We’ve done quite a bit of research over the last few years into data visualization best practices, and the cognitive psychology of how people best absorb visual information. This two-part series is to summarize what we’ve learned so far, in an effort to help our audience be better communicators, and to foster conversation around making good charts in the planning community.
One thing we’ve talked a lot about in the last year is that creating your visuals in planning (data visualization and plan communications) is a very specific area of study, and discipline.
photo credit: menshealth.com
Communications in business, generally, should be designed for optimal readability by their audience, to cut risk. Miscommunication in business is bad. This means we need to actually put some think-time and design-work into our plan-related communications.
If you and your organization haven’t circled back around just yet, to make sure you’re doing it right, this article might help give you some food for thought on how to retroactively initiate a design phase. Continue reading →
I love this topic because it elicits a higher level of thought around designing the data visualizations we need in planning, in a way that my simple mind can consume.
In her book “Storytelling with Data,” Cole Nussbaumer Knaflic points out very early on that there are really two kinds of data visualizations: exploratory and explanatory. Exploratory visuals are created to help us figure out what the important things are within the data…they have an analytical purpose. Explanatory visuals are meant only to show us the important things…there should be little to no intended analytical value. Continue reading →
Nine. Well, so says Scott Berinato, in his book Good Charts. He bases this number on a conversation he had with Tamara Munzner, a data visualization expert and professor of computer science at the University of British Columbia. Here is an example Gantt chart with more than 8 colors.
…Well, in plan communications and Gantt charts, it does.
Size, when used as an attribute to denote meaning in data visualization, will likely force our brain to look at the largest items first. In her book “Storytelling with Data,” Cole Nussbaumer Knaflic tells us that “Relative size denotes relative importance.”
The marketing industry has played a large role in figuring out how to best get information across to audiences. I realize we’re in the planning-world here…so bear with me, folks.
“Storytelling” is something marketing experts have been talking about for years, as a better way to communicate brands, products, and what sets businesses apart. It’s now a recognized, tried and true approach, and one that has taken a firm foothold due to its effectiveness. Our customer experiences online are, in large part, shaped by “stories” that marketers have set up for us to more easily get to know what they’re selling, and eventually buy it.
Because of this success, storytelling is now quickly making its way into business vernacular, specifically with respect to data. With so much data being collected over the course of doing normal business, we need better ways to communicate that data (the stuff we’re “selling”), in such a way that it can be easily consumed (“buying it”). Continue reading →