Machinery Shipment Tracker

Work backward from the commissioning date: riggers, crane, site access and the OEM engineer are all bookings made against the freight ETA. The board's job is keeping that ETA honest weekly so the bookings move WITH it — the expensive failure mode is the site team learning of a two-week slip one week out, after the crane window was paid for.

The constraint encoded in the site / install date field: a machine arriving early with no riggers booked is as useless as one arriving late. Generic trackers show where freight is; cargo-specific tracking shows whether the plan still works for what this freight IS — and that difference is where the expensive mistakes hide.

Whoever learns first — typically the ops person reading carrier notifications — with a single named owner per board so statuses can be trusted. For this cargo the discipline matters doubly: downstream parties (QA, sites, sales) make real commitments off these rows, so 'the board is always current' has to be a rule, not an aspiration.

That's the compounding payoff: a quarter of rows is this lane's real transit and exception record for THIS cargo — far more persuasive than generic carrier stats. Late-rate by carrier, slip distribution, exception causes: export, pivot, and bring it to the QBR. Specific cargo data wins arguments generic benchmarks lose.