A couple weeks ago I spoke to Harvard University graduate students about visualizing survey results. This not at all to very survey scale is quite common in my research circles so I’m sharing our ideas with all of you, too.
Before
Here are some of the survey questions that were asked before and after program participation. Don’t worry, the online survey was formatted much more beautifully than this screenshot from the Word version of the survey!
After
Here’s the first style I tried. I’m not very creative when it comes to making up fake numbers so ignore the exact percentages (which are conveniently identical for all the after results).
- I display patterns over time from left to right across the page. Before results go on the left and after results go on the right, so they get vertical columns (not horizontal rows).
- I convert responses into percentages when there are more than 100 responses and I use raw numbers when there are fewer than 100 responses. In my fictional dataset, there are 200 survey responses, so everything is displayed as percentages.
- The very knowledgeable to not at all knowledgeable scale is ordinal so I selected one hue (blue, or green, or orange) and used darker and lighter versions of each hue to correspond to the amount of knowledge.
- I added a title and introductory sentence to the handout and titles and subtitles to each graph. I’m a visual person and prefer reading graphs over paragraphs but some viewers will prefer reading paragraphs over graphs.
Stacked bar charts are one of the most common ways to display survey results because surveys often include scales like this one. But we have to be careful because one page with two points in time, three survey questions, and five options per survey question can get cluttered, fast! In this version of the handout, I used saturation to guide the viewer’s eyes towards the very knowledgeable sections. In your project, you may choose to draw attention to the not at all knowledgeable category. Or, you may draw attention to both the very knowledgeable and moderately knowledgeable categories lumped together. There are several correct ways to guide eyes with saturation. Your job is to anticipate what your viewers will find most useful.
Want to explore these graphs in more detail? Purchase the Excel spreadsheet and the Word document used to create these handouts.
Purchase the spreadsheet ($5)
Dave Paradi
May 9, 2017 -
Excellent point in the second makeover about using color to highlight the key message.
If you find stacked columns hard to follow because the related segments don’t start at the same baseline, you can create a small multiples style graph that places each set of segments on their own baseline. This can be created in Excel or PowerPoint as a single graph so it is easier to update or re-use. Here is an example I created for the New England History data above: http://www.thinkoutsidetheslide.com/wp-content/uploads/2017/05/SmallMultColumnsMay92017.jpg (sorry, couldn’t figure out how to paste an image in a comment).
Ann K. Emery
May 10, 2017 -
Good to hear from you, Dave! I’ve placed stacked bar charts on the same baseline as you suggested, too. These charts are always so challenging to read so I usually push the chart’s creators/analysts to focus viewers’ attention on just a slice of the information with saturation (the second example here) or to combine a few of the categories together (a later blog post). Or, if they’re sure that every single exact category is equally important, then a table (or heat table) tends to be easier to read than a squished stacked bar chart.
Dave Paradi
May 10, 2017 -
I totally agree with pushing the analyst to determine what the real message is. Often, as you say, they think that every category and data point is important for the audience to see. The reality is that the audience cares about what they need to know in order to make the important decisions they are tasked with making. If we want to get this example truly focused, then we could just show the dramatic increase in the “Very” percentage from before to after and not show the other categories at all. This freaks out so many analysts because they think the audience cares as much about every data point as they do. The reality is that a decision maker sees that dramatic increase in a measurement that is important to the organization and can easily make the decision to continue to support the education initiative. When presenting the results of analysis, the primary focus should be on what the audience needs, not trying to cram every number in.
Carrie
May 10, 2017 -
This is great Ann! I often have trouble quickly deciphering stacked bar charts. The second example is SO easy to read/understand – I’ll definitely be using this!