Dashboards and data stories: knowing when to use which

Dashboards and data stories are both legitimate data communication tools. Most organisations use both. But when the wrong one is used in the wrong situation, communication fails, regardless of how well it's built.

Understanding what each tool is designed to do makes it easier to choose between them, and to get more out of both.

What a dashboard is for

A dashboard is designed to give an audience ongoing access to data they already understand. It surfaces key metrics and is updated regularly for people who know what to look for. It doesn't explain what the data means because it doesn't need to—its audience already knows.

This is what makes a dashboard valuable for the right audience. A team that checks the same metrics weekly doesn't need context every time. They need clarity and speed.

But that same design (no context, no narrative, and data that updates) is exactly what makes a dashboard a poor storytelling tool.

For more on the distinction between these two types of communication, see Data storytelling vs data visualisation: what's the difference?

Five reasons dashboards don't tell stories

Here are five reasons dashboards don't make good data storytelling tools:

Dashboards rarely explain context. Stories use context to aid understanding. A dashboard presents data without explaining what it means, why it changed, or what should happen next. For an audience unfamiliar with the subject, that meaning gap is too wide.

Dashboard data updates. A data story communicates a specific message at a specific point in time. When the underlying data changes, the story can change or disappear entirely. A dashboard can rarely hold a story still.

Dashboards can house multiple stories, or none. A well-built dashboard might contain a bunch of metrics, each of which could support a different story. Presenting all of them together doesn't tell any of those stories—it leaves the audience to draw their own conclusions, which they may or may not be equipped to do.

Filters can change the story lens. Interactivity is a dashboard feature, not a storytelling one. When an audience can filter the data themselves, they're exploring. This is useful, but different from being guided through a specific insight toward a specific action.

Sometimes a data story is best told without a visual at all. Telling a narrative can be verbal, written, or visual. Dashboards are always visual, and always interactive.

What a data story is for

A data story is another form of data communication, but designed for a different audience than dashboards. Their audience are not as familiar with the data, so they need context to understand what they're looking at. They may also need to take a specific action, or understand a specific message, that the data alone won't communicate.

A data story moves an audience from context to insight to implication. It tells them what the data shows, and also why it matters to them, and what they should do about it.

How to choose

The question to ask is "what does my audience need from this communication?"

If your audience is familiar with the data and subject, checks it regularly, and needs ongoing access to current metrics: a dashboard is the right tool.

If your audience needs context to understand the data, you want them to take a specific action, or you need to communicate a clear message to people who aren't close to the data: a data story is the right tool.

A good data communication strategy uses both. Dashboards serve the teams doing the ongoing work. Data stories serve the decision-makers who need to understand what that work means.

The Data Storyteller's Handbook covers how to design each type of communication for its intended audience and purpose.

Kat Greenbrook is a data storytelling consultant, author, and workshop facilitator based in Wellington, New Zealand. She is the founder of Rogue Penguin and the author of The Data Storyteller's Handbook.