Proactive Value Chain Resilience

Resilience starts below
your supplier list.

Every supply chain risk tool tracks your Tier 1 and Tier 2 suppliers. Most stop there. PMG traces every assembly to its raw material source — eight levels deep — and scores what it finds. What lives in those lower tiers changes the risk picture in ways no supplier map can reach.

T1 Declared TTR 8–12 wk Supplier's own estimate
of their recovery time
PMG Computed TTR 52+ wk Computed from the material
chain beneath the supplier

The gap — 40+ weeks — originates at Level 5 in the material genealogy: a sintered rare earth magnet production process with maximum manufacturing complexity, concentrated in a handful of facilities globally. The Tier 1 supplier's estimate is honest. It does not include what they cannot see beneath themselves.

Six analytical surfaces. Six questions your leadership is already being asked to answer.

Each surface is a standalone capability with its own data model, scoring logic, and explainability chain — all grounded in the same PMG material graph.

01

Risk patterns in your material structure

Where does a single deep-tier node — often invisible at Tier 1 — sit on the only viable path for two or more of your top-level assemblies? PMG identifies every such diamond pattern across the full material hierarchy, scores each by the number of assemblies affected and recovery complexity, and surfaces the concentration clusters, single-source fan-outs, and tooling lock-in distributions that repeat across your portfolio. These are the structural signatures of systemic risk — not individual flags, but recurring patterns that tell you where your supply architecture is load-bearing.

Diamond detection Concentration clusters Single-source fan-outs Tooling lock-in mapping

02

Where is your supply base geographically concentrated?

Start with the question already on your CPO's desk: how many strategic suppliers share the same country, and does the concentration warrant action? PMG answers that at the supplier level — and then extends the picture further. Supplier headquarters is not where the risk lives. What matters is the physical location where a specific material is processed, refined, or extracted. A single smelting region can account for 60–70% of a critical material's global production capacity. A single industrial district can hold the majority of a specialty polymer's qualified compounding capacity. Neither fact appears on a supplier profile. Geographic concentration analysis maps your full supply base — from T1 suppliers down to deep-tier material sources — to their processing geographies and ranks your assemblies by exposure to each concentration point.

Country-material heat map Assembly exposure by geo cluster Jurisdiction-level aggregate

03

What does a tariff change actually cost you — by material, by assembly?

A new tariff schedule lands. The question your finance and procurement teams face immediately: which products are affected, at what percentage of material cost, and is there a lower-exposure sourcing alternative? Answering that from a spreadsheet takes weeks and produces estimates. Tariff and trade risk analysis maps commodity codes to material nodes across every tier depth. When a schedule changes — Section 301, Section 232, EU CBAM — the impact propagates through the material chain automatically.

HS code attribution by material node Cost exposure by assembly Alternate sourcing simulation

04

Which of your suppliers are financially deteriorating — and which assemblies does that put at risk?

The first question is straightforward: which of your Tier 1 suppliers is under financial stress right now? The harder question is the one no tool currently answers: what about the sub-tier suppliers — at T3, T5, T7 — whose financial deterioration will ripple through your supply chain before you ever hear about it? When a critical sub-tier supplier goes bankrupt, the OEM feels the pinch after the incident. There is no early warning because there was no visibility to begin with. PMG maps suppliers all the way to Tier 8 in lockstep with the material graph. This gives the platform a structured basis for determining which sub-tier suppliers actually matter — based on the materials they supply, the number of assemblies they feed, single-source status, and TTR profile. Financial health monitoring is then applied to that prioritised set of deep-tier suppliers, not indiscriminately across thousands of entities. Tracking covers six dimensions — financial health, operational performance, compliance posture, cybersecurity exposure, ESG trajectory, and regional risk — with distress phase trajectory updated continuously through our financial health monitoring partners. Every signal, at every tier, is connected to the supplier's position in the material graph — so you see which assemblies are exposed and how far the exposure runs before the event occurs, not after.

6-dimension health scoring Distress phase trajectory OTIF% + quality defect rate Assembly exposure linkage

05

Which of your materials are approaching regulatory restriction — before the restriction takes effect?

ELV, REACH SVHC, RoHS, and Critical Raw Material exposure lives in the material composition of your assemblies — not in your supplier certificates. A supplier can be fully certified today while their sub-tier inputs contain substances on restriction watch lists or approaching authorisation deadlines. Regulatory compliance exposure maps restriction lists to the chemical compound and substance data at your material nodes. When restriction lists are updated, exposure propagates automatically to all affected assemblies.

ELV · REACH SVHC · RoHS CAS-level attribution Restriction timeline tracking CRM scarcity mapping

06

Where in the risk landscape does each supplier and material actually sit?

At its simplest: which of your T1 suppliers need attention first? Risk quadrant positioning places every supplier on a two-axis grid — risk severity against strategic importance — answering that question at the supplier level immediately. As material depth is layered in, the same positioning extends to material nodes: a single deep-tier material can shift a supplier's quadrant entirely, moving it from apparent leverage into hidden risk. Position is computed from the graph, not from self-reported data. Strategic risk, hidden risk, leverage, and background zones each carry different recommended actions — whether your team is starting with T1 supplier visibility or working with the full eight-level picture.

