ProcureMind AI Procurement Leakage Report
Report delivery and governance controls
Report email path
Authenticated Industrial IQ runs attempt branded report email delivery and retain delivery status in the platform report inventory.
Human review required
Low-confidence or high-impact findings should be accepted, rejected, assigned, deferred, or marked needs-more-data before remediation.
No ERP write-back
Industrial IQ produces evidence and recommendations only. It does not autonomously change SAP, Maximo, Oracle, EAM, CMMS, procurement, inventory, or asset records.
CFO command view
Diagnostic components
| Score input | Value |
|---|---|
| emergency rows | 0 |
| stocked but purchased rows | 21 |
| repeated purchase groups | 1 |
| price variance groups | 1 |
| supplier alias groups | 1 |
| procurement leakage estimate | 39042.5 |
| required fields mapped | 2 |
| optional fields mapped | 10 |
| source rows profiled | 24 |
| estimated row value total | 169920.0 |
| supplier overlap families | 1 |
| missing commercial control rows | 0 |
| contract leakage signals | 1 |
Product maturity and competitive depth
| Priority | Implemented product capability |
|---|---|
| P0 | Emergency-buy, stocked-but-purchased, repeated-purchase, supplier-alias, price-variance, and vendor-overlap detection.; PO-to-stock evidence for buy vs transfer review.; Commercial control gaps where supplier or price fields are missing. |
| P1 | Supplier consolidation opportunities, buyer/category evidence view, contract-leakage signals, and emergency premium model.; Vendor overlap graph connecting item family, supplier alias, price variance, and purchase recurrence.; Procurement leakage score with action tracker items by buyer owner. |
| P2 | Buy vs transfer vs review recommendation engine with human approval controls.; Avoided-spend ledger and supplier consolidation QBR report.; Procurement benchmark pack by category, site, emergency rate, and supplier fragmentation. |
ICP packaging
| Package | Engines | Decision supported |
|---|---|---|
| CFO Pack | FinanceMind AI, PartsCleanse AI, InventoryMind AI, ProcureMind AI | Fund value realization only after capital exposure, carrying cost, procurement leakage, and review confidence are visible. |
| Procurement Pack | ProcureMind AI, PartsCleanse AI, InventoryMind AI, FinanceMind AI | Convert supplier, PO, duplicate stock, and price-variance evidence into sourcing action without unsupported savings claims. |
Advanced product insights
| Product output | Diagnostic value |
|---|---|
| buy transfer review | {"buy_review": 0, "human_review": 3, "transfer_review": 21} |
| vendor overlap graph | [{"family": "082b6edcf93a", "relationship": "item-family -> supplier aliases -> price/PO review", "supplier_count": 2}] |
| contract leakage signals | 1 |
| emergency premium model | {"base_premium_assumption": 0.0, "conservative_premium_assumption": 0.0, "emergency_value": 0, "limitation": "Premium is an estimate unless uploaded unit prices and normal-price references are present."} |
Buyer committee views
Can quantified exposure justify a diagnostic or remediation budget?
ProcureMind AI shows 432075.0 as the current capital or leakage signal before owner review.
Next question: Which findings have enough confidence and value to enter the financial business case?
Which findings threaten operational continuity, site readiness, or uptime?
1 high-attention findings require operational owner review.
Next question: Which findings must be resolved before the next outage, shutdown, or planning cycle?
Is the data ready for governed AI without ERP write-back risk?
Industrial IQ produced evidence from exports only and did not change ERP, EAM, CMMS, or procurement systems.
Next question: Which missing fields or governance gaps should be fixed in the next export?
Where do supplier, purchase, or stocked-but-purchased signals need review?
Procurement actions should be evidence-led and routed through human review before supplier action.
Next question: Which supplier or purchase findings are defensible enough for category review?
Will spare availability and catalog quality support maintenance execution?
Maintenance should use the evidence queue to protect planned work and critical assets.
Next question: Which findings block planned work, shutdown readiness, or critical equipment coverage?
Is this risk material enough to fund recurring diagnostic intelligence?
The result is diagnostic evidence, not an autonomous system change or unsupported ROI claim.
Next question: Should leadership fund the next diagnostic cycle, review queue, or remediation scope?
Evidence graph
20 nodes | 19 evidence relationships. This graph links uploaded source rows to findings, confidence, business impact, recommended actions, report output, and score history.
Renewal value view
Findings
| Analyzer | Finding | Severity | Confidence | Evidence | Action |
|---|---|---|---|---|---|
| Stocked-But-Purchased Analyzer | 21 rows show stocked-but-purchased leakage | HIGH | 82% | 21 | Compare PO lines with current stock and duplicate families before buying again. |
| Repeated Purchase Analyzer | 1 rows show repeated purchase patterns | MEDIUM | 72% | 1 | Consolidate equivalent purchase lines and create preferred buying rules. |
| Price Variance Analyzer | 1 rows show price variance exposure | MEDIUM | 72% | 1 | Normalize equivalent items and validate supplier price variance. |
| Supplier Alias Analyzer | 1 supplier alias clusters detected | MEDIUM | 70% | 1 | Normalize supplier aliases and route equivalent suppliers through a governed review. |
| Vendor Overlap Analyzer | 1 item families are bought through multiple supplier names | MEDIUM | 76% | 3 | Normalize supplier aliases and review preferred supplier rules for overlapping item families. |
Evidence records
| ID | Confidence tier | Severity | Description | Value | Source | Reason codes |
|---|---|---|---|---|---|---|
| E-de3526ce | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 3135.0 | row:1:MAT-001-001 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-10c31cff | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 4760.0 | row:2:MAT-002-002 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-60b3ee4b | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 6675.0 | row:3:MAT-003-003 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-6aad3bcd | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 8880.0 | row:4:MAT-004-004 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-00c9fc31 | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 11375.0 | row:5:MAT-005-005 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-de62416b | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 8160.0 | row:6:MAT-000-006 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-3999988e | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 2380.0 | row:8:MAT-002-008 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-d57c51e3 | Medium Confidence | HIGH | 21 rows show stocked-but-purchased leakage | 4005.0 | row:9:MAT-003-009 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-bd530acc | Medium Confidence | MEDIUM | 1 rows show repeated purchase patterns | 169920.0 | row:1:MAT-001-001 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-dbe4fb48 | Medium Confidence | MEDIUM | 1 rows show price variance exposure | 14520.0 | row:1:MAT-001-001 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-77867bcc | Medium Confidence | MEDIUM | 1 item families are bought through multiple supplier names | 3135.0 | row:1:MAT-001-001 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-81b5a118 | Medium Confidence | MEDIUM | 1 item families are bought through multiple supplier names | 4760.0 | row:2:MAT-002-002 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
| E-8018548c | Medium Confidence | MEDIUM | 1 item families are bought through multiple supplier names | 6675.0 | row:3:MAT-003-003 | material-id-present, description-signature, supplier-alias-signal, site-context, value-bearing-row, spec-token-match |
Recommended actions
Consolidate equivalent purchase lines and create preferred buying rules.
Owner: CPO | Due: 60 days
Compare PO lines with current stock and duplicate families before buying again.
Owner: CPO | Due: 30 days
Normalize supplier aliases and review preferred supplier rules for overlapping item families.
Owner: CPO | Due: 60 days
Normalize equivalent items and validate supplier price variance.
Owner: CPO | Due: 60 days
Normalize supplier aliases and route equivalent suppliers through a governed review.
Owner: CPO | Due: 60 days
Mapping and validation
| Input | Source column | Completeness | Confidence | Reason |
|---|---|---|---|---|
| po_number | po_number | % | % | |
| description | description | % | % | |
| material_id | material_id | % | % | |
| supplier | supplier | % | % | |
| unit_price | unit_price | % | % | |
| quantity | quantity | % | % | |
| order_date | order_date | % | % | |
| order_type | order_type | % | % | |
| emergency_flag | emergency_flag | % | % | |
| stock_on_hand | stock_on_hand | % | % | |
| site | site | % | % | |
| currency | currency | % | % |
Source fit, AI match, and normalization
| Quality signal | Value |
|---|---|
| source fit score | 100 |
| ai match score | 100.0 |
| diagnostic readiness score | 100 |
| required mapped | 2 |
| required total | 2 |
| optional mapped | 10 |
| optional total | 10 |
| required completeness | 100.0 |
| row count | 24 |
| column count | 30 |
| blockers | 0 |
| warnings | 0 |
| source fit band | Strong |
| ai match band | Strong |
| readiness band | Strong |
| diagnostic confidence score | 92.5 |
| diagnostic confidence band | Strong |
Normalization plan
| Engine field | Source column | Original sample | Normalized preview | Rule |
|---|---|---|---|---|
| Po Number | po_number | PO-2026001 | PO-2026001 | Normalize blanks, trim source values, preserve original evidence, and label any assumptions before engine execution. |
| Description | description | Oil & Gas pump bearing seal kit model 1 stainless 4 inch | OIL & GAS PUMP BEARING SEAL KIT MODEL 1 STAINLESS 4 INCH | Normalize case, abbreviations, punctuation, industrial units, specification tokens, and obvious spacing noise. |
| Material Id | material_id | MAT-001-001 | MAT-001-001 | Trim whitespace, preserve leading zeroes, normalize item/material identifiers, and keep original source reference. |
| Supplier | supplier | Industrial Supply Co | INDUSTRIAL SUPPLY CO | Normalize supplier aliases and vendor naming variants for leakage and overlap analysis. |
| Unit Price | unit_price | 1045 | 1045 | Parse PO unit price and compare with normal price signals when available. |
| Quantity | quantity | 3 | 3 | Parse numeric quantity, keep negatives for audit context, and separate blank/zero from missing. |
| Order Date | order_date | 2026-05-02 | 2026-05-02 | Parse purchase/work-order date into recency and aging bands. |
| Order Type | order_type | Standard | STANDARD | Normalize purchase order class, emergency type, stock/non-stock signal, and expedited context. |
| Emergency Flag | emergency_flag | N | N | Normalize Y/N, urgent, breakdown, rush, AOG, emergency, and expedited markers. |
| Stock On Hand | stock_on_hand | 1 | 1 | Parse on-hand stock quantity and preserve site-level balance context. |
| Site | site | Plant-2 | Plant-2 | Normalize plant, site, storeroom, facility, depot, or operating-unit labels. |
| Currency | currency | USD | USD | Normalize ISO currency code or use country/system assumption with visible limitation. |
Assumptions and limitations
Assumptions
- Uploaded data is treated as the source of truth for this diagnostic run.
- No ERP write-back is performed. Outputs are recommendations and evidence records only.
- Financial estimates use uploaded values where available and conservative assumptions otherwise.
- Industry language is adjusted for Oil & Gas: plants, wells, refineries, shutdowns, turnarounds, and asset integrity.
- Workbench scores were calculated before and after engine execution: source fit 100%, AI match 100.0%, mapping readiness 100%, diagnostic confidence 92.5%.
- Public sample report: deterministic AI2COE sample data was used. Replace with uploaded customer data for customer-specific findings.
Limitations
- Results are diagnostic signals, not final accounting entries.
- Low-confidence findings require human review before remediation.
- Missing source fields reduce confidence and may suppress some analyzers.
- Benchmarks are labelled assumptions unless validated by uploaded data.