Find what my dashboard is not telling me
Reviews a dashboard for blind spots, missing comparisons, vanity metrics, and misleading views, and suggests what to add.
The prompt
Review my dashboard and tell me what it is not telling me: the blind spots, misleading signals, and missing context.
Dashboard contents: [PASTE the metrics, values, and charts, or describe a screenshot, including filters]
Purpose of the dashboard: [e.g. "weekly sales performance for regional managers"]
Decisions people make from it: [e.g. "where to add support staff", "which campaigns to cut"]
How metrics are defined: [OPTIONAL - definitions, data sources, refresh timing]
Look for:
1. Numbers shown without a target, prior period, or benchmark.
2. Averages and totals hiding the spread, small segments, or a few large accounts.
3. Missing leading indicators (only lagging results shown).
4. Vanity metrics that can rise without the business getting better.
5. Missing counter-metrics (e.g. speed without quality, growth without churn or cost).
6. Data freshness, coverage gaps, and filters that silently exclude records.
7. Metrics that people could game.
8. Questions a leader would ask that the dashboard cannot answer.
Return:
1. The three biggest blind spots, and the risk each creates for decisions.
2. A table: Gap | Why it matters | Metric or view to add | Data needed.
3. Any metric that may mislead as currently shown, with a fix.
4. Five questions to ask the dashboard owner.
Base findings on what I've shared. Where you are inferring rather than seeing something, say so.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Data & Analysis prompts
What to fill in
- e.g. "weekly sales performance for regional managers"
- e.g. "where to add support staff", "which campaigns to cut"
- OPTIONAL - definitions, data sources, refresh timing
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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