4-quadrant risk scatter Hidden risk identification Portfolio prioritisation view
Prescriptive Intelligence

From finding alternatives to understanding trade-offs

Most prescriptive tools recommend an alternative supplier. ECC evaluates whether the alternative is viable — materially, structurally, and regulatorily — before recommending it.

+

What most tools do: flag a risk, suggest an alternative supplier in a different country, initiate dual-sourcing outreach. The answer is always "find another supplier." It is useful. It is not sufficient.

01 — MATERIAL SUBSTITUTION

Evaluate whether substitution works — and under what conditions

When a material is at risk, the prescriptive layer queries a database of 570,000+ materials across 80+ international standards for global equivalents. Mechanical and physical properties of each candidate are compared against the performance specification. Compliance status against ELV, REACH, and RoHS is checked for each option. Multi-criteria scoring ranks candidates by functional fit, supply concentration, and sustainability profile. The output is an engineering-grade substitution brief — not a sourcing alert. Procurement and engineering work from the same document.

02 — SOURCING VIABILITY

Verify that the alternative can actually be sourced at scale

Once a candidate substitution material is identified, the prescriptive layer maps qualified manufacturers across a live supply graph of direct and indirect dependencies — country-of-origin, capacity indicators, dependency strengths, geographic distribution. The question "does an alternative exist?" is answered alongside "is this executable, by whom, and what does their supply graph look like?" Simulation runs before the recommendation surfaces to the team.

03 — CROSS-DOMAIN CONSEQUENCES

Understand what the action does across tariff, regulatory, and risk domains simultaneously

A prescriptive action that reduces tariff exposure might change the DPP compliance baseline or introduce a new geographic concentration. Because the prescriptive orchestration layer draws from the same material graph across proactive, trade, and regulatory domains, every recommendation is evaluated for cross-domain consequences before it surfaces. The procurement lead and the compliance lead see the same picture. No coordination overhead. No domain surprises discovered after the fact.

Resilience Fabric

Beyond the computable. The three pathways above draw from the material graph and partner intelligence networks. ECC's prescriptive layer also draws from a curated resilience knowledge base — built from hundreds of supply chain research papers and documented historical incidents — containing the mitigation strategies that were deployed, what worked, and what did not. When the platform identifies a critically important sub-tier supplier under financial stress, it can surface options that go beyond replacement: supply chain finance instruments, inventory pre-build programmes, collaborative recovery frameworks. The right action is not always the obvious one.

PMG is the graph underneath. The six analytical surfaces above are what you navigate it with. Below is why this graph can do what others cannot.

Four architectural facts that separate PMG from every supplier-level tool

These are not feature claims. They are decisions about where risk actually lives — and what it takes to reach it.

01

Eight levels deep

PMG traces every assembly from the finished product at Level 1 to the raw ore source at Level 8. Most tools stop at Tier 2. The material constraints that drive the longest recovery times — rare earth processing concentration, specialty alloy tooling lock-in, chemical synthesis bottlenecks — live at Level 4 through Level 7. They are invisible to any tool that does not go there.

170,000+ nodes · 8 BOM levels · 540+ suppliers

02

Material and supplier, simultaneously

PMG scores both supplier nodes and material nodes in the same pass. A supplier score without a material score misses half the risk picture. The same Tier 1 supplier can have low operational risk and catastrophic material-level exposure depending on which processing path their components follow three levels below them.

Dual-node scoring · 4-vector risk model

03

TTR computed, not declared

Suppliers self-report recovery timelines. Those estimates reflect their own operations — not the chemistry of their material chain. PMG computes Time-to-Recover from the graph itself, tracing the actual constraint: tooling recut times, chemical re-qualification periods, geographic concentration at the ore source. The difference between a declared TTR and a computed one can exceed 40 weeks.

Computed from material physics · Not supplier-declared

04

Every score explained

100% of risk scores carry a structured reasoning chain — traceable to the specific computation that produced it, at the moment it was produced. Not reconstructed after the fact. Auditable by compliance teams. Readable by procurement analysts. Ingestible by AI systems for question-answering and workflow guidance. Explainability is infrastructure in PMG, not a feature added afterwards.

XAI audit trail · 100% coverage · Dual-consumer output

Real findings from a real dataset

From a modelled European BEV bill of materials running live on the PMG platform — 170,000+ nodes across eight levels of a representative electric vehicle supply chain.

115

nodes in a single EPS sub-graph carry both tooling lock-in and single-source constraints simultaneously — a combination that produces a TTR floor independent of supplier capacity.

PMG Analysis · EPS Sub-Graph · European BEV Archetype

52+

weeks is the material-computed TTR for the NdFeB magnet path in a BLDC assist motor — against a Tier 1 declared estimate of 8–12 weeks. Root cause: Level 5, sintered rare earth block production.

