Data visualization guideline
I had an opportunity to be a part of an eCommerce environment as a project manager while being slightly obsessed with figuring out what makes people use, or not use, certain products, the effectiveness of the campaign and which factors are involved into buying decisions. Also, I love data visualizations – I can spend an eternity on tweaking fonts, colors, lines, and texts until the visualization inclines with the conclusion.
In the last several years though, something’s been bothering me. Even while more and more organizations are getting into data visualization, there still appears to be a hesitation among some to embrace visual design in reporting which many see as diminishing the legitimacy of reports. On the other hand, I saw many organizations embracing data visualizations in every part of their structure and using them for everything, whether or not they helped communicate the data.
The real challenge is that we just don’t have enough study to tell us would it make a difference to "improve" our reports by adding data visualization to it which makes it's scaling a challenge.
One of the helpful guides I found years ago was a checklist checklist by Stephanie Evergreen & Ann K. Emery , which is a practical measure of the quality of data visualizations which we can use it for our research. It was made so that we can use it to make our own graphs better while comfortable with our work. The checklist is the most reliable measure of data viz quality I could found. If you are interested in the study this guideline was built on, you can read it here.
Even though I couldn't find a report which clearly shows the direct connection between the use and quality of data viz and use of reports, I did find that reports more like guided and proofread were used more than any other. You love data visualizations, that’s why you’re reading this article. And I know you believe that good data viz makes a difference, otherwise, you wouldn’t bother doing your graphs as good as they can be and that is the reason I would love to encourage you to try the checklist out.
If you want to make sure you understand well the guidelines and how to use them to rate a graph, then take the interactive training for a ride here