Industrial IQ Index

Research methodology Reviewed 2026-09-01 Methodology language is planning context until replaced by uploaded-data evidence.

Methodology and assumptions

AI2COE publishes planning ranges as assumptions, not promised-savings claims. Diagnostic reports replace these assumptions with uploaded-data evidence, confidence tiers, review status, and report-owner metadata.

Research methodologyEvidence type

2026-09-01Last reviewed

No ERP write-backGovernance boundary

Reference pointSource page

What this helps you decide

Industrial IQ Index buyer brief

The Industrial IQ Index is AI2COE's benchmark framework for measuring how ready an industrial organization's operational data is for trusted diagnostics, AI adoption, ERP modernization, and recurring decision intelligence.

Run Free Industrial IQ Snapshot Talk to AI2COE

Who uses itCFOs, COOs, procurement, maintenance, and ERP leaders building a defensible value case before budget approval.

Data neededMethodology assumptions plus uploaded catalog evidence when a diagnostic is run.

Next actionUse this methodology only as planning context; run working capital intelligence for customer-specific evidence and confidence tiers.

Short answer

Industrial IQ Index: what it means.

What is not claimed: The Industrial IQ Index is not an ERP certification, inventory optimization guarantee, or autonomous remediation instruction. Customer-specific results require uploaded-data diagnostics and owner review.

What is measured

Catalog Intelligence
Inventory Risk
Procurement Leakage
Working Capital Exposure
Asset-to-Part Readiness
Maintenance Readiness
AI Readiness
Governance Readiness

Methodology assumptions

Inputs that must be transparent.

Public index interpretation is a benchmark model until replaced by uploaded operational data.
Each signal must preserve assumptions, limitations, confidence tier, and human-review requirements.
Recurring uploads create stronger decision evidence than one-time benchmarks because score movement and action closure can be observed over time.

Calculation model

How the methodology is interpreted.

Upload exported data -> map fields -> run diagnostic engines -> generate evidence -> apply confidence tiers -> calculate scores -> produce executive reports -> create actions -> track recurring improvement.

How AI2COE uses it

From estimate to evidence.

AI2COE Industrial IQ turns index assumptions into uploaded-data diagnostics, score history, action tracking, planning comparison, and renewal value reporting across the eight engine model.

Related Industrial IQ engine

Working Capital Intelligence.

Run the relevant Industrial IQ diagnostic to replace public assumptions with customer-specific findings, confidence tiers, and report evidence.

Run Working Capital Intelligence

Analyst-style research structure

How this methodology should be read before a buyer acts.

Research question	Industrial IQ Index
Executive summary	The Industrial IQ Index is AI2COE's benchmark framework for measuring how ready an industrial organization's operational data is for trusted diagnostics, AI adoption, ERP modernization, and recurring decision intelligence.
Who should care	CFO, COO, CIO, procurement, maintenance, reliability, and ERP data owners.
What is measured	Catalog Intelligence Inventory Risk Procurement Leakage Working Capital Exposure Asset-to-Part Readiness Maintenance Readiness AI Readiness Governance Readiness
Why it matters	AI2COE Industrial IQ Index measures catalog intelligence, inventory risk, procurement leakage, working capital exposure, asset readiness, maintenance readiness, AI readiness, and governance readiness.
Data required	Public interpretation uses stated assumptions; customer-specific proof requires uploaded operational exports, mapped fields, evidence rows, confidence tiers, and review status.
Methodology	AI2COE separates methodology assumptions from uploaded-data diagnostics, then connects evidence, confidence, score, report output, and owner-reviewed action.
Calculation model	Upload exported data -> map fields -> run diagnostic engines -> generate evidence -> apply confidence tiers -> calculate scores -> produce executive reports -> create actions -> track recurring improvement.
Assumptions	Public index interpretation is a benchmark model until replaced by uploaded operational data. Each signal must preserve assumptions, limitations, confidence tier, and human-review requirements. Recurring uploads create stronger decision evidence than one-time benchmarks because score movement and action closure can be observed over time.
Limitations	The Industrial IQ Index is not an ERP certification, inventory optimization guarantee, or autonomous remediation instruction. Customer-specific results require uploaded-data diagnostics and owner review.
What is not claimed	The Industrial IQ Index is not an ERP certification, inventory optimization guarantee, or autonomous remediation instruction. Customer-specific results require uploaded-data diagnostics and owner review.
How to interpret the methodology	Use it as executive planning context only. Do not treat it as a customer result until Industrial IQ analyzes uploaded data and labels confidence, assumptions, and limitations.
What uploaded diagnostic replaces	Planning assumptions are replaced by mapped source records, evidence rows, confidence tiers, and score history.
Buyer committee interpretation	Finance reads exposure, operations reads continuity, procurement reads leakage, maintenance reads readiness, and CIO teams read governance risk.
Related Industrial IQ engine	Run Working Capital Intelligence
Related methodology	AI2COE benchmark methodology and Industrial IQ diagnostic evidence contract.
Recommended diagnostic	Run Working Capital Intelligence
CTA	Run Working Capital Intelligence

Industrial IQ Scorecard Grid

Eight intelligence dimensions turn operational data into board-readable decision evidence.

