AI TEMPLATE · REPORTING
AI Dashboard Review Template
Turn dashboard data into executive-ready narrative. A structured framework for interpreting metrics, detecting anomalies, explaining context, and recommending actions.
Last updated May 20, 2026
Category
Reporting & Analytics
Audience
Analysts, Managers, Data Leads
Format
PDF · 7 pages
What's Inside
01Dashboard Health Check
02Metric Inventory
03Anomaly Detection
04Context Layer
05"So What?" Framework
06Metric Relationships
07Narrative Summary
08Audience-Specific Views
09Action Items
10Dashboard Improvement Log
Who This Is For
- Data analysts & leads
- Operations managers
- Business intelligence teams
- Anyone presenting dashboards
- Leaders receiving reports
When To Use It
- Weekly metric reviews
- Stakeholder presentations
- Performance deep-dives
- Board or exec updates
- Quarterly business reviews
The "So What?" Framework
For every insight, answer these three questions:
1
What happened?
2
Why does it matter?
3
What should we do?
Copy-Paste AI Prompt
Act as a senior data analytics leader.
Review the dashboard data below and produce an executive-ready
narrative that turns numbers into decisions.
Structure:
1. Dashboard Health Check (data freshness, gaps, filters)
2. Metric Inventory (current vs target, status)
3. Anomaly Detection (spikes, drops, trend breaks, divergences)
4. Context Layer (business reasons behind movements)
5. "So What?" Analysis (what happened, why it matters, what to do)
6. Metric Relationships (correlations that held or broke)
7. Narrative Summary (situation, changes, risks, focus)
8. Audience-Specific Takeaways (exec vs manager vs analyst)
9. Action Items (specific, owned, time-bound)
10. Dashboard Improvement Notes (what to fix next time)
Rules:
- Lead with insight, not description.
- Every metric needs context. Numbers alone are noise.
- Flag anomalies explicitly. Do not bury them.
- Separate facts from interpretation.
- End with actions, not observations.
- If data is missing or stale, say so upfront.
Dashboard data: [PASTE METRICS HERE]
Time period: [PASTE PERIOD]
Business context: [PASTE CONTEXT]
Known issues: [PASTE KNOWN ISSUES]Common Mistakes
- Describing charts instead of interpreting them
- Presenting all metrics equally
- Ignoring broken correlations
- Showing green/red without context
- Averaging away important spikes
- No actions produced from the review
- Never improving the dashboard itself
Best Practices
- Start with anomalies, not summaries
- Add context to every movement
- Use "So What?" for every insight
- Show metric relationships
- Tailor depth to your audience
- Produce at least one action per review
- Kill metrics nobody acts on
Download the full 7-page template with anomaly detection tables, narrative frameworks, and audience guides.