Why data storytelling matters more than charts alone
Data is powerful—but only when it’s understood. In a world full of dashboards and KPIs, it’s easy to forget that analytics is as much about communication as it is about computation. That’s where data storytelling comes in.
This post explores what it means to go beyond the dashboard and deliver insights that drive action.
It’s tempting to throw every metric on a dashboard: page views, user counts, rates, filters, bar charts, pie charts, trendlines, and more.
But here’s the catch:
More visuals don’t always mean more clarity.
In many organizations, decision-makers are left staring at crowded dashboards, wondering what they’re supposed to do with the data.
That’s where analysts become essential—not just to crunch numbers, but to highlight what matters and why.
A good analyst doesn’t stop at data presentation—they bring clarity to the questions that stakeholders care about:
Are we hitting our targets?
Why are we seeing this trend?
What should we prioritize next?
What will happen if we don’t act?
This means pairing analytics skills with business fluency, storytelling structure, and visual empathy—understanding how your audience takes in information.
Imagine you’re analyzing support tickets during Open Enrollment. You notice that 43% of inquiries are about “who’s eligible” for a pretax benefit plan.
Now ask yourself:
Is that normal or high?
How does that compare to last year?
What types of participants are asking this question?
What’s the cost (time, confusion, claims delays) of not addressing it?
Rather than showing a pie chart and calling it a day, a strong data story might look like this:
Insight: Eligibility confusion made up 43% of OE support tickets, up 15% from last year.
Trend: This rise correlates with a change in plan language on employer communications.
Quote (from ticket log): “My spouse was eligible last year—why isn’t she now?”
Recommendation: Refine eligibility communication using plain language and infographics. Run post-enrollment surveys to measure clarity.
Here’s a mockup of how this insight could be visualized clearly and actionably:
Notice how one insight is brought to the front. It’s not buried in charts—it’s presented in a way that answers the “So what?” for the business.
Your technical tools matter—Python, SQL, Tableau—but your value lies in clarity. The best data stories don’t just report. They persuade. They guide. They lead to better decisions.
“Good data is accurate. Great data is understood.”