A dashboard is not judged by how good it looks, but by the decisions it helps people make. Yet many dashboards end up as collections of charts that impress in a demo and go unused a week later. Knowing how to design a dashboard people open every morning is as much an art as a discipline. Here are the essentials.
What makes a dashboard good
A good dashboard answers business questions. Before opening Qlik Sense, Power BI or Tableau, the question is not “what data do I have?” but “what does this person need to know in order to decide?”.
That means designing for a specific audience and purpose. The dashboard for a sales director who needs to see the sales trend in ten seconds looks nothing like the one for an analyst investigating the cause of a deviation. A dashboard that tries to serve everyone serves no one well.
Design principles
Dashboards that work share a handful of principles:
- Less is more. Every element you add competes for attention. If a chart does not help answer the central question, it does not belong. White space is not wasted space; it is what lets the important things breathe.
- Visual hierarchy. The most important element goes top left, where the eye lands first. Size, position and colour should signal what to look at first and what is secondary.
- Context. A number on its own rarely means anything. “1,200 sales” does not say whether that is good or bad; “1,200 sales, up 15% on last month and above target” does. Always compare against a target, a prior period or an average.
- Consistency. The same colours for the same categories, the same date and number formats across the panel. Consistency reduces the effort of reading.
Choosing the right chart
Each type of data calls for a particular visualisation. Choose badly and you force the reader to mentally translate what they see, and that is where the message gets lost. As a quick guide:
- Change over time: line chart.
- Comparing categories: bar chart (horizontal is better when labels are long).
- A value against a target (KPI): a highlighted indicator or a bullet chart.
- Composition or parts of a whole: stacked bars beat a pie chart, which becomes unreadable beyond three slices.
- Relationship between two variables: scatter plot.
The underlying rule: pick the chart that communicates the idea with the least interpretation effort possible.
Typical mistakes
The same failings appear again and again:
- Clutter. Twenty charts on one screen is not a dashboard, it is noise. If you need to show a lot, spread it across several views with a clear hierarchy.
- Poor use of colour. Colour is a message, not decoration. Use a restrained palette, reserve strong colours for what must stand out, and design for colour-blind readers by not relying on red/green alone.
- Misleading charts. Axes that do not start at zero, confusing dual scales or 3D effects distort perception. Visual honesty is part of rigour.
- False precision. Showing “34.7182%” gives an impression of accuracy that rarely helps. Round to what the decision actually needs.
From design to action
A dashboard finishes its job when it prompts a decision. That is why the best design anticipates the next question: it lets people filter and drill down to move from the “what” to the “why”, it highlights what falls outside the expected, and it guides the eye towards what demands action.
Designing a panel well is, to a large degree, an exercise in communication. And like all communication with data, it gains power when it is framed within a narrative: we recommend reading our guide on data storytelling and how to tell stories with data.
At Digital Fox Data we design dashboards people actually use, through our Business Intelligence consulting. If your panels are not moving decisions, let’s talk.