Definition #
ML models balancing inventory, transportation, and demand signals.
Key Characteristics #
- Digital twin simulations
- Route optimization
- Supplier risk scoring
- Carbon-aware logistics
Why It Matters #
Reduces logistics costs by 22% and improves OTIF by 35% (McKinsey).
Common Use Cases #
- Just-in-time manufacturing
- Cross-docking optimization
- Supplier payment terms
Examples #
- Blue Yonder Luminate
- Coupa Supply Chain
- o9 Solutions
FAQs #
Q: Data integration needs?
A: ERP, WMS, and IoT sensor data required for full optimization.
Q: Implementation timeline?
A: 3-6 months for enterprise deployments with clear data pipelines.