How do we transition from Exploratory to Explanatory analysis in data storytelling?
I often find myself presenting every single chart I created during my research, which overwhelms my stakeholders. How do I filter out the "noise" and move into a truly explanatory mode? What are the best practices for choosing only the data points that support a specific business narrative without cherry-picking or being misleading?
2025-04-12 in Data Science by Robert Miller
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All answers to this question.
The key is to remember that exploratory analysis is for you, while explanatory analysis is for your audience. In 2024, our team adopted the "So What?" test for every slide. If a chart doesn't directly answer a business question or prompt an action, it goes into the appendix. I recommend starting with the conclusion first—the "Headline"—and then using the data to prove why that headline is true. In a 2023 project for a retail client, we cut our deck from 40 slides of raw data to 8 slides of narrative-driven insights, and the project approval rate doubled because the "why" was finally clear.
Answered 2025-05-20 by Susan Patterson
When you move to explanatory mode, do you prefer using a linear slide deck or an interactive dashboard where the audience can still "explore" a little bit on their own?
Answered 2025-06-15 by Steven Graham
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Steven, for a high-stakes meeting, a linear deck is usually better. It keeps the focus on the story you are telling. Dashboards are great for weekly monitoring, but they often distract from a specific narrative.
Commented 2025-07-02 by Michael Higgins
You should focus on "Pre-attentive Attributes" like color and size to draw the eye exactly where the insight is. Gray out the background data and highlight the trend.
Answered 2025-07-15 by Jennifer Hudson
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I agree with Jennifer. Highlighting is the easiest way to turn a "data dump" into a "story." It tells the audience's brain exactly where to look first.
Commented 2025-07-22 by Robert Miller
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