Demand inputs
Use historical registrations, active student populations, program structures, curriculum requirements, course availability, and planning assumptions.
UniversiTools Schedulers planning module
Plan the right course sections before timetable generation begins.
Course Forecasting helps academic and registrar teams estimate future demand, plan section counts, review instructor load, and prepare a stronger scheduling input before the Course Scheduler is launched.
- Demand and section planning
- Instructor-load visibility
- Forecast-to-schedule continuity
Selected schools, universities, and organizations working with White Mountain Technologies.
Overview
Move from historical counts to an explainable offering plan
Reliable scheduling starts with a realistic view of what should be offered. Forecasting combines curriculum requirements, student progression, registrations, historical demand, program and plan relationships, elective choices, and institutional assumptions into a structured planning process.
The result is not a black-box decision. Authorized users can review counts, assumptions, section recommendations, instructor implications, and planning changes before approving the forecast that feeds the scheduling process.
Capabilities
What Course Forecasting brings into one controlled process
Course Forecasting combines historical demand, current registrations, curriculum requirements, academic progression, program structures, planning assumptions, and staffing implications in one explainable offering process.
Program and plan analysis
Review demand by program, plan, sub-plan, department, campus, level, student group, or other approved dimensions.
Section recommendations
Translate expected demand into proposed section counts, capacities, teaching methods, and delivery requirements.
Instructor planning
Associate forecasted sections with teaching load, instructor availability, staffing assumptions, and departmental responsibility.
Scenario comparison
Compare alternative demand, capacity, offering, and staffing assumptions before approval.
Scheduling handoff
Provide the approved offering plan as structured input to course and classroom scheduling.
How it works
From institutional evidence to an approved course-offering plan
Forecasts are built from governed inputs and explicit assumptions, reviewed by academic owners, and then transferred into the scheduling process as approved planning data.
- 01
Collect
Bring together curriculum, program, registration, progression, course, and historical demand data.
- 02
Model
Apply the institution’s approved rules and assumptions to estimate demand and section requirements.
- 03
Review
Analyse proposed offerings, instructor implications, capacity, and alternative scenarios.
- 04
Approve and schedule
Confirm the forecast and pass the approved course-offering plan into the scheduling workflow.
Operational value
Operational value before timetable generation begins
For academic departments
A clearer basis for deciding which courses and how many sections to offer.
For registrars
More structured scheduling inputs and fewer late offering changes.
For faculty planning
Earlier visibility into teaching load and staffing pressure.
For students
Better alignment between required course demand and planned availability.
Implementation focus
Establish the evidence, assumptions, and ownership behind every forecast
Forecasting becomes useful when departments can explain why a section is recommended, which assumptions influenced it, and how the approved plan will be refreshed as demand changes.
Historical and curriculum data
Validate prior demand, enrollment, completion, repeats, prerequisites, program and plan requirements, progression patterns, and any known changes to the curriculum.
Planning assumptions
Document expