Procurement leakage score
Use the score as a diagnostic signal that needs evidence review.
Industrial IQ | AI2COE | ProcureMind AI
ProcureMind AI Procurement Leakage Report
Report takeaway
What this sample report answers
ProcureMind AI Sample Report shows how AI2COE Industrial IQ turns sample operational data into evidence rows, confidence tiers, score output, actions, report value, and governance controls. Sample results prove workflow and output structure; uploaded customer data is required for customer-specific findings.
Sample boundary: private source files are not required to view this sample. In live diagnostics, uploaded source files are used to generate report packs and then purged.
Review owner
Enterprise buyers inspecting report quality before uploading private operational data.
Input files
Engine-specific operational CSV exports or deterministic AI2COE sample data.
Diagnostic evidence
Evidence, scores, assumptions, limitations, actions, and governance status.
Next action
Sample report output map
How to evaluate the Procurement Leakage Intelligence output bundle
This visual map helps buyers trace the sample report as a product output: source file, field mapping, evidence rows, confidence context, report pack, and governed owner action stay connected before any private upload.
PO line, supplier alias, price variance
Inspect source context, confidence, assumptions, and limits.
ProcureMind AI Procurement Leakage Report
Use HTML and PDF views for buyer committee review.
Owner, status, next review
Keep remediation buyer-controlled after the sample is replaced with uploaded data.
Baseline and rerun movement
Use recurring reviews to see what changed after accepted actions.
CSV, mapping, data dictionary
Give data owners the field expectations before private upload.
Output boundary: this sample proves output structure and workflow only. Uploaded operational data is required before customer-specific findings can be reviewed.
Evaluation kit
Download the supporting assets for this Procurement Leakage Intelligence sample.
Use the HTML sample to inspect report structure, then use the supporting files to understand what data owners would prepare before replacing sample assumptions with uploaded-data evidence.
PDF
Offline review artifact for buyer committees.
Sample CSVDeterministic sample input used for testing the workflow.
MappingColumn mapping guide for source-fit review.
DictionaryField definitions and expected diagnostic meaning.
Product pageReview the Procurement Leakage Intelligence engine page.
Trust boundary: sample assets are deterministic demonstration files. Live diagnostics remain read-only, require owner review before action, and do not write back to ERP/EAM/CMMS systems.
Executive Summary
0.0Procurement leakage score
Board-Level RiskRisk level
Medium ConfidenceConfidence
13Evidence records
Source mode: Sample dataset result. Sample results demonstrate workflow and report structure; uploaded-data results replace assumptions with customer source evidence.
Score interpretation: Lower health or readiness scores indicate higher unresolved exposure, weaker readiness, or stronger review need. Scores are deterministic and derived from mapped source fields, findings, evidence, and component inputs.
Executive interpretation: Focus on asset integrity, turnaround readiness, working capital exposure, and audit-safe ERP preparation.
Report delivery and governance controls
Email
Report email path
Authenticated Industrial IQ runs attempt branded report email delivery and retain delivery status in the platform report inventory.
Review
Human review required
Low-confidence or high-impact findings should be accepted, rejected, assigned, deferred, or marked needs-more-data before remediation.
ERP safety
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.
Data handling: Uploaded source files are processed to generate the diagnostic report pack and then purged. Summary metrics and audit metadata may be retained for governance.
CFO command view
432075.0Capital exposure signal
51849.0-120981.0Recoverable range
77773.5Annual leakage signal
Board-Level RiskBoard attention band
Diagnostic components
0EMERGENCY ROWS
21STOCKED BUT PURCHASED ROWS
1REPEATED PURCHASE GROUPS
1PRICE VARIANCE GROUPS
1SUPPLIER ALIAS GROUPS
39042.5PROCUREMENT LEAKAGE ESTIMATE
active_deterministic_evidence_engineDIAGNOSTIC DEPTH
2REQUIRED FIELDS MAPPED
Score formula: 100 - procurement_risk/source_rows*100 with stocked-but-purchased and emergency rows weighted higher Random score used: False
| 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 |
| validation issue count | 0 |
| validation blocker count | 0 |
| prompt injection signal count | 0 |
Product maturity and competitive depth
Competitive position: Competes against ERP-native PO reports by linking catalog duplication, stock availability, supplier aliases, and price variance into one governed diagnostic.
| 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 review role. |
| 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
CFO
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?
COO
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?
CIO
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?
Procurement
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?
Maintenance
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?
Board
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
Model: Source Record -> Finding -> Evidence -> Confidence -> Business Impact -> Recommended Action -> Review Status -> Report -> Score History
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
432075.0EXPOSURE IDENTIFIED
5REVIEW QUEUE SIZE
5ACTIONS CREATED
0ACTIONS REVIEWED
34566.0CONSERVATIVE VALUE REALIZATION
69132.0BASE VALUE REALIZATION
monthly for high-risk sites; quarterly for controlled sitesNEXT REVIEW CADENCE
Recurring value interpretation: Compare this run against the next upload to show exposure reviewed, actions completed, score movement, and remaining risk.
Key Findings
Trust control: Each finding must be interpreted with its confidence, evidence count, mapped fields, and source records. Similar-looking industrial records may still require owner review before action.
| 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-03403ad6 | 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-ea1744c2 | 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-0873f72a | 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-d001e292 | 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-bbff566d | 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-56007039 | 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-1d719e30 | 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-b92be16d | 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-a1e06f66 | 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-a8954dda | 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-caaa3cf0 | 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-a5010913 | 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-d1f2bf8a | 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
P1
Consolidate equivalent purchase lines and create preferred buying rules.
Owner: CPO | Due: 60 days
P0
Compare PO lines with current stock and duplicate families before buying again.
Owner: CPO | Due: 30 days
P1
Normalize supplier aliases and review preferred supplier rules for overlapping item families.
Owner: CPO | Due: 60 days
P1
Normalize equivalent items and validate supplier price variance.
Owner: CPO | Due: 60 days
P1
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 | 100.0% | 100.0% | Exact ERP alias |
| description | description | 100.0% | 100.0% | Exact ERP alias |
| material_id | material_id | 100.0% | 100.0% | Exact ERP alias |
| supplier | supplier | 100.0% | 100.0% | Exact ERP alias |
| unit_price | unit_price | 100.0% | 100.0% | Exact ERP alias |
| quantity | quantity | 100.0% | 100.0% | Exact ERP alias |
| order_date | order_date | 100.0% | 100.0% | Exact ERP alias |
| order_type | order_type | 100.0% | 100.0% | Exact ERP alias |
| emergency_flag | emergency_flag | 100.0% | 100.0% | Exact ERP alias |
| stock_on_hand | stock_on_hand | 100.0% | 100.0% | Exact ERP alias |
| site | site | 100.0% | 100.0% | Exact ERP alias |
| currency | currency | 100.0% | 100.0% | Exact ERP alias |
Source fit, AI match, and normalization
100%Source fit score
100.0%AI match score
100%Mapping readiness score
92.5%Diagnostic confidence score
Workbench interpretation: Source fit measures whether the uploaded file contains recognizable inputs. AI match measures column-mapping confidence. Diagnostic readiness measures whether the normalized mapped data can support trustworthy engine output.
| 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.