PMG Analysis · NdFeB Path · European BEV Archetype

365d

Time-to-Recover at Level 5 and Level 6 of the rare earth path — computed from process chemistry and geographic concentration at the T6 supplier in this chain.

PMG Analysis · Nd Metal Path · European BEV Archetype

PMG ANALYSIS · MODELLED EUROPEAN BEV ARCHETYPE · NOT OEM-VALIDATED DATA · FIGURES ILLUSTRATE PLATFORM METHODOLOGY APPLIED TO REPRESENTATIVE SUPPLY CHAIN

One Investment · Two Returns

The data layer that serves risk intelligence and regulatory compliance simultaneously

PMG builds its material graph using science-quality life cycle inventory data — CAS-level compound data, international LCI datasets, critical minerals sourcing intelligence. This is the same data foundation required for EU Digital Product Passport compliance.

The work ECC does to build your material genealogy for risk intelligence simultaneously builds your DPP compliance baseline. Every European OEM facing DPP deadlines is already paying for this data work twice — separately for risk and for compliance. PMG does it once.

Return 01

Material-level risk intelligence

Dual-node risk scoring, computed TTR, diamond pattern detection, geographic concentration — grounded in the material graph.

↕ same data layer

Return 02

EU DPP compliance baseline

Science-validated material data ready for Digital Product Passport declaration — accelerating compliance before the first supplier questionnaire.

Your stack stays exactly as it is.

PMG integrates with SAP and other SCM systems through published APIs or SAP's own agentic connectors. Your existing procurement workflows, ERP configuration, and supplier relationships are untouched.

ECC reads the data it needs on a need-to-know basis, through a defined and auditable integration layer. Nothing more.

  • Read-only access. ECC does not write to your systems.
  • API-native. No direct database access, no raw data extraction.
  • Defined scope. Integration covers only the plant and vehicle line in scope.
  • Auditable. Every data access through the integration layer is logged.

Your data never leaves your infrastructure.

ECC deploys into your own Azure subscription and your own Neo4j instance. We provision and configure. You own the infrastructure.

Az
Azure deployment in your subscriptionECC provisions the platform into your existing Azure tenancy.
N4
Neo4j instance in your accountThe material graph runs in a Neo4j instance you own and control.
🔒
Security documentation on requestBuilt to enterprise standard. Security architecture, threat model, and testing results available on request.

How a pilot works

Scoped to one plant and one vehicle line. Validated risk intelligence output in 4–6 weeks. No permanent commitment on either side.

Phase 1

Weeks 1–2

Data Connection

We connect to your BOM and supplier data through published APIs. Read-only access, defined scope. No raw data extraction, no persistent access beyond the integration layer.

Phase 2

Weeks 2–4

Graph Build & Scoring

PMG builds the material genealogy graph for your scoped vehicle line. Every node scored. Every TTR computed from the material chain. Every reasoning chain generated and stored.

Phase 3

Weeks 5–6

Validated Output Review

We walk through the output with your team. Every finding is traceable. Every number has a computation behind it. You decide what to do with it.

Platform Technical Brief

Architecture, scoring methodology, agent intelligence layer, integration model, and deployment design — written for technical evaluators, procurement architects, and risk leads who want depth before a conversation.

PDF · 6–8 pages · Requires email

What procurement teams ask before engaging

No. Your SAP instance, ERP, and procurement workflows stay exactly as they are. ECC integrates through published APIs, reads what it needs for the scoped engagement, and operates as a separate intelligence layer. Nothing in your existing stack changes.

In your own Azure subscription and your own Neo4j instance. ECC provisions and configures the infrastructure — you own it. Your data never moves to ECC's environment, and we do not maintain access after the engagement scope is completed.

Not yet. Our primary security mechanism is architectural: your data never leaves your own infrastructure. We provide security architecture documentation, threat model, network isolation design, and testing results on request, built to enterprise standard.

BOM data, supplier master data, and relevant procurement data for the scoped plant and vehicle line. Read-only access through defined APIs. The data scope is agreed and documented before any connection is established.

No. ECC deploys into your infrastructure — not into a shared cloud environment operated by ECC. Your graph instance is yours, running in your Azure subscription, isolated from all other customers.

The pilot produces a validated risk intelligence output for the scoped plant and vehicle line. We review the findings with your team. You then decide whether and how to extend coverage. There are no automatic commitments and no subscription that activates at the end of the pilot period.

Through defined APIs only. No direct database access, no access to internal networks beyond the API layer, no persistent connection beyond the scope of the active engagement.

See what lives beneath
your Tier 1 suppliers.

A scoped conversation. No commitment. We show you the methodology and what it finds in a value chain like yours.

Request Pilot Access →

One plant · One vehicle line · 4–6 weeks · No stack changes required

Download Platform Technical Brief

Architecture, scoring methodology, integration model and deployment design — written for technical evaluators.

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