In this interview, our guest Kent Eisenhuth, Staff UX Designer for Google shares his tactics for how to organize data & insights for maximum impact as well as storytelling principles for how to clearly and effectively communicate with data.
Kent is a speaker in RETHINK Mentorship Program: Storytelling to Influence Change where he teaches a workshop about how to tell impactful stories using data.
See program details and apply here
Thank you for having me.
Let's start by learning a little bit about your story. How did you get interested in how to communicate effectively with data visualization?
My father was a high school geography teacher, and he taught me how to read maps at a very early age. Because of this, I’ve had an interest in maps dating back to my early childhood. I just loved how shapes, symbols, colors and other graphical elements were used to describe physical locations.
Fast forward to the early part of my career, and I was making a switch from working in advertising to product design. I worked at Electronic Ink, a consulting firm in Philadelphia. At the time, a lot of our solutions involved some sort of visualization. Once thrown into the work, I realized it was something that came easy to me, and I really enjoyed it. Later on, after joining Google, I was lucky enough to have an opportunity to focus on designing maps, graphs, charts and visualizations full time. The rest is history.
What is the most difficult part for you when telling stories with data?
For me, it’s all about understanding the underlying data set and evaluating its reliability. Is the data accurate? Is it updated on a regular basis? Is it coming from a reliable source? Who is maintaining it? Is the data continuous? Are there gaps in it? This was especially challenging when I was working at a consultancy. All of these factors contribute to one’s trust in the underlying data set and the chart’s ability to communicate information that supports a larger story.
Accessibility is also a fun and challenging space. Meeting compliance has its own challenges, especially when it comes to the visual presentation of the information. Thinking about ways to provide glanceable insights to someone who is blind or has a vision disability is also a difficult challenge and one we’ve been thinking about for the last two years.
What are some of the foundational lessons you’ve learned about how to clearly and effectively communicate with data?
First and foremost, I like to think about how the data will be used and how it will help someone achieve a goal or complete a task. Next, I try to think about questions people will be asking of the data along the way, and which metrics are essential to answering these questions.
For example, getting ready to leave your house is a task. You may look at the daily weather forecast to understand how to dress appropriately. Metrics like hi and low temperatures and precipitation amounts will help you determine what to wear. Will you need a jacket? Will you need an umbrella or sunglasses? Well crafted visualizations in a weather app can help you make these decisions quickly and complete the task of getting out of your house.
Thinking about questions people are asking of the data will help you determine what charts to use, and how to design them in a way that will quickly provide answers. I cannot stress the importance of keeping it simple. Using charts that people are familiar with is essential. Overloading a single chart is problematic. Sometimes it’s better to use multiple charts to show the same information. Next time you’re thinking about using a line chart with a dual axis, ask yourself if it’s absolutely necessary.
What tactics do you have to organize data & insights for maximum impact?
Understand the core purpose of the chart
It all goes back to the purpose of the chart and how it's used. For example, an analyst may be interested in exploring data. If this is the case, the visualizations should have prominent affordances for exploring the data.
In other cases, we know the questions people are asking of the chart. For example, when looking at a stock quote, we’re interested in the performance of the stock. Is it trending up or down? In this case, we can highlight unexpected spikes, dips and trends in the stock’s performance.
In other cases, visualizations are used to support an overarching narrative. For example, an executive presentation may highlight product sales for the last 4 quarters. In this example, the visualization’s main takeaways may be annotated and highlighted for the viewer. These are just a few examples of how charts, graphs, and visualizations are designed around their core purpose.
Use real data
It’s easy to create a mockup of a chart or graph in Figma. Working with actual data will help you understand the order of magnitude you’ll be working with. It will help you understand the constraints and limitations of the dataset, which will inform the design of your visualization. It may also help you choose a chart.
Keep it simple
Again, using familiar chart types is essential. Not overloading one single chart with too much information often maximizes its ability to provide glanceable insights.
What are your guiding principles for using storytelling with data visualization to help influence decisions?
Edward Tufte’s six principles for graphical integrity have always worked for me. These include facilitating comparisons, showing causality, building multivariate experiences, providing context, integrating different modes of information, and establishing credibility by providing documentation.
These principles have always helped me craft data experiences that support rich storytelling, which leads to more well-informed decisions. For example, I’ve created several data experiences for people, developers who are creating, launching and maintaining mobile apps that run on a Cloud. In a lot of cases, these visualizations are used to help a developer determine the root cause of an incident. Visualizing a timeline of alerts that show when incidents occurred was a nice start. It gave developers an understanding of when and how many alerts were firing.
Stacking other charts that show changes in CPU utilization, Memory usage, and other key metrics over the same span supercharged this idea. This is an example of how we made a multivariate data experience that prioritized the comparison of different metrics. It enabled developers to understand the correlation of key metrics and events leading up to the time of the alert.
I’m also biased, but Material Design’s six principles for designing any chart are worthwhile. These principles are a nice supplement to Tufte’s principles.
Kent is a speaker in RETHINK Mentorship Program: Storytelling To Influence Change where he teaches a workshop about how to tell stories using data.
See program details and apply here
Part of my RETHINK Storytelling to Influence Changes workshop focuses on creating accessible data experiences. Data visualization and accessibility is a gnarly, tangled mess of a design challenge. For the past several years, I've spent countless hours at the whiteboard solving this problem with engineers, product managers, designers and researchers. Drawing helped us make progress on this important challenge. Yes, you can use drawing to solve real problems. This is one of the many experiences that led me to writing Drawing Product Ideas. Drawing can help your team solve difficult challenges. Find out more. RETHINK community gets 30% OFF with code: DPI23 at checkout.
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