The skill: Turning numbers into a narrative that makes people act. The analysis is only half the work. If you can't communicate it, it didn't happen.
In a Nutshell
- SCR framework: Situation, Complication, Resolution. This is the backbone of every data presentation that works.
- Lead with the punchline. State the insight first, then show the evidence. Not the other way around.
- One chart, one insight. If a chart requires a paragraph of explanation, it's the wrong chart.
- Chart type by comparison: bar for ranking, line for time, scatter for correlation, table for lookup.
- Insight titles, always. "Churn spiked 40% after the pricing change" not "Monthly Churn Rate."
- Remove everything that doesn't help. Gridlines, legends you can label directly, decimal places nobody needs.
- Prepare three objections. Before presenting, ask yourself what a skeptic would challenge. Have the backup slides ready.
The SCR framework in practice
The Situation-Complication-Resolution framework works because it mirrors how people naturally process information.
Situation is the context everyone already knows. Keep it to one or two sentences. "We launched the new pricing page three weeks ago. Conversion was stable at 4.2% before the change." This grounds the audience. Don't spend five slides on background they already have.
Complication is the tension, the thing that changed, the problem, the surprising finding. This is where you have their attention. "Since launch, conversion dropped to 3.1%, a 26% relative decrease. The drop is concentrated in the self-serve tier, enterprise conversion is unchanged." One chart here. Maybe two. The chart title states the insight.
Resolution is your recommendation. Not "we should investigate further" (that's not a resolution, that's a stall). A real resolution: "We should revert the self-serve pricing page to the previous version and run a proper A/B test with the new design. Based on current traffic, we'd need 3 weeks for a valid test." Concrete, actionable, with a timeline.
The whole thing takes 3-5 minutes to present. Which is exactly right. Most data presentations fail because they're too long, not too short.
Do's and Don'ts
Written with ❤️ by a human (still)