😶 I don’t like dashboards. There, I said it.

Ok, some nuance: I don’t like _most_ dashboards. The main reason: they’re trying to do everything, everywhere, all at once.

On the spectrum of data visualization, two main clusters of powerful visuals exist:

1️⃣ Data visuals for analysis: useful for data analysts, who have time to explore the data in full detail, with lots of filters, offering many different perspectives on the data. Their goal: extracting the insights from the data.

2️⃣ Data visuals for communication: useful for managers, or a more general audience. They don’t have a lot of time and want to know the major insights, fast, loud and clear. For more complicated stuff, we can craft a strong narrative to guide them through the major insights.

What most dashboards are trying to do, is both of these things simultaneously: raw data goes in, crystal-clear insights come out – or so people expect.

The solution? We make a full-fledged dashboard for the analysts, and a dedicated light-weight version for the management, showing only what they need to know for their decision-making. Or we do our analysis first, and translate those insights into an engaging visual storytelling piece, or an attractive visual report.

As always, we have to think about the audience and their goals. Not just dump the data on top of them, and hope they will figure it out!