer’s overall understanding of the data.
- The value of each category of data is not labeled, and it is difficult (if not impossible) to make direct comparisons between one category value and another.
- Categories can’t be ranked or ordered in any logical way.
As always, our first and over-arching objective must be to show the data and the story in it.
Enter the far less showy and oh-so-sensible, ever-practical bar chart. Displaying data using a bar chart affords us the ability to show the entire label for each value. Additionally, with the use of only one color, the viewer is no longer distracted by trying to understand what the different colors mean (nothing), and instead can see the shape of the data. It is also possible to directly label the value of each bar being displayed, and to rank the results or display them in some other potentially meaningful way, such as alphabetically by category.
Now let’s consider another scenario where bubbles hinder our ability to show the data clearly and in context.
Imagine that we have been asked to create a display for a provider group that delivers services for patients (male and female) diagnosed with reproductive issues. The display needs to include the number of cases in each category for:
- the current month,
- the year to date compared with the previous year to date and the difference, and
- a twelve-month rolling trend.
For this example, let’s also assume that we are displaying data by calendar year, and that the last month of available data is for June of the current year.
Employing these techniques, we can use our label once and display the current month’s case count, followed by year-to-date versus prior year-to-date, and the 12-month rolling trend. Now the viewer can easily see that there are more cases for male than female in the current and year-to-date data, and that this seems to be an ongoing trend.
I know, I know: bars are boring; bubbles are fun. But that is not the point. The goal here — always — is to convey the data in a clear and compelling manner that will make the story in it stand out, and move people to inquire further, learn something new, and when appropriate take action.
If all the same you’re really feeling the need for some fun bubbles, I’ve got a case of leftover Champagne that I’d be thrilled to share.