Ocean + fleet network
Anonymized pattern: global ship tracking and fleet orchestration feeding inventory allocation — so port congestion and lane delay reshape replenishment before the stockout meeting.
Context
A logistics-linked manufacturing network watched vessels in a control tower and trucks in another system. Planners saw cover break after the fact.
Challenge
- Ship ETA lived outside the planning object.
- Fleet exceptions did not update replenishment.
- Expedites were reactive and expensive.
Approach
- Ingested lane/ETA and fleet exception signals into the knowledge graph.
- Inventory optimization used risk-adjusted cover.
- Explainable expedite vs wait recommendations with planner control.
Outcomes (qualitative)
Earlier visibility of lane risk into allocation. Fewer blind expedites. One decision surface for ocean and road exceptions.
Related reading
- Ship and fleet tracking — live GIS operations in the product
- Inventory optimization white paper — how lane risk turns into replenishment
- Case study: global manufacturing — the plant side of the same network
- Supply chain AI guide — definitions, use cases and evaluation criteria
Frequently asked questions
What does ocean and fleet visibility change in planning?
It turns a vessel delay into an inventory consequence. When a lane slips, the items on that lane are re-scored for cover, and the replenishment or allocation response is raised before the shortage reaches a customer.
What data feeds the lane and ETA risk view?
AIS vessel positions, port call and dwell data, carrier milestones and fleet GPS telemetry, joined to the purchase orders and inventory those shipments serve.
Does this replace a transport management system?
No. It reads from transport and visibility systems and adds the decision layer: what the delay does to cover, service and allocation, and which action to take about it.
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