Writing this blog has so far resulted in a few new ideas and one big realization: I must get organized if I want to improve the consistency with which I produce effective data visualizations.
- What are the qualities of an effective data visualization?
- Where are my opportunities?
- What are my personal development priorities?
What are the qualities of an effective data visualization? Articulating what I’m trying to accomplish
I’ve always understood the effectiveness of a data viz to be determined by how easily the intended audience is able to interpret the message. I’ve come to think this is an over simplification.
Can a viz be categorized as ‘easy to interpret’ if no one looks at or pays attention to it? If a tree falls in the forest and no one hears it, did it make a sound? What if it gets some attention, but the call to action is lost on the audience?
To be effective, the viz must capture the attention of the audience, be easy to interpret, and persuade the audience to take action. Advancing my own thought process, I consider “attention grabbing” to be a condition for effectiveness and “persuasiveness” to be a measure of effectiveness.
So, there needs to be some element of attractiveness. Oftentimes attractiveness is interpreted as bright colors and flashy design, but we can more effectively attract our audiences’ attention by making the data more relatable. Examples:
- Relate the viz back to the individuals in your audience. ie: by demonstrating where they stand in some measure relative to their peers
- Credit this idea to Steve Wexler. It’s Your Data, Not the Viz, That’s Boring
- Relate the viz back to a matter of importance for the majority of your audience. ie: budget, healthcare, poverty…
Once you’ve captured your audiences’ attention and delivered an easy to interpret viz, how do you know if it was, in fact, effective? Calls to action are not always easy to measure. Sometimes a viz is drawn to elicit emotion or to persuade an audience the author has no direct access to.
In some cases, we have to rely on our own expertise to make an educated guess as to how effective the call to action is. To develop that expertise, we rely on continuous feedback and idea sharing from our peers; which is one key way in which this community is so important.
What are my opportunities? This will not be an inclusive list
Too often I find myself tackling a Makeover Monday dataset from the perspective of, “How can I make something cool that will get a lot of likes?”. More recently, I’ve tried to keep the intended audience in mind as I get started; but, I have found those good intentions to be fleeting.
My lizard brain overrides those good intentions and I find myself caught up in building something impressive; I enter a spiral of trying new things until I either score (rarely) or find I’ve wasted a few hours. It’s not always random trial and error; rather, I often find myself lost in the internet or a data viz book (The Big Book of Dashboards has been my top choice of late). While I’m learning a ton, I realize I’m not retaining as much as I would like and, worse, I’m spending hours on Makeover Monday; in some cases ending up with nothing to publish.
After a few weeks of trying, and often failing, to keep my focus on the intended audience, I realize I must set goals each week. This blog is meant in part to help me organize my thoughts so I can then prioritize what I hope to learn in the near future and set aside time specifically for learning.
GOAL – Set aside separate time for learning new concepts. Focus Makeover Monday time on practice.
What are my priorities? I reserve the right to modify at any time 🙂
- Practice new chart types to give me more flexibility in building a story and making the data more relatable
- Starting with
- Waffle charts
- Bump charts
- Starting with
- Improve the manner in which I use annotations, labels, titles and text boxes to tell the story and highlight my call to action
- Get more creative in leveraging tooltips for added context and drilling home the call to action
- Drill-down info
The plan is to post an update in a few weeks. The hope is I’ll have successfully tackled my top priorities and will have some lessons-learned to share.
While I write for myself, I choose to do so in a public blog so we can learn from each other. If you found this post to be helpful or have feedback, please share. Find me on Twitter @RelatableData and let’s keep the conversation going.
Photo credit: Nick Youngson