The work of creating data visualizations (data viz) attracts some of the most creative and passionate minds in virtually all industries. Data viz work can be both scientifically and artistically rewarding for data viz designers. When the creative mind takes over, space and time fall away, focus is heightened, allowing some of the best data viz to be produced. However, the stakes are high for producing effective data viz. Creating and presenting good data viz can have an enormous effect on shaping organizations’ competitive strategies. The conflict and tension lives here: data viz designers are challenged to protect their creative process while adhering to the realities of working under a timeline, budget and scope for their organizations.
One way to alleviate stress for data viz designers and minimize risk on projects is for designers to proactively seek out feedback during the creative process, not at the end. Asking for feedback is not easy. It can be uncomfortable to willingly ask for and accept potential criticism of one’s data viz work, since so much time, thought and effort was spent creating something meaningful. On the reverse, it’s important to not just receive feedback, but to also give feedback on others’ data viz, which contributes to building a healthy culture of collaboration.
Here are three tips to consider on giving and receiving good feedback on data viz.
Incorporating regular data viz feedback sessions into your team’s weekly schedule, project plan, or agile scrum sprints is an easy way to ensure that feedback is not delayed to the end of a project (when it’s generally too late to make changes). These sessions shouldn’t be designed to be super formal, but rather a low-risk, safe-space collaborative opportunity for designers to show their data viz and receive helpful feedback that will encourage beneficial improvements to be made.
In the book Storytelling With Data: Let’s Practice!, Cole Nussbaumer Knaflic suggests introducing “present and discuss” time into recurring meetings, by reserving 10 minutes for a team member to present what they are working on and then have a conversation where each person shares a positive point and a suggestion for improvement. This idea ensures feedback time is integrated into the normal day-to-day, but also encourages team members to share their thoughts and be welcomed into the creative process, promoting team cohesiveness and providing critical, timely feedback to the designer on their data viz work.
It’s important that the feedback is aimed at improving the story that the data visualization is attempting to tell its audience. It’s far too tempting and easy for those providing feedback to nitpick and be critical of aesthetics, like borders, font styles, colors, or chart orientation. Aesthetics are indeed important and should absolutely follow data viz best design practices, but there is often time enough to clean those details up.
Feedback can get off to a rocky start if the feedback provider is overly critical out-of-the-gate on something like a color choice, potentially putting the data viz designer on the defensive right away. Instead, the focus should remain on the idea behind what the data viz is attempting to communicate. In the book, Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations, Scott Berinato suggests making a “note of the first idea that forms in your mind and then search for more.” This is an exercise that can help drive a feedback session. The data viz designer can display their visualization, give time for it to be studied, and then ask team members to share the ideas that pop into their heads about what the viz is trying to tell them. This allows multiple diverse and fresh perspectives to be captured versus only having the designer’s perspective to gauge the effectiveness of the visualization. The instant and honest feedback from team members can then help the designer course correct or refine the data viz to ensure the intended compelling story is being effectively communicated.
Berinato also suggests making “notes on likes, dislikes, and wish-I-saws.” This method can provide a respectful and helpful way for feedback providers to address and share not just the likes, but any dislikes or things they’d like to see in the data viz being discussed. This method is a safe way for a team to share feedback on some of those finer design details that could be perceived as nitpicky, like chart formatting (e.g. chart grid lines), without losing sight of focusing on the big picture.
Receiving feedback on a regular basis from team members is a huge step forward but it’s equally important to share back with the team how their feedback was considered and leveraged to enhance the data viz. This will continue to drive engagement in giving and receiving feedback.
An effective way to close the feedback loop is to keep a running tab of the feedback collected and discuss what has been incorporated into the latest version of the visualization. Not all feedback will be in the end product of course (and that’s ok), but it’s important to maintain an open and transparent process on how the feedback is helping to shape the big picture in the visualization. Lastly, as it comes time for any data viz to be released into the wild, it’s important to share the success and the win together as a team. Give virtual high fives, clear the slate and move on to the next exciting data viz project.
The job of producing good data viz that communicates a big picture idea is hard work, as it is common for the process to go anywhere, but in a straight line. The odds of data viz hitting its target can be greatly increased by incorporating feedback into the creative process. Setting regular data viz feedback sessions, focusing on the data viz big picture, and closing the feedback loop by celebrating wins can provide exponential benefits to the quality of the data viz produced, the designers, and the feedback team as a whole in encouraging one another to do good data viz work.
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