It’s a truth universally acknowledged: Data dashboards look rad—the eye-catching colors, the illustrations of complex relationships, the way data is shown to change over time. Done right, it all adds up to information that’s immediately understandable. And incredibly valuable: An effective data visualization or dashboard can play a key part in helping leaders make better, data-driven decisions.
If you’ve ever seen a great one in action, your first thought was probably something like, “This is amazing. Now how can we do something like this?” You want your own organization to be innovative and data forward, and you see the potential for what a great visualization can offer. But to really make sure this tool is effective, where should you begin?
Read on to get the solution.
Want to learn more from the experts? Watch our interview with Anna Peterson to hear how she creates effective data visualizations.
Start by Defining the Why Behind Your Data Visualizations
Obviously “looking cool” isn’t the reason you want a great data dashboard. What you’re really after is actionable intelligence that will help guide the decisions of people throughout your organization.
The best place to start, then, is to define the why that motivates you. What questions is your organization trying to answer? What challenges are you wrestling with right now, and how will data guide your response? What information do you need, specifically, to take the next step forward?
By defining these parameters up front, you can ensure that the data dashboard you create will specifically address those problems that you’re trying to solve. Your data dashboard won’t just look good, it will be a functional tool that people want to adopt because it helps them do better work.
The world of data analytics is littered with unused dashboards that look great but don’t offer much to their users. Yours should provide information that your stakeholders need to ensure they’ll want to keep using it.
Be Patient through the Development Process of Your Data Dashboard
Defining your why isn’t the only part of the process that takes time and consideration. The actual development itself is going to be a pretty big lift, one that suffers when rushed. Your new data dashboard has the potential to change the way your team works, but only if you invest the time to get it right.
Creating an effective data dashboard may be a very big project, but it can be broken down into smaller, digestible chunks. If your dashboard is home to multiple visualizations, you can still choose to launch small and iteratively add on additional pieces and parts. This approach also enables you to continually refine each visualization until you’ve hit on the best way to show data.
An iterative approach also allows you to stay open to comments and questions. If your users question how data is visualized, push back on your processes, or suggest improvements, that’s critical feedback that should shape the next iteration. Welcome it as a healthy part of the development process.
Understand Your Limitations and Work within Them
You may have an idea for a visualization you’d like to create but discover gaps within your data resulting from technical limitations, a governance issue, or a problem with the data source itself. Most people feel uncomfortable when they discover these gaps, and they want to find a low-friction workaround.
It’s much better to resist the urge to paper over that gap with a placeholder and instead work with the limitations you have as you start to build your assumptions. Doing so can be challenging—especially if the standards are not clearly defined. But, trust us, this is where your approach can really grow. Research and good data scientists who can help you clarify what that missing data means in the context of your visualization.
You want your visualization to be as complete as possible, but you also don’t want to mislead your audience. Recognizing that you’ll always face certain limitations can be the start of learning how to work within them.
Remember the Story You’re Trying to Tell with Data Visualizations
When you’re deep in the weeds of creating an effective data visualization, you can start to get lost in the details. It’s important throughout the process to periodically step back and remember what story you want to tell.
It all goes back to the why. Why are creating this visualization in the first place? What do you hope to accomplish, and whom do you need to persuade? If your visualization could convey a single takeaway, what do you want it to be?
The way you answer these questions will help you define the boundaries within which you need to work, and that’s a great thing—these boundaries give you purpose, keep you focused, and can even make the whole process fun. When you remember the story you’re telling, it gives shape and purpose to the visualization that you create.
