wshobson Data Storytelling
Transform raw data into compelling narratives that drive decisions and inspire action.
When to Use This Skill
- Presenting analytics to executives
- Creating quarterly business reviews
- Building investor presentations
- Writing data-driven reports
- Communicating insights to non-technical audiences
- Making recommendations based on data
Core Concepts
1. Story Structure
Setup → Conflict → Resolution
Setup: Context and baseline
Conflict: The problem or opportunity
Resolution: Insights and recommendations
2. Narrative Arc
1. Hook: Grab attention with surprising insight
2. Context: Establish the baseline
3. Rising Action: Build through data points
4. Climax: The key insight
5. Resolution: Recommendations
6. Call to Action: Next steps
3. Three Pillars
| Pillar | Purpose | Components |
|---|---|---|
| Data | Evidence | Numbers, trends, comparisons |
| Narrative | Meaning | Context, causation, implications |
| Visuals | Clarity | Charts, diagrams, highlights |
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Best Practices
Do's
- Start with the "so what" - Lead with insight
- Use the rule of three - Three points, three comparisons
- Show, don't tell - Let data speak
- Make it personal - Connect to audience goals
- End with action - Clear next steps
Don'ts
- Don't data dump - Curate ruthlessly
- Don't bury the insight - Front-load key findings
- Don't use jargon - Match audience vocabulary
- Don't show methodology first - Context, then method
- Don't forget the narrative - Numbers need meaning
Source: wshobson/agents → plugins/business-analytics/skills/data-storytelling/SKILL.md