The lost art of data storytelling
Credit: Dalle on Microsoft Bing

The lost art of data storytelling

As dashboard technologies like Power BI and Tableau become more powerful and dashboard design becomes more efficient, dashboards become a flashy, complex, jumbled mess of as many data sources as possible crammed into a single screen.

What question are you trying to answer with your data, for whom, and what action should they take?

Dashboards, at their core, are automated, recurring insights. They help your audience interpret complicated information, highlight essential points to your audience, and tell them where and how to take action. Some questions to consider:

What is your hypothesis? What story do you think the data will tell you? You should be able to write out the question you are answering and for whom in a single sentence.

What data do you need to tell your story? Now that you know the story you want to tell, what data do you need, and where do you need to get it?

Audience and purpose matter. Are you providing insights to the sales executive team about where to focus their efforts? Or are you helping call center managers improve the quality of their operations? Given their audiences and purpose, these two dashboards will dramatically differ.

What action are you recommending? Use data sets that guide your narrative, so be intentional about what you include. However, be sure to be impartial. Including data that doesn't support your story or action may increase credibility by demonstrating transparency and caution. At its core, the data you include and how you include it should point to an action or change that will help your business.

In the next article in this series, I will share tips on choosing the correct visualization to bring focus and power to your story and recommendation. See you next week!

Michael Verdi

All things GTM

11 个月

What's an example story from your past experience?

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Taylor Dunlap

Solutions Architect @ dbt Labs

12 个月

Great write up, Mark! Too often dashboards are created straight from requirements, without thought to develop a hypothesis.

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