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Solutions for airports

Airport ground staff scheduling driven by the flight schedule

Airports that run their own ground or terminal services staff to the combined schedule of every airline they serve. ShiftLine turns that schedule into demand per function, sizes the team and builds compliant shift lines.

What planning teams deal with

  • Demand depends on the whole airport's schedule, not one airline's.
  • Passenger-facing functions need enough staff to meet service-level targets at the peaks.
  • Equipment has to be planned with the people who use it.
  • Shift lines must follow local labor law and any collective agreements.

Demand you can trace to flights

See demand per function by weekday, as an average, a realistic busy day (P85) or the maximum, and break any interval down to the rule and flights behind it.

Demand profile for the Ramp workgroup by weekday: a 15-minute staffing curve with average, P85 and max views, and a breakdown of the demand rule behind the selected interval.
Demand per workgroup from flights and demand rules, with average, busy-day (P85) and max views.

How ShiftLine helps airports

  • Demand from every airline's flights

    Import the schedule for the station and apply rules by airline, aircraft type or service type.
    Demand planning
  • Passenger-driven staffing

    Counters and check-in sized from passenger flow with Erlang C service-level targets.
  • Equipment planning

    Equipment demand from the same rules, per interval, next to staff demand.
  • FTE with shrinkage

    Shift fit and monthly shrinkage turn work hours into the FTE to hire and roster.
  • Optimized shift lines

    Lines that cover demand at the lowest paid hours, or to the FT/PT mix you set.
    Shift bidding
  • Labor law and agreements

    Rules with sources, applied in the solve and checked on every line.
    Labor-contract compliance

See ShiftLine with your own flights and contracts

Book a walkthrough with your schedule, demand standards and labor rules, or start right away in a workspace with demo data.