The blog
Signed opinion on warehouses, fleets, planning and the systems underneath. Where the field library traces a handoff, the blog takes a side on it.
logistics
Advance ship notices, carrier load tenders, freight invoices, and status updates still travel largely as EDI documents between trading partners, often through value-added networks. APIs are growing, but most carriers and shippers support both, and the edge cases live in EDI maps nobody has touched in years.
logistics
The choice between Ultra-Wideband and Bluetooth Low Energy for warehouse tracking depends on the consequence of a wrong location, the physical environment, and the operational burden the facility can support.
logistics
A logistics company evaluating quantum computing for fleet routing faces an immediate architectural decision: the hardware paradigm. You can map your constraints to a quantum annealer, or build variational circuits for gate-based processors accessed through a managed service like Amazon Braket.
logistics
AMRs depend on Wi-Fi, warehouse management systems, and vendor fleet managers. Production rollout is where the integration work begins.
logistics
When logistics executives ask about quantum computing, the real question is usually whether the organization knows its own operations well enough to formulate the problem.
logistics
A polygon on a map triggers arrival alerts, detention billing, theft alarms, and driver time records. In practice, GPS drift at the fence edge, polygons nobody maintains, sites that changed their gates, and alert volumes that dispatchers learn to ignore undermine it. Designing geofences, dwell rules, and exception handling that operations and billing can rely on.
logistics
Onboard axle load sensors, tire pressure monitoring, and RFID tire tags each produce data that only pays off when it reaches maintenance, dispatch, and compliance systems. Integration, calibration, and ownership determine whether the data helps or hurts.
logistics
Every planner knows the forecast will miss. The operation fails not because demand moves but because the plan assumes it won't. Build buffers and triggers for the error.
logistics
The warehouse can pick, pack and ship perfectly and the delivery can still fail at the doorstep. The last mile is about promises kept, updates that explain, and rescheduling that's easy.
logistics
A warehouse management system can't fix an item record that's wrong before the first pick. Wrong dimensions, missing weights, duplicates and stale locations are an operational problem with an owner.
logistics
Grid-based automated storage packs bins in stacks with robots running on top, storing far more in the same footprint than shelving. It also turns the warehouse into a single machine: throughput depends on software, robots, and charging, one failure can stop picking, fire protection is harder in a dense grid, and the vendor relationship lasts as long as the building. What IT and operations need to plan for before signing.
logistics
Most logistics optimization failures are not algorithm problems. They are master data, constraint capture, and planner trust problems.
logistics
Temperature loggers and real-time sensors produce the records that prove a shipment stayed within range. When an excursion happens, the data decides whether product is destroyed, who pays, and whether a regulator is involved.
logistics
Automation is a multiplier: a conveyor moves a bad decision as efficiently as a good one. Map the work as it actually happens and fix the handoffs and data before you lock them into equipment.
logistics
The boundaries between warehouse management, execution, and control systems are defined by latency, state ownership, and exception handling—not feature matrices. Draw them before the automation vendor draws them for you.
logistics
If your team makes three calls to find one shipment, you don't have visibility. Visibility is a reliable answer to one question, connected to the order and the customer commitment.
logistics
The diagnostic port, the vehicle network, and the gap between what telematics vendors promise and what the hardware actually exposes.
logistics
Foundation models pretrained on large collections of time series can forecast a new series with little or no training, which helps with new products, sparse history, and catalogs too large to model one by one. They are weaker at promotions, price changes, and causal drivers the model never saw, and harder to explain to a planner who has to defend the number.
logistics
Reservoir computing trains only a linear readout on a fixed random network, making it cheap for chaotic time series but hard to govern in production logistics systems.
logistics
The yard between the gate and the dock is where location and condition data collide, and where no single system owns the outcome.