Key takeaways
- The feasibility test is the match: curriculum audit demand against staff loading supply.
- The contact ratio governs supply; the cited ~0.78 target is an English example.
- The model is re-run at every staffing change, not filed after the first pass.
- Expertise, rooms, and part-time patterns constrain the match beyond raw period counts.
The match that decides feasibility
Demand: the curriculum audit prices the signed-off structure in periods per subject. Supply: the staff loading chart prices each teacher's capacity at the chosen contact ratio. Feasible means they match, subject by subject, not just in total; a surplus of humanities periods does not staff a physics shortfall.
The match is a living check. It is re-run whenever staffing changes, and a resignation in May re-opens it however final the plan felt in March.
Running the model
One pass, then re-runs on every change.
- Price the structure: periods per subject from the curriculum audit.
- Price the staff: periods each teacher can give at the chosen contact ratio.
- Collect must-teach and can-teach preferences from heads of department.
- Match demand to supply per subject, using can-teach flexibility where it is real.
- Audit specialist rooms against the structure's demand for them.
- Name the risks the match reveals: sole specialists, thin subjects, part-time concentration.
How to do this in Smootables: the staffing data in one place
Teaching eligibility
Define which teachers can be selected automatically for each study unit.
Resources holds the supply side: teachers with Weekly max hours and Yearly max hours, rooms and equipment as their own resource types, and student groups and students alongside. Teaching eligibility records which teachers can be selected automatically for each study unit, a direct home for the can-teach scale; it is optional and feeds the solver's automatic selection while manual assignment stays open.
Availability rules carry the part-time patterns, and the planning workload panel audits assigned against maximum hours per teacher as the plan fills, so the loading chart's numbers stay visible while allocation happens rather than in a separate spreadsheet.
The constraints beyond the count
Three things constrain the match beyond raw periods. Expertise: staff teach only what they are certified and skilled for, which is what the must-teach/can-teach scale encodes. Rooms: specialist spaces are hard constraints with their own supply and demand, covered in depth in room and equipment constraints. Patterns: part-time staff bring room sharing, parents'-evening availability, and two-week-cycle friction, so their concentration per department belongs in the model.
The availability mechanics behind that last one are in teacher availability.
Questions planners ask about staffing the curriculum
What happens when a sole subject specialist resigns?
The sourced finding is blunt: the programme can effectively disappear overnight. In one survey, 76% of leaders were unsure they had systems to retain a programme and only 32% thought a new teacher could pick up a complete one. Mid-year departures also recruit from a thinner pool, which is why sole-specialist subjects deserve a named risk line in the model.
Why collect "can teach" and not just qualifications?
Heads of department express staffing preference on a must-teach to can-teach scale, and the can-teach entries are what give the model room to move. More honest flexibility recorded up front means fewer impossible corners when the match is tight.
Rooms too, or just people?
Rooms, emphatically. A specialist room is a hard constraint: History placed in the only free Chemistry lab is not a solution. If specialist room supply does not cover the structure's demand, the model fails regardless of staffing.