Designing Dashboards That Deliver — Reflection
Have you ever built a beautiful, interactive dashboard, only to be asked to export the data to Excel and send it instead?
I’ve been there. Early in my career, I was a zealous data analyst eager to prove myself. I said yes often — focused on the beauty and interactivity of the visuals, as well as delivery speed. However, I noticed that usage would plummet a few months after launch, and the same users would ask for the data in an Excel sheet instead. Over time, I gained experience and started developing dashboards that retained engagement over time.
Key Takeaways
Yesterday, I attended an event called “Designing Dashboards That Deliver,” presented by Amanda Makulec and hosted by Data Visualization DC. My initial thought was, “Where were you five years ago?” And by the end of the presentation, I realized that this book is a must-have.
Amanda pointed out that most dashboards fail because developers jump straight into building. It’s easy to do — the tools are accessible, the tech is exciting, and it feels productive. But skipping the discovery and design phases means missing the foundation that makes a dashboard useful.
Start with Discovery
When building a dashboard, one must understand the user and the problem that needs to be solved. Amanda shared a simple but powerful framework for building a user story:
As a [user job title], I need to understand [state the problem], in order to [the why].
Once the user story is formulated, sharing it back and asking, “Did we capture everything?” is best practice. Amanda stated, “Instead of asking, ‘What do you want to build?’ ask, ‘Why do you need this information, and how will you use it?’” This simple shift changes everything — it moves the focus from features and visuals to function and impact.
Prototype Early and Collaborate Often
Prototyping is an inexpensive yet highly effective way to keep users engaged and maintain alignment between developers and users. It’s much better to make changes earlier in the process than later.
A Personal Reflection: Simplicity Wins
In my five years working in healthcare analytics, one thing has become clear: simplicity wins. Some of my most successful dashboards — the ones still in use years later — were simple:
- A trend line with a goal reference
- A few key metrics (BANs)
- Straightforward filters
They were successful because users kept coming back. The reason they kept coming back was simple: the dashboards were easy to understand and easy to use.
In the end, our job is to meet our users where they are. We might be tempted to use the newest features or experiment with creative designs—but ultimately, our goal is to help users make decisions with confidence.
My previous, zealous data analyst self could have been more effective much sooner had I applied these tips earlier. But as with most things, growth comes through trial and error.