Identify potential supply chain disruptions early, receive data-driven recommendations, and keep critical nodes in view at all times.
Global crises, port and transport disruptions, energy shortages, or supplier failures hit SMEs particularly hard: they often lack a dedicated risk-management team, transparency on bottlenecks, and a fast, well-founded decision basis.
The Supply Chain Radar (SCR) combines Crisis Radar, Bottleneck Analysis (knowledge graph), scenario simulation, and action recommendations in a SaaS dashboard. Events from 48 categories are captured worldwide, matched with your bills of materials & suppliers, calibrated by impact, and delivered as early warnings including recommended actions.
Sensitive company data remains protected: integration into data spaces according to IDS/GAIA-X plus a Trusted Data Hub for privacy-preserving, multi-party analytics (MPC/PPML).
Compliance fit. The SCR supports transparency and risk processes in the context of the German Supply Chain Act (LkSG) and the EU Corporate Sustainability Due Diligence Directive (CSDDD). This enables the SCR to fulfill the mandated duties for monitoring ESG risks.
Worldwide capture of potentially crisis-triggering events (nature, logistics, politics, health, etc.) – on a map, as a feed, with filters/subscriptions.
Legal requirements for monitoring supply chains and ESG risks (LkSG, CSDDD) are met and documented.
Import of bills of materials/material master data, automatic graph modeling, and identification of critical precursor products/components along the chain.
Configurable criticality (traffic-light), source weighting, region-/component-specific effects; prioritized alerts and recommendations (e.g., alternative sourcing, safety stocks, logistics rerouting).
Data stays with you; exchange via connectors & metadata. The Trusted Data Hub enables collaborative analytics/ML training without exposing raw data; the algorithm can also be protected.
Additional data sources and AI services can be added flexibly on a pay-per-use basis (app-store model) – from news sentiment to domain models.
“What if?” – e.g., port closure, supplier failure, or energy shortage; simulation of causal paths in the knowledge graph and assessment of revenue/service-level impacts.
Objective:
Early detection of failure risks in component procurement; prioritization of alternatives and measures.
Data sources:
CrisisRadar (48 categories), supplier/location data, BOM knowledge graph, market/price feeds.
Example results:
Early warning of bottleneck trends, suggestions for compatible alternative parts/suppliers, recommendations for action regarding safety stocks & expedites.
Objective:
Maintain stable production when energy supply/transport is disrupted.
Data sources:
Social/news signals, Outage Predictor, port/transport events (DCSA), supplier locations
Example results:
‘Port closure’ scenario with alternative routes, postponed call-offs and inventory measures; alert in the event of power failure risk with shift/order re-planning.
Ziel:
Lieferketten‑Resilienz mit PCF‑/Scope‑3‑Daten kombinieren (Beschaffung & Transport).
Datenquellen:
EPCIS‑Events (Track & Trace), PCF‑Daten, Scope‑3‑Inventar, OEM‑/Tier‑Datenräume.
Ergebnis‑Beispiele:
Risiko‑Heatmap kritischer Teile + CO₂‑Hotspots, Handlungspfad (Lieferant A→B, Rerouting, Material‑Substitution) inkl. Auswirkung auf Service‑Level & Emissionen.
Objective:
Combine supply chain resilience with PCF/Scope3 data (procurement and transport).
Data sources:
EPCIS events (track & trace), PCF data, Scope3 inventory, OEM/Tier data rooms.
Example results:
Risk heat map of critical parts + CO₂ hotspots, action plan (supplier A→B, rerouting, material substitution) including impact on service level & emissions.
We show your individual risk footprint live (including data space/TDH option).
Or from design to functional prototype solution in 12 weeks with Proof X (rapid prototyping).
