Explain revenue variance vs. budget
Decompose monthly revenue actuals against budget into volume, price, mix, and timing drivers — with commentary suitable for a board pack.
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You are a senior FP&A Analyst producing the following deliverable: explain revenue variance vs. budget.
Context
- Workflow: Variance Analysis
- Inputs available: {paste the data here}
- Period: {month / quarter}
- Audience: {who reads this}
What to produce
1. The headline takeaway in one sentence.
2. The three things that materially moved the result, with quantified contribution.
3. The one risk or anomaly worth flagging.
4. A short forward-looking note: what to watch next period.
Guardrails
- Use only the numbers provided; do not invent values.
- Cite a row reference for every claim.
- Flag anything you cannot reconcile rather than smoothing it over.
Run it in four steps
- Export revenue actuals and budget for the period at the same grain (SKU or product line), with the ASP or unit-count split alongside.
- Paste both into
{paste the data here}, set{month / quarter}, and name the reader in{who reads this}so the commentary lands at the right altitude. - Run it in your AI tool of choice using the buttons above.
- Before circulating, check the volume/price/mix split against any product renamed or reclassified this period; that is where the attribution quietly breaks.
When to reach for this prompt
What you can expect back
Headline: Revenue +$842K (+4.2%) vs. budget, driven primarily by mid-market upsell.
| Driver | Δ vs. budget | Detail |
|---|---|---|
| Volume | +$1.1M | new logos N=14 vs plan 11 |
| Price | -$310K | ASP softening on Pro tier renewals |
| Mix | +$120K | Enterprise share 38% vs 32% budgeted |
| Timing | -$78K | 3 deals slipped to next month |
Anomaly worth flagging: Pro tier ASP -6% MoM — investigate discounting.
This prompt has real limitations you should understand.
Categories drift between systems
Your CRM says "Expansion." Your ERP says "New Logo." The model cannot reconcile the two — and will fabricate a plausible-looking driver narrative anyway, with full confidence.
SKUs renamed mid-period
Volume / price / mix / timing decomposition is only as honest as the line items. The same product under different names will collapse into a "mix shift" that's actually a data hygiene problem. The model cannot tell, and will not flag it.
Trend window contamination
Anomaly detection assumes six clean prior periods. If you migrated ERPs in the last two quarters, or changed how you book deferred revenue, every "1.5σ flag" is noise — and the prompt will surface them as findings.
What your data needs to look like
- Monthly revenue actuals by SKU or product line
- Budgeted revenue for the same period at the same grain
- ASP / unit-count split (or invoiced quantity)
- A consistent product hierarchy with no mid-period reclassifications
See how FinanceOS handles this prompt on real financial data.
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