Case studies
Simulation: overtime across 96 controllers
How was overtime shared across 96 controllers? This simulation examined the unit’s existing workforce and working-position allocation. It followed an April scenario with 120 controllers, which added 24 staff and produced 37 overtime shifts.
The scenarios used different months and leave assumptions. Their results should not be interpreted as a controlled headcount comparison or measured production savings.
Scenario setup
| Input | Value |
|---|---|
| Strategic roster | 1–31 May 2022 |
| Tactical period examined | 2–8 May 2022 |
| Workforce | 96 employees in 12 teams of eight |
| Pattern | Morning–Afternoon–Night–Rest–Off–Off (MANROO) |
| Morning duty | 07:00–14:00 |
| Afternoon duty | 14:00–21:00 |
| Night duty | 21:00–07:00 |
The staffing requirements were 15 ATC positions for morning and afternoon duties, 12 at night, and two supervisor positions on every shift.
Annual leave was distributed using annual averages. May contained 152 leave days, with no English-training or other duty days registered. The April scenario had contained 488 days: 326 annual-leave and 162 English-training days.
Tactical allocation assumptions
The positions were executive (EXE), planner (PLN), supervisor (SUP) and air flow manager (AFM). EXE and PLN work allowed a maximum of two different positions, one hour each, before at least an hour’s break.
The configuration allowed SUP position work for 100% of morning and afternoon duties and 50% of night duties. AFM coverage ran from 07:00 to 18:00. These were model inputs, not general ATC break requirements.
SkyRoster generated the strategic and tactical rosters using constraint optimisation. The outputs were analysed in Power BI.
Overtime result
The model covered the specified requirements using 118 overtime shifts: 56 morning, 57 afternoon and five night shifts. That was 81 more overtime shifts than the April scenario.
Five of the 96 employees (5.2%) had no overtime. The other 91 (94.8%) received between one and three overtime shifts. Two employees received three overtime shifts; they represent 2.08% of the full 96-person workforce. All teams had overtime assignments.
Reported time on position
| Period | Reported time on position |
|---|---|
| Morning EXE/PLN | 57.14%–71.42%, or four to five hourly slots |
| Morning SUP and AFM | 100% |
| Afternoon EXE/PLN | 42.85%–71.42%, or three to five slots |
| Afternoon SUP | 100% |
| Afternoon AFM | 57.14% |
| Night SUP | 50% |
| Night EXE/PLN | Approximately 46%–54% in the source summary |
The weekly EXE/PLN hours summary ranged from five hours for one employee to 26 for another. Some employees also worked other position types; the employee with five EXE/PLN hours had a further nine hours in the other reported category.
The team position-time summaries reported minimum, average and maximum values of 11, 21 and 36 hours for EXE/PLN, and 16, 28 and 47 hours for SUP/AFM.
The reported team share of time on position did not exceed 62.31% for EXE/PLN. Including SUP and AFM, it ranged from 55.56% to 65.44%.
Interpretation
The simulation shows how the specified demand and leave could be represented with the available staff and additional duties. It does not establish that the same result would apply with different absence, qualification or demand assumptions.
The source uses approximate night-duty percentages and does not explain their relationship to its hourly-slot counts. It also uses an ambiguous “efficiency factor”. Those labels should not be used as an additional performance claim.
Review the published case studies and methodology for further context.