Turn spreadsheet analysis into an executive summary
Convert verified metrics into decisions, changes, risks, and requests without overstating evidence
6 min setupTested with:ChatGPTReviewed: 2026-08-28
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Write a decision-ready executive summary from spreadsheet analysis.
Reader and decision:
[audience]
Verified findings with periods, denominators, baselines, and sources:
[findings]
Risks, unknowns, and requested action:
[limits]
Use only supplied findings. Lead with what changed and why it matters for the decision. Separate observed facts, plausible interpretations, and recommendations. Preserve material denominators, comparison periods, uncertainty, and data-quality limits. Return a short headline, 3–5 key findings, decision implications, risks/unknowns, and one explicit ask. Add a metric trace table linking every number in the summary to its supplied source.
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From input to outcome
A worked example
See how concrete context turns this recipe into a usable result
Actual input
Reader and decision
COO deciding whether to fund a two-week investigation into checkout performance.
Verified findings
Complete weeks only. Online conversion fell from 4.8% to 3.9% over six weeks, −0.9 percentage points/−18.75%. The largest step was 4.6% to 4.1%. Mobile is about 70% of checkout starts. Tracking definition changed 11 May; mobile release was 1 June. No controlled comparison. Source: Conversion_Weekly pivot v3, refreshed 27 Aug 2026.
Risks, unknowns, and requested action
Need event-level validation and Mobile versus non-Mobile breakdown. Ask to assign one analyst and one engineer for two weeks. Do not state the release caused the decline.
Example output
Checkout conversion shows a sustained decline that warrants focused investigation
Observed: Across the six most recent complete weeks, conversion declined from 4.8% to 3.9%—down 0.9 percentage points, or 18.75% relative.
Observed: The largest single step was 4.6% to 4.1%, followed by two smaller declines. Mobile represents about 70% of checkout starts.
Interpretation: The pattern is operationally material, but the 11 May tracking-definition change limits comparison and the data does not establish that the 1 June mobile release caused it.
Decision implication: A short investigation can determine whether the change is measurement-related, concentrated on Mobile, or distributed more broadly before larger remediation is funded.
Risks/unknowns: event-level tracking validity, Mobile versus non-Mobile rates and denominators, delayed conversions, and post-refresh revisions.
Ask: Assign one analyst and one engineer for two weeks to validate tracking and produce a device-level diagnosis with recommended action.
Metric
Source
4.8% → 3.9%; −0.9pp/−18.75%
Conversion_Weekly pivot v3, six complete weeks
4.6% → 4.1% largest step
same source
Mobile ≈70% of starts
same source; verify event-level denominator
Why this works
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Separating facts, interpretations, and recommendations prevents analysis from turning into unsupported certainty.
2
A metric trace table keeps compressed executive language auditable.
Check the result
Can every number be traced to a supplied finding and period?
Are interpretations labeled separately from observations?
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