Individual skill
insight-synthesis
Transform data findings into compelling insights. Use when converting analysis results into actionable insights, connecting findings to business impact, or preparing insights for stakeholder communication.
04-data-storytelling-visualization/insight-synthesis/SKILL.md
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SKILL.mdcore · 2,899 bytesassets/insight_brief_template.mddoc · 1,538 bytesreferences/insight_framework.mddoc · 3,486 bytesreferences/prioritization_guide.mddoc · 2,542 bytes
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# Insight Synthesis
# When to use
- An analysis has produced many statistics but no clear "so what"
- The team has findings but is struggling to prioritise which ones to act on
- Stakeholders are asking "what does this mean for us?" rather than "what did you find?"
- Multiple analyses need to be synthesised into a unified set of recommendations
- Preparing an insight briefing for a team that doesn't have time to review the full analysis
# Process
1. **List all findings** — enumerate every statistically meaningful finding: trends, comparisons, correlations, anomalies, surprises. Write each as a factual statement. Don't interpret yet.
2. **Apply So What → Why → Now What to each finding** — convert each fact into an insight by answering: So what (why does this matter to the business?), Why (what is the most likely explanation?), Now what (what specific action should follow?). See `references/insight_framework.md`.
3. **Quantify business impact** — for each insight, estimate the financial, customer, or operational magnitude. An insight without a number is an observation. Use order-of-magnitude estimates if precise data is not available.
4. **Prioritise by impact × confidence × actionability** — score each insight on these three dimensions (1–3 scale). Insights that score high on all three are the ones to lead with. Deprioritise insights that are high-impact but low-confidence until validated.