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Working Capital Exposure Methodology

Industrial IQ documentation

Working Capital Exposure Methodology documentation for AI2COE Industrial IQ buyers, operators, data owners, executives, and governance teams.

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Executive decision context

Working Capital Exposure Methodology

Summarizes value-at-risk, carrying-cost assumptions, emergency premium assumptions, and customer-specific diagnostic requirements.

This guide explains what problem is solved, who cares, what data is needed, what output is delivered, what ROI lever is affected, what report can be shared internally, and what recurring value is created.

UploadCSV export or sample dataset
Source FitRequired fields and data quality
AI MatchColumn aliases and confidence
NormalizeCanonical field preparation
DiagnoseEngine logic and evidence
ReportScore, actions, assumptions
RepeatScore history and renewal value
Required data by engine

Use this table before upload.

EngineRequired Data FileRequired FieldsOptional FieldsOutput GeneratedMinimum Viable UploadBest Upload
FinanceMind AI Inventory value file Material Id, Stock Value Description, Quantity, Unit Cost, Duplicate Family, Carrying Cost Rate, Emergency Premium Working capital score, evidence, report, actions, score history Material Id, Stock Value Required fields plus site, value, date, owner, asset, supplier, and criticality context where available.
Accepted CSV format

Prepare clean exports before upload.

Use UTF-8 CSV with one header row, one operational record per row, stable identifiers, ISO-style dates where available, numeric values without currency symbols, and separate columns for site, supplier, asset, quantity, value, and owner context.

Common errors: merged header rows, hidden subtotal rows, mixed currencies in one value column, duplicate column names, free-text dates, missing material or asset identifiers, and supplier names embedded inside descriptions.

If fields are missing: Industrial IQ still profiles source fit, but unmapped required fields reduce the AI Match Score, Mapping Readiness Score, diagnostic confidence, and report completeness until the user normalizes the data.

Sample row examples

Minimum viable row patterns.

  • Catalog Intelligence: Description: 6205-2RS bearing sealed SKF
  • Inventory Risk Intelligence: Material Id: MAT-100245 | Quantity: 42
  • Procurement Leakage Intelligence: Po Number: PO_NUMBER | Description: 6205-2RS bearing sealed SKF
  • Working Capital Intelligence: Material Id: MAT-100245 | Stock Value: 1850.00
Related engines

Which diagnostic should the buyer run next?

Related engine

FinanceMind AI

Duplicate capital exposure, carrying cost, emergency premium, and recoverable value scenarios.

Open documentation
Report anatomy

What the buyer can share internally.

Industrial IQ reports include scope, source-fit score, AI match score, mapping readiness, diagnostic confidence, score components, evidence records, assumptions, limitations, review requirements, action items, and recurring score history.

Working Capital Exposure MethodologyValue lever
Uploaded dataCustomer-specific diagnostic required
FinanceMind AIRelated diagnostic engine
EstimateAssumption-labeled until reviewed
Benchmark assumptionUploaded evidenceConfidence tierHuman reviewReportable value
Force Team validation

Working Capital Exposure Methodology buyer enablement checklist.

Problem solvedTurns an operational data question into source-backed diagnostic evidence.
Who caresCFO, COO, CIO, procurement, maintenance, reliability, ERP, governance, and board stakeholders where relevant.
Data neededCSV exports with stable IDs, descriptions, quantities, values, dates, site, asset, supplier, and owner context where available.
Output deliveredScores, evidence table, confidence tiers, executive report, action tracker items, score history, and governance status.
Value quantifiedWorking capital, carrying cost, emergency premium, dead stock, stockout risk, readiness gaps, or governance risk depending on diagnostic intent.
Decision supportedWhether to act, review, normalize data, escalate findings, fund remediation, or repeat the diagnostic cadence.
Report shared internallyExecutive, CFO, procurement, inventory, readiness, governance, or renewal value report.
Recurring valueBaseline score -> re-upload -> score movement -> action closure -> benchmark comparison -> renewal value report.
Assumptions and limitationsBenchmarks and estimates remain planning context until customer-specific uploaded data is analyzed and reviewed.
Trust controlsNo ERP write-back, evidence traceability, confidence tiers, human review, false-positive control, audit trail, and data-retention boundaries.
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