Explore & Engage

Practice makes perfect. The more you create data visualizations, the more comfortable and the better you’ll be.  Don’t be afraid to experiment. Here are some activities and tips that will give you opportunities for applying and building your data visualization skills. 

Action – Learn to choose before you learn to create. Learn to create simple before you create complex. 

1. Learn which visuals to use when. Start by learning which types of charts, graphs, or other forms of visuals are best for showing which type of information. You can find hundreds of infographics, articles, and even pre-built ‘recommenders’ inside data tools that will guide you on which visualizations show which types of data findings best (e.g., bar charts are usually best for findings about data taken at a single point in time while a line chart is better suited if the data is from multiple points in time.). These tools do require that you first know what relationship or finding that you are trying to show – this is why your data translator skills that we talked about earlier are so important. Practice translating your findings into the visuals that are best suited to sharing that message.
2. Learn which visuals are best for people analytics. Use your data consumer skills to review the work of other people analytics professionals and pay special attention to how they choose to show their data visually. By reading articles, attending conferences, or networking with peers, you can learn the types of visualizations most often used in people analytics. For example, radar chats are often used for skills, alluvial diagrams for employee movement, waterfall charts for displaying headcount changes in relation to hiring & attrition, hierarchical displays are often used for org charts, skill maps or organizational network analyses are usually shown on a graph, and more.
3. Start simple. Learn to make simple visuals well first. Don’t try to create complex charts, graphs, dashboards, reports, or infographics right away and don’t move on to making complicated visuals until you are sure that you have not only mastered how to create the visual but how to do so while incorporating design and accessibility principles well. Those aspects increase in difficulty as the visual increases in complexity. Begin with basic charts like bar charts, line charts, and scatter plots. Then move to more complicated visuals like plotting multiple variables in a single graph, flowing changes over time, animations, interactive dashboards, or graphical mapping.

Action – Follow the Experts 

1. Leverage Existing Design Principles: Learn basic design principles like color theory, composition, and white space. These principles will help you create balanced and visually appealing charts and graphs.
2. Use templates and tools (with caution). Many data analysis and presentation tools offer pre-built templates and style options. These can be a great starting point and provide a solid foundation for your visualizations. Just be careful, while tools and templates will have pre-built visuals, they can never know what the important story or message is. Often they will even recommend the worst possible visible for your purpose. Using templates and tools requires that you first have the skills and ability to choose the appropriate visual for the message that needs to be conveyed.

Action – Learn About Visual Accessibility Standards

It’s critical that your data visualizations are accessible to everyone, regardless of visual abilities. In many cases, it is required for them to be so, but accessible data visualization isn’t just about compliance – it’s about inclusivity and ensuring everyone can benefit from the insights your visualizations reveal.

1. Learn about color. 
   1. Always ensure adequate color contrast between data points, text, and the background. Tools can help you check contrast ratios and identify color combinations that meet accessibility guidelines. Or, just simply place your image far away or at a very small size and see if you are still able to distinguish aspects. Don’t forget to view your visuals on various types of displays and resolutions.
   2. Many people experience various forms of color blindness. If you are not one of them, find resources online to first learn about how those individuals experience color to increase your understanding and empathy (e.g., look up images that show what items look like to people with different types of color blindness). Then be sure to use color palettes designed for accessibility or avoid relying solely on color to convey information.
2. Learn to design for different tools.
   1. Every visual element should have clear and concise alt text that accurately describes the information being presented. This acts as a voiceover for screen readers and users who are blind or visually impaired.
   2. If your visualization is interactive, ensure it can be navigated and understood using keyboard navigation and use clear focus indicators to show which data point or element is currently selected, so it can be used with assistive technologies.

Action – Play the “What Does This Tell You?” Game

This is possibly the single best thing you can do to ensure your visual conveys the story you intend and that it does so clearly. All you need to play is your data visualization and a person willing to play the with you. Here’s how you play:

1. Create a visual. Keep in mind exactly what you believe it should ‘tell’ people and what the most important thing they should learn from it is.
2. Show it to your other player and ask them to describe what they know from the visual to you. The rules are:
   1. You cannot answer any questions. If they ask “what does this mean?” you can only respond with “what do you think it means?” Take note of what they were confused about and what they think it means. You are going to want to explain it to them, don’t!
   2. Repeatedly ask the other person “what else do you think this visual is telling you?” over and over until they can’t think of anything else. Yes, this can get awkward, but don’t cheat! Take note of their responses.
   3. Once they can no longer identify anything else about the visual. You may ask one additional question but only if they have not made any mention of the most important item that you wanted them to notice. If they made no mention of the topic at all, you should ask them, “did you happen to notice anything about ___, what do you think it means?” But don’t mention the finding you wanted them to see, only the topic and see what they tell you. Take note to see if they can come to conclusion you hoped for with this question.
   4. Take notes of every response they give you. Mark every response in one of three ways a) they correctly interpreted what was intended, b) they incorrectly interpreted what was intended, c) they did not notice or did not accurately/fully understand what was intended.
   5. Take your notes and go update your visual. Here are some tips for how you might want to update your visual based on how the other player responded:
      1. Was the person confused and didn’t know how to read your visual? If so, consider whether you may have had too much stuff on the page and need to make it more clear with more white space. Alternatively, you may have chose the wrong type of chart; was it a bar chart when it was about change over time and a connected line graph would have shown change over time better? Or maybe you used 3D effect, a bubble shape, or pie chart and that made it too hard to see small differences.
      2. Did they ask you any questions? If so, consider the best ways to answer them visually. Do you need to add a legend or label your axes? Make sure that your next version directly answers they had.
      3. Did they mention a finding that wasn’t important or relevant to your main message? If so, add elements like color, outlining, or bolding to your visual that draw attention specifically to where you want it to go.
      4. Did they get your main takeaway but only after you prompted them by asking if they noticed it? If so, consider adding a title that states the main takeaway.
   6. After you have finished updating your visual repeat the game, with a new player if possible. If you plan to continue playing with the same person, make sure not to answer any of their questions in the first round and do not tell them what you are hoping they will say. (Keep in mind, this game may drive many of your friends crazy; they will want to know what they were supposed to find out from the data.)

Tip. While aesthetics are important, this game is all about prioritizing clear communication of the data. The way to ‘win’ is to ensure your visuals are in the correct form for your data, easy to understand, and that they neither overload your viewer with too much information nor leave them without enough information.