Stephanie Evergreen’s research-based approach to data visualization and design make her a sought-after speaker and consultant for organizations. An interview in twelve questions. Stephanie Evergreen: ’’Powerful, effective data visualization is not just for the tech types or the programmers. Everyone can present data effectively’’.
Graphic Hunters: What is the power of a good visualization? In what way can a visualization help to understand or to communicate information?
Stephanie Evergreen: Good visualization can change the conversation. Clear, effective communication can illuminate patterns and trends that lead to faster decision-making and action. When this happens on a large scale, we are taking about culture change.
I have read that someone has to understand a visualization within seconds, others say visualizations should leave something to explore. What is your opinion on this?
It depends on the purpose of the visualization and what the audience expects. Most of my audiences are paying a researcher or consultant to find out answers, based on data, and report it succinctly. They want to know the bottom line so they need to understand the visual fast. And sometimes that can lead to more questions for exploration. But that’s a different audience and purpose than presenting data as an art form to be explored.
What is the first most important question one should ask before starting visualising the data?
What’s your point? I elaborated on this here. The answers drive everything from the graph type to the title to the colors to the dissemination.
What tools are important to learn when you want to work with visualizations?
Pencil and paper first. Sketching out ideas is where you work out logical errors. Then jump on a computer. I’m platform agnostic but I do believe you need to be a master of the software you choose to use so that you can maximize its visualization capabilities. I use Excel and find it to be the most flexible, accessible platform out there.
What is the role of design in a visualization?
Beautiful interfaces have been correlated with greater usability. In other words, better design and usefulness go hand in hand. Applying design principles can take a graph from confusion to perfection.
What is the secret on how to balance design, data and the story?
If I tell you this now, why have a workshop?
What’s the biggest mistake often made in visualizations?
Assuming that the defaults are sufficient. No visualization program can do the thinking for you. No program can analyze your data and figure out the story you need to tell. You’ll always have to manipulate the defaults.
Who needs data visualization most and doesn’t know it?
The low budget nonprofit, fighting for more funding, without the funding to get data visualization training.
You have a research-based approach to evaluation and design. Can you tell a bit more about this approach?
My dissertation pulled in research from a dozen fields to create a set of design guidelines. This is a fresh approach because much of the design and even data visualization world makes choices based on personal aesthetic preferences or, at best, what those with more experience feel is good or bad. I prefer to make decisions about data and visualization based on what research shows people can interpret with accuracy. Thus I usually ditch the visualizations that lean more toward art because they lack interpretive power.
I read on the RAD Presenters Podcast that you teach people how to become presentation rockstars so that audiences give a damn about what they say. When does the music start to play in a presentation?
Haha! It plays in your head the whole way through.
What is the most frequently asked question in your training sessions and what is your answer to this?
“Now that I have to remake everything I’ve ever done, I’m overwhelmed by the task. Where do I begin?” Answer: “Start by making great titles. Then think about color. Then think about whether you have the right graph type. Start somewhere and change one thing at a time.”
What lessons do you want the participants to take home for the training?
Nondefault graph types often support the data’s story the best, we just need to learn how to make them. We can make them using tools we already have access to. Powerful, effective data visualization is not just for the tech types or the programmers. Everyone can present data effectively.