Skip to main content
2,200+ service businesses benchmarked. Do you know your gross profit per labor hour? See where you stand →
Level
← All finance systems

Public preview

Actual spending versus budget

Which differences from budget or last period need a decision?

Calculate dollar and percentage differences. Organize possible reasons, including timing, volume, price, work mix, expense categories and missing or inconsistent records.

Records you need

  • ✓Monthly actual amounts
  • ✓Budget
  • ✓Earlier period actual amounts

What you get

  • ✓Important differences
  • ✓Possible reasons
  • ✓Review questions

Checks performed

  • ✓Comparable account categories
  • ✓Dollar and percentage difference
  • ✓Small budgets can exaggerate percentages

From finding to decision

An annual contract can look like a monthly overspend.

Test timing and accounting treatment before interpreting a budget difference as recurring waste. Small budgets can also exaggerate percentage changes.

  1. Check that actual and budget amounts use comparable accounts and periods.
  2. Inspect invoices for annual billing, prepayments or one-time purchases.
  3. Separate changes in the ongoing spending level from timing differences or incorrect expense categories.

Evidence ready for review

Each important difference has a dollar explanation and either a supported cause or a clear unanswered question.

Who makes the next decision?

The budget owner updates the forecast, explains the timing or requests a correction supported by records.

Collect the supporting records from your software

Level diagnostic method reviewed . Apply it to the selected records and accounting policy; the teaching example does not resolve a live account.

Guided synthetic example

See the check from input to decision

The three July overhead accounts shown finished $6,100 above budget in total; software and insurance ran over while vehicle expense was $800 under budget. Revenue performance is not included in this extract.

How review effort might be shared

An illustrative allocation is 15% collecting records, 20% applying checks, 10% flagging results, 25% investigating reasons, 20% finance review and 10% choosing an action. These percentages were not measured across engagements. Actual effort varies with data quality, complexity and the issue found.

1

Start with the source records

AccountActualBudgetVariance
Software$18,400$12,000+$6,400
Vehicle expense$9,200$10,000-$800
Insurance$14,500$14,000+$500
2

Apply the documented check

For this synthetic review, flag an account when absolute variance is at least $1,000 and at least 10% of budget. Separately flag budgets below $1,000 for denominator review. Calculate Actual minus Budget; a percentage flag is not proof of waste.

3

Surface the flagged result

Needs review

Software expense is $6,400, or 53.3%, above budget, exceeding the $6,100 net overhead variance of the three accounts shown.

4

Use recorded finance judgment to analyze possible reasons

At Level, we record the review logic, known explanations, and questions our finance professionals use in this situation. AI applies that documented human judgment to organize the most plausible reasons, without pretending it knows which reason is true.

Possible reasons to investigate

The variance could reflect a new annual contract, miscoding, headcount-driven licenses, an unbudgeted tool, or timing rather than ongoing overspend.

5

Make the final human judgment

In a Level engagement, a Level finance professional validates the source evidence, challenges the AI-assisted analysis, and decides which explanation is supported.

Which vendors created the variance?
Is the expense recurring or timing-related?
Was the budget or classification wrong?
6

Make the operating decision

Trace the software transactions, identify the owner and renewal terms, then update the forecast or correct the classification.

Each skill uses an independent synthetic scenario. Shared month labels do not mean the examples describe one company or a single financial period.

Use this system

Start with the example, then inspect the structure

The JSON download is a sample record file to inspect with an AI assistant or developer. It is not a file to upload into your accounting software.

  1. Download the invented input and expected output.
  2. Replace one field at a time with a safe test value.
  3. Compare the result with the expected structure.
  4. Have a finance professional review every exception before acting.

Website example JSON and registry: CC BY 4.0 (attribution required). Downloadable toolkit ZIP: MIT. Each version identifies its own frozen examples.

Developer preview: AI-assistant helper (MCP)

This tool call returns fixed, invented sample records only. It does not connect to your books. Read the setup instructions.

run_synthetic_example {"slug":"monthly-variance-review"}

Human review is part of the system

This check organizes evidence and surfaces exceptions. A person with finance domain expertise still needs to interpret the result, validate the source records, and discuss the operating decision.

Open source does not mean open client data. We publish reusable finance tools, checks, templates, and playbooks. Client records, workpapers, credentials, communications, and private configurations remain confidential.

Use it yourself, or bring us the messy part

Get a one-page plan for checking your records

Tell us where the records stop making sense. We will reply with the first check to run, the records it needs, and the decision that still needs human finance judgment.

Install the free skills yourself

No commitment. We will reply with the first check, the records needed, and the decision a finance lead must make.