Each dimension starts as a benchmark question, then becomes customer-specific only after an Industrial IQ diagnostic maps uploaded data, generates evidence, assigns confidence, and preserves review status.

01 | PartsCleanse AI

Catalog Health

Duplicate-family evidence, description quality, UOM consistency, and catalog review readiness.

02 | InventoryMind AI

Inventory Health

Dead stock, excess inventory, slow movement, critical spare coverage, and stockout risk.

03 | ProcureMind AI

Procurement Leakage

Emergency buys, repeated purchases, supplier overlap, price variance, and stocked-but-purchased signals.

04 | FinanceMind AI

Working Capital Exposure

Inventory value, carrying-cost impact, recoverability assumptions, and finance interpretation.

05 | AssetMind AI

Asset-to-Part Readiness

Asset linkage, BOM coverage, critical equipment context, orphan spares, and coverage gaps.

06 | ReliabilityMind AI

Reliability Readiness

Work-order spare availability, false stockout risk, shutdown readiness, and maintenance action context.

07 | ReadyMind AI

AI Readiness

ERP export usability, data completeness, first-use-case fit, and transformation readiness gaps.

08 | GovernanceMind AI

Governance Readiness

Evidence traceability, confidence tiers, human review, auditability, and no-write-back controls.

Why it matters

Industrial AI and ERP transformation need explainable operating evidence.

AI and ERP programs stall when operational data is fragmented, duplicated, ungoverned, or not explainable. The Industrial IQ Index gives leaders a disciplined way to inspect readiness before transformation spend becomes a remediation surprise.

1Upload exported operational data.

2Map fields and run the relevant Industrial IQ engines.

3Generate evidence, confidence tiers, scores, reports, actions, and recurring score history.

Buyer interpretation

How each member of the buying committee reads the index.

CFO	Working capital exposure, carrying-cost risk, and financial evidence required before claiming value.
COO	Operational readiness, downtime risk, stockout exposure, and site-level action priority.
CIO	Data readiness, ERP modernization risk, AI governance, and source-system control before automation.
Procurement	Supplier fragmentation, emergency buys, stocked-but-purchased risk, and leakage review.
Maintenance / Reliability	False stockouts, work-order spare availability, asset-to-part gaps, and shutdown readiness.
Board	Benchmark visibility, governance confidence, recurring score movement, and decision discipline.

Sample index view

Illustrative scorecard example.

Catalog Intelligence	Illustrative score: 72 / 100; review duplicate-family evidence before remediation.
Inventory Risk	Illustrative score: 64 / 100; inspect dead stock, slow-moving stock, and stockout exposure.
Procurement Leakage	Illustrative score: 58 / 100; review emergency-buying and repeated-purchase signals.
Working Capital Exposure	Illustrative score: 61 / 100; replace assumptions with uploaded-data finance evidence.
Asset-to-Part Readiness	Illustrative score: 67 / 100; validate critical spare coverage and orphan spare signals.
Maintenance Readiness	Illustrative score: 69 / 100; inspect false stockout and work-order readiness signals.
AI Readiness	Illustrative score: 55 / 100; validate field completeness and governance readiness.
Governance Readiness	Illustrative score: 74 / 100; confirm confidence tiers, audit trail, and review ownership.

Planning disclaimer: Index examples are illustrative unless based on a customer-approved diagnostic dataset. Benchmarks are planning inputs and should be replaced by uploaded-data evidence before operational or financial decisions.

Run Free Industrial IQ Snapshot View Sample Reports Explore Industrial IQ How Industrial IQ Works

Industrial IQ platform bridge

How this connects to AI2COE Industrial IQ

Industrial IQ Index is not treated as an isolated content topic. Industrial IQ connects it to uploaded data, engine evidence, confidence tiers, executive reports, actions, score history, and governance review.

Run Free Industrial IQ Snapshot Explore 8 Diagnostic Engines

PartsCleanse AIcreates catalog evidence and duplicate-family findings.

InventoryMind AIextends catalog signals into inventory risk, dead stock, excess stock, and stockout exposure.

ProcureMind AIconnects supplier and purchase signals to emergency buying, repeat purchases, and leakage.

FinanceMind AItranslates operating findings into working-capital exposure, carrying-cost assumptions, and finance-review scenarios.

AssetMind AIconnects parts to asset relevance, equipment coverage, and plant-register context.

ReliabilityMind AIconnects spare availability to maintenance readiness, false-stockout risk, and shutdown planning.

ReadyMind AIevaluates ERP, data, governance, and AI readiness gaps before transformation spend.

GovernanceMind AImanages confidence, evidence traceability, human review, and auditability.

