Reading Your Loads Honestly
Inventory shows one route in exact depth; Load Monitoring interrogates the whole network for flights breaking a load condition. Reading them well means keeping booked and flown numbers apart.
Fog of war covers your rivals in PlaneSim, but never yourself. Your own flights report exact sold counts and exact loads, with nothing withheld. Two pages carry that truth at two altitudes. Inventory is the microscope: one route, every departure, day by day. Load Monitoring is the dragnet: a query across the whole network for flights that break a load condition you define.
The microscope
Pick a directed pair on Inventory and you get four layers, top to bottom.
The KPI strip summarizes the route: flown load factor over the last 7 days, booked-ahead load, cargo load, and on-time performance. The load summary underneath is a class-by-day pivot of the next 5 days, seats sold against seats offered per cabin plus belly cargo kilograms, today first. This is the booking curve at a glance. Current inventory then lists every departure in the window as its own row, with tail, per-class loads, cargo, delay and status, tabbed by flight number. At the bottom sit the pair settings and the weekly capacity history, the same pricing and service block that Market Analysis carries, so a fare change never requires leaving the page that justified it.
Booked is not flown
The KPI strip deliberately separates two numbers that beginners merge. Flown load factor is history: what the last 7 days actually carried. Booked-ahead load is a claim about the future, and a moving one, because bookings build gradually as daily passes run over each departure in the window. An empty cabin three days out is normal; the same cabin empty on the morning of departure is a verdict.
Money follows the same discipline. Booked revenue is recognized only when a flight arrives, so a booked seat is not yet an earned fare. The curve tells you how demand is arriving. Only the flown numbers tell you what you kept.
The dragnet
Load Monitoring is a genuine query builder. You set filters and submit; the server evaluates every condition and returns matching flights.
| Filter | Options |
|---|---|
| Time windows | Five 24-hour buckets of departure time, from 48 hours back to 72 hours ahead, combined freely |
| Geography | Origin country, destination country |
| Fleet | One aircraft type you operate |
| Flight number | Matches numbers starting with a prefix, such as one number group |
| Load condition | A cabin class or belly cargo, at or below, or at or above, a percentage |
Results show each flight with per-class loads, cargo load, its worst class, delay and status. They are sortable and searchable, and capped to the first few hundred matches, so on a big network tighten the filters before you widen them.
Two sweeps worth stealing
The empty-seat sweep: economy at or below 70 percent, departing in the next 24 to 48 hours, run weekly. Each hit deserves a click-through to the route and a judgment about whether the problem is price, timing, or the route itself, and then a response through the pricing tools.
The spill sweep: any class at or above 95 percent in the recent windows. A flight that sells out early is leaving money on the table, because demand that finds no seat is lost that day, not deferred to your next departure. Raise the fare, upgauge, or add frequency.
Cargo has its own rhythm. The cargo condition finds belly space flying empty, and belly cargo is pure marginal revenue on flights whose costs are already committed.
Where it points next
Neither page tells you why a number is wrong, only that it is. The competitive half of the answer, meaning who else is on the pair and how the market ranks every option, lives on Market Analysis. The reference for both pages is Inventory & load monitoring on the wiki, and both are live now at play.theplanesim.com.