3 principles for turning data in decisions

A good dashboard should do more than display data. It should help someone understand what is happening, why it matters, and what they might need to do next.

That sounds obvious, but many dashboards fall short because they are designed around the data that is available rather than the decisions people need to make. They may contain the right numbers and look polished, but still leave the reader asking: So what?

What does someone need to know or decide after looking at this dashboard?

The best place to start is with the audience and the decision. A chief executive, an operational manager and an analyst may all be looking at the same organisation, but they need very different levels of detail. A useful dashboard is clear about who it is for and what questions it should help them answer.

That also means being selective. Just because a measure can be reported does not mean it needs to appear. When too much information is given equal weight, the important signals become harder to see. A well-designed dashboard makes the most important information obvious and keeps supporting detail in its place.

Context is equally important. A number such as 72% means very little on its own. Is it improving? Is it below target? How does it compare with last year or with similar organisations? Trends, targets and benchmarks help turn a number into something people can interpret.

The same principle applies to visual design. The aim is not to use the most sophisticated chart, but the clearest one. Sometimes a line chart is enough to show a trend. Sometimes a simple comparison or a short sentence will communicate the message more effectively than another visual.

Perhaps most importantly, a dashboard should help direct attention. Titles, annotations and short commentary can make the difference between showing information and communicating meaning. A chart labelled ‘Applications by month’ tells the reader what they are looking at. A title such as ‘Applications have fallen for three consecutive months’ tells them what they should notice.

A simple way to test a dashboard is to give it to someone who was not involved in building it and ask them to look at it for 30 seconds. Can they explain what is happening, why it matters, whether anything is surprising, and what they might do next?

If not, the dashboard may be reporting the data without really communicating it.

Ultimately, a useful dashboard is not defined by how many charts it has, or which software was used to build it. Its value comes from presenting the key information needed for users to make evidence-based decisions.