Benchmark interpretation

How leadership should use this benchmark.

Industrial IQ Index should be treated as an executive planning tool, not a substitute for a diagnostic. It helps a buyer ask the right question: is the exposure large enough to justify a governed review, and what data must be uploaded to replace assumptions with evidence?

Benchmark assumption Public planning range; not a customer-specific result

Uploaded-data proof Customer catalog, field mapping, confidence tiers, and evidence rows

Governed action Owner review, accepted findings, remediation plan, and audit trail

Buyer committee interpretation

CFOUse the benchmark to size possible working-capital exposure, then require uploaded-data evidence before budget approval.

COOTranslate the benchmark into operational risk: false stockouts, downtime pressure, planner trust, and service continuity.

CIOUse the benchmark to test whether ERP exports are clean enough for governed AI or require data-quality remediation first.

ProcurementUse the benchmark to identify supplier overlap, emergency-buying exposure, price variance, and duplicate-stock leakage.

Evidence discipline

What changes after a diagnostic run.

The benchmark becomes a customer-specific result only after AI2COE maps the export, validates field coverage, runs deterministic scoring, produces source-backed evidence, assigns confidence tiers, and labels any remaining assumptions.

Run Working Capital Intelligence Read Methodology

FAQ

Questions this research page should answer clearly.

What does the Industrial IQ Index measure?

It measures evidence readiness across catalog, inventory, procurement, finance, asset, reliability, readiness, and governance signals.

How is the index different from a benchmark?

A benchmark explains planning assumptions. An Industrial IQ diagnostic replaces assumptions with mapped source records, evidence rows, confidence tiers, and score history.

Why do recurring diagnostics matter?

Recurring diagnostics show whether actions are closing, risk is moving, planning comparison is improving, and the value case supports renewal or multi-site expansion.

Decision framework

What this page helps leaders decide.

Definition

The Industrial IQ Index is AI2COE's benchmark framework for measuring operational data readiness across catalog, inventory, procurement, finance, asset, maintenance, AI, and governance dimensions.

Commercial relevance

The index helps executives understand where fragmented operational data may be weakening investment decisions, ERP modernization, AI readiness, working capital, and operational continuity.

Operational symptoms

Low readiness appears as duplicate catalog records, inventory risk, procurement leakage, weak asset-to-part coverage, false stockout signals, poor AI readiness, and unowned evidence.

Required input files

Operational exports from ERP, EAM, CMMS, inventory, procurement, asset, maintenance, finance, and governance systems.

Diagnostic method

Industrial IQ maps fields, runs relevant diagnostics, scores dimensions, applies confidence tiers, and converts evidence into executive interpretation.

Evidence model

Index output includes dimension scores, supporting evidence, assumptions, limitations, owner actions, and recurring score movement.

Buyer-role interpretation

Boards read governance confidence, CFOs read capital exposure, COOs read readiness, CIOs read data risk, and operating teams read action priorities.

Traditional approach vs Industrial IQ

Traditional maturity models often rely on interviews. The Industrial IQ Index is designed to be strengthened by uploaded operational evidence.

Trust boundary

Index examples are illustrative unless based on a customer-approved diagnostic dataset.

Recommended next step

Run an Industrial IQ Snapshot when the buyer needs routing clarity, view sample reports when the buyer needs proof format, request a diagnostic discussion when scope and data availability are known, or explore pricing when the buying path is ready for commercial review.

Related Industrial IQ pages

Industrial IQ platform · Industrial IQ Snapshot · Sample reports · Documentation · Trust Center

Run Free Industrial IQ Snapshot Sample reports · Diagnostic discussion · Pricing

Research authority map

Move from definition to method, evidence, and decision guidance.

Research assets use one controlled vocabulary and keep methodology, assessment, evidence standards, and future benchmark governance distinct.

Open Research Center

Framework

Canonical definitions and readiness pillars define what the assessment is designed to evaluate.

Method

Assessment inputs, field mapping, source fit, and review steps remain inspectable.

Evidence

Observed, Derived, Estimated, and Hypothesis classes protect interpretation quality.

Executive use

Decision guidance connects research to proceed, constrain, remediate, investigate, or defer choices.

Research method

This research page defines the method, evidence class, and publication boundary.

Research Center pages support Industrial AI Readiness authority. They define methodology, evidence classes, terms, and publication boundaries without presenting published benchmark outputs as market proof.

Audience

Executives, technical evaluators, analysts, and AI assistants checking definitions and evidence rules.

Evidence to prepare

Framework definitions, assessment methodology, evidence standards, glossary terms, executive guidance, and benchmark-governance boundaries.

Output

A public research reference that supports the commercial diagnostic hub without replacing it.

Trust boundary

Methodology-led content only. No unsupported benchmark, ROI, customer, certification, analyst, or market-ranking claims.

Research Center Commercial diagnostic hub Evidence standards Category guide