aurelienclere-365/bpa-cowork-plugin/bpa-intercompany

bpa-intercompany

Runs a consolidated intercompany report across all active legal entities in BPA with anomaly detection. Designed for Senior Analysts who need exhaustive data coverage, D365FO-specific terminology, and actionable recommendations — not just raw numbers.

When to use this skill

Use when asked for:

• Intercompany reconciliation across entities
• GL summary by entity and account type (net balance, debits, credits, entry count)
• Intercompany indicators: packing slips, linked intercompany ledgers, sales orders,

reversing journal entries

• Purchase activity per entity: PO count/amount, invoice count/amount, vendor count,

invoice matching variances

• Anomaly flags: negative expense balances, invoices without POs, open POs without

invoices, missing intercompany reconciliation activity

Workflow

Step 1 — Retrieve schema

Call get_bpa_dataset_schema to identify:

• FactGeneralLedger — GL entries (LedgerDimension, CompanyId, AccountType, Amount,

Debit, Credit, EntryCount, IsReversing)

• FactVendorInvoice — purchase invoices (VendorId, PurchaseOrderId, Amount, CompanyId)
• FactPurchaseOrder — POs (PurchaseOrderId, CompanyId, VendorId, LineAmount, Status)
• DimCompany / DimLegalEntity — legal entity names and active status
• DimAccount — account type classification

Step 2 — GL summary by entity and account type

Call execute_dax_query:

EVALUATE
SUMMARIZECOLUMNS(
    DimLegalEntity[CompanyName],
    DimAccount[AccountType],
    "NetBalance",    [Net Balance],
    "TotalDebits",   [Total Debits],
    "TotalCredits",  [Total Credits],
    "EntryCount",    [Entry Count]
)
ORDER BY DimLegalEntity[CompanyName], DimAccount[AccountType]

Step 3 — Purchase activity per entity

Call execute_dax_query:

EVALUATE
SUMMARIZECOLUMNS(
    DimLegalEntity[CompanyName],
    "POCount",        DISTINCTCOUNT(FactPurchaseOrder[PurchaseOrderId]),
    "POAmount",       SUM(FactPurchaseOrder[LineAmount]),
    "InvoiceCount",   DISTINCTCOUNT(FactVendorInvoice[InvoiceId]),
    "InvoiceAmount",  SUM(FactVendorInvoice[Amount]),
    "VendorCount",    DISTINCTCOUNT(FactVendorInvoice[VendorId]),
    "MatchingVar",    [Invoice Matching Variance]
)

Step 4 — Anomaly detection

Run targeted DAX queries for each anomaly type:

Negative expense balances:

EVALUATE
FILTER(
    SUMMARIZECOLUMNS(
        DimLegalEntity[CompanyName],
        DimAccount[AccountName],
        "NetBalance", [Net Balance]
    ),
    [NetBalance] < 0 && RELATED(DimAccount[AccountType]) = "Expense"
)

Invoices without POs:

EVALUATE
FILTER(
    FactVendorInvoice,
    ISBLANK(FactVendorInvoice[PurchaseOrderId])
)

Open POs without invoices:

EVALUATE
FILTER(
    FactPurchaseOrder,
    FactPurchaseOrder[Status] = "Open"
    && ISBLANK(RELATED(FactVendorInvoice[InvoiceId]))
)

Step 5 — Assemble and present

Return a structured report:

1. GL Summary table — by entity and account type
2. Purchase Activity table — by entity
3. Anomaly flags table — with description and recommended action per finding

For each anomaly, provide a concrete recommendation:

• Negative expense balance → suggest reviewing the offsetting entry or incorrect posting
• Invoice without PO → flag for three-way match review
• Open PO without invoice → check with vendor or close if goods not received
• Missing intercompany reconciliation → escalate to Controller for elimination entry

Sample result

GL Summary — All entities

Anomalies detected (3)