Budget vs. actual — analyzing spend variances in natural language
Budget vs. actual analysis by cost center typically takes a morning in Excel. With the Spendesk MCP, Claude pulls the data, calculates variances, and identifies significant overruns — in 30 seconds.
The problem
Every quarter, same scenario: pull the Spendesk export, open it in Excel, build pivot tables by cost center, calculate variances against budget, then spend an hour investigating abnormal lines.
And if someone asks for a variation — by department, by category, by quarter — you're back to another 45 minutes.
Budget vs. Actual analysis in a single prompt
Budget vs. Actual Analysis — Q2 2026 by Cost Center
| Cost Center | Budget | Actual | Variance € | Variance % |
|---|---|---|---|---|
| Engineering | €845,000 | €891,200 | +€46,200 | +5.5% |
| Marketing | €320,000 | €398,700 | +€78,700 | +24.6% |
| Sales | €180,000 | €165,400 | -€14,600 | -8.1% |
| G&A | €95,000 | €94,100 | -€900 | -0.9% |
| R&D | €210,000 | €187,300 | -€22,700 | -10.8% |
| Total | €1,650,000 | €1,736,700 | +€86,700 | +5.3% |
3 variances to investigate (> 10%)
Would you like me to analyze Marketing or R&D detail first?
Investigating the Marketing overrun
The previous response identifies the problem. This question finds the cause.
Marketing Q2 2026 overrun breakdown (+€78,700)
Primary driver — Digital advertising (+€53,000)
| Supplier | Q2 Budget | Q2 Actual | Variance |
|---|---|---|---|
| LinkedIn Ads | €45,000 | €76,200 | +€31,200 |
| Google Ads | €38,000 | €58,100 | +€20,100 |
| Meta Ads | €12,000 | €13,700 | +€1,700 |
Secondary driver — Unbudgeted events (+€22,000)
Offsetting savings (-€2,700)
Summary: 68% of the overrun came from digital (rising CPL), 28% from a last-minute event.
Would you like a summary slide for the board, or a monthly trend analysis for LinkedIn?
Three other everyday use cases for FP&A
Tracking SaaS and recurring subscriptions
SaaS subscriptions with > 20% increase — Jul 2025 vs. Jul 2026 comparison
| Tool | July 2025 | July 2026 | Increase |
|---|---|---|---|
| Datadog | €8,200/mo | €14,800/mo | +80% |
| Figma (Enterprise) | €1,200/mo | €2,100/mo | +75% |
| Notion | €890/mo | €1,340/mo | +51% |
| Slack | €2,400/mo | €3,200/mo | +33% |
| Salesforce | €9,800/mo | €12,400/mo | +27% |
Annualized impact of increases: +€165,600/year
Spend per employee for benchmarking
Spend per employee — Q2 2026
| Department | Headcount | Total spend | Spend/employee |
|---|---|---|---|
| Engineering | 48 FTE | €891,200 | €18,567/employee |
| Marketing | 12 FTE | €398,700 | €33,225/employee |
| Sales | 22 FTE | €165,400 | €7,518/employee |
| G&A | 8 FTE | €94,100 | €11,763/employee |
Would you like me to project these ratios against the H2 budget accounting for hiring plans?
Key takeaways
- Budget vs. Actual analysis goes from 3 hours to 30 seconds
- Claude automatically identifies variances and suggests likely causes
- Each answer can generate the next question — investigation in conversational mode
- Spendesk data (operational spend) combines easily with your HR budgets for per-employee analyses
- Ideal for preparing monthly business partner reviews
Related skills
Analyze spending over periods exceeding 366 days by splitting into sub-periods and aggregating results.
Break down spending by cost center with per-employee detail, resolving cost center names from IDs.
Analyze month-over-month spend trends by cost center, detect accelerating or declining budgets, and flag anomalies.