Open finance skill
Check profit by customer
Is the data complete enough to trust customer-level margin?
Check whether revenue and costs can be assigned consistently to customers before calculating their profitability. Include labor, materials, subcontractors and any shared-cost policy.
Records you need
- ✓Customer revenue
- ✓Direct costs
- ✓Allocation policy
What you get
- ✓Profit supported by assigned records
- ✓Costs not assigned to customers
- ✓How much is assigned and what remains uncertain
Checks performed
- ✓Revenue assigned to customers
- ✓Costs assigned to customers
- ✓Consistent allocation policy
From finding to decision
Most revenue may be assigned to customers while many costs are missing.
Check how each cost component is assigned to customers. A precise customer margin can mislead when labor, inventory or shared costs have not been included.
- Check that customer revenue and each direct-cost sum match their reported totals.
- Use original job, customer and document-line IDs instead of guessing from supplier names.
- Separate costs traced directly to customers, costs assigned under an approved policy and amounts not yet assigned.
Evidence ready for review
For each component, show how much is assigned and how it was allocated. Keep unresolved costs visible.
Who makes the next decision?
Finance approves any allocation policy before the owner uses customer rankings for pricing or account decisions.
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.
Financial evidence in practice
Can moving an account improve customer or channel margin?
It can change the displayed margin without changing company profit. Preserve disjoint cost pools, map each channel once and foot allocations to company contribution. Interpret inventory timing and labor classification before comparing periods.
Run the check
- Declare the contribution definition and included costs.
- Bridge changed account classifications to a comparable basis.
- Allocate shared cost once with visible assumptions.
- Foot channel totals to the company and keep missing cost unmeasured.
Fictional example: Monthly margin classification and inventory bridge
Fictional $10,000 revenue less $3,000 labor and $2,000 materials gives $5,000 gross profit. Moving labor below gross profit raises displayed gross profit to $8,000 while company profit is unchanged. In a separate scenario, a $1,000 expense for unsold inventory sits outside the $2,000 sold-materials amount. It reduces purchase-period book profit from $5,000 to $4,000; capitalization restores $5,000, with other operating expenses held at zero.
Invented teaching inputs in USD cents. This is purchase-period book presentation for unsold goods, not a recommendation about tax inventory methods.
Inspect the expected output
{
"fictional": true,
"unit": "USD cents",
"id": "margin-basis",
"comparableGrossProfitCents": 500000,
"apparentGrossProfitAfterReclassCents": 800000,
"companyProfitChangeFromReclassCents": 0,
"bookProfitWithSeparateInventoryExpenseCents": 400000,
"bookProfitAfterInventoryCorrectionCents": 500000,
"profitDepressionFromPrematureInventoryExpenseCents": 100000,
"capitalizationCorrectionRaisesProfitCents": 100000,
"inventoryAssumption": "Separate purchase-period book scenario: unsold inventory was expensed outside the sold materials input; other operating expenses held at zero; not tax method advice",
"limitation": "This is teaching arithmetic from supplied invented inputs, not source authenticity, financial assurance or authority to post."
}Reproduce this calculation
Download the code and input into one folder, then run:
node reproduce.mjs margin-basis.input.jsonThe code checks declared units and identities and refuses unsupported inputs. No browser or customer account is used. Source authenticity and accounting approval require separate evidence.
Reviewed 2026-10-06. Level financial-control guidance, with visibly fictional teaching examples. The example shows a control boundary, not a measured customer outcome or industry benchmark.
Read this content revision history
Continue with the related financial decision →Guided synthetic example
See the check from input to decision
Revenue maps to customers, but a meaningful share of direct labor does not.
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.
Start with the source records
| Population | Total | Attributed | Coverage |
|---|---|---|---|
| Revenue | $500,000 | $490,000 | 98% |
| Direct labor | $180,000 | $126,000 | 70% |
| Materials | $120,000 | $114,000 | 95% |
Apply the documented check
Calculate coverage for every margin component and refuse precise customer margin when material costs are unattributed.
Surface the flagged result
Needs review
$54,000 of direct labor is unattributed, so customer-level margin is not yet decision-grade.
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
Missing job or customer coding, shared crews, payroll mapping, and timing differences could all produce the gap.
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.
Make the operating decision
Fix labor attribution or approve a documented allocation policy before comparing customer profitability.
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.
- Download the invented input and expected output.
- Replace one field at a time with a safe test value.
- Compare the result with the expected structure.
- 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":"customer-margin-attribution"}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