a good chart takes time

Last month, I spoke at the GMN Conference in Seattle. Leading up to the conference, I asked participants to send me examples of data visualizations on which they would like my feedback. 

The following was one such submission. The slide was titled "more generational differences."

The title made clear that the graph was intended to show differences. After scanning through the bars, I see by the legend at the bottom that I'm looking at Baby Boomers in red and Millennials in blue. Now that I've deciphered what I'm looking at, my eye scans back up over the bars to look for interesting differences. I see a big gap in the proportion who have created social network profiles. And some other gaps. I've been able to come up with a couple interesting observations, but it's taking some time and I feel like there might be more nuanced insights that I'm overlooking. I think we can remedy this (and also reduce the burden of work we're putting on the audience) by making a few relatively quick changes.

Here's my makeover:

Here's an overview of the changes I made and why:

• Title and legend: Every graph needs a title! Think of it as an introduction to your audience (audience, meet my chart) - it ensures they know what they're looking at. This also frees up your slide title to call out something more interesting than the title of your graph. In regards to the legend: in Western cultures, most people read from left to right, top to bottom, so by placing the legend at the upper left, we make it so the audience encounters how to read the chart before they get to the actual data. It's a nice thing to do, and makes it so the audience doesn't have to search to figure out what's they're looking at.
• Color scheme: the bold text and red and blue series on the original graph are all of similar strength, which means they're all vying equally for the audience's attention. In the remake, I've provided a visual order of priority through the colors. I drew the audience's attention to the Millenials trend in blue, made the Baby Boomers trend grey, so it's still there for comparison but isn't competing for attention. 
• Text: I found the bold text in the original version distracting, so cleaned that up and also right-aligned the labels and made the spacing such that each label would fit on one line (trick: you get more flexibility in Excel by having your labels in cells in the worksheet, rather than on the graph directly; just be careful that your labels line up correctly with the data). I also labeled my x axis (% agreeing with statement) to make it clear to the audience what they are looking at. (Every axis needs a label!)
• Order: It wasn't clear to me that there was an intentional scheme to the ordering in the initial graph. I played around with this a bit. Since the original slide title called out the difference, I decided to actually show that on the graph and arranged the information in descending order of difference.

It turns out that the original chart is what you get if you put the data into Excel and let it create a chart for you (I realized this when I initially graphed the data - it looked just like the original chart, with the exception of the bold text - that was an explicit choice). 

Creating a chart in Excel should be considered the first step of your data visualization process, not your last.

Once you have the initial graph, look at it. Think about the point you want to make and how you can make that point clear to your audience. Draw attention through explicit use of color. Push things that don't need to draw attention to the background. Basically, play around with emphasis and de-emphasis. Label everything. Think about whether there is an intrinsic order that you should leverage. 

A good chart takes time, but it's time well spent if it allows you to draw better insights or make a point to your audience (and hold their attention long enough to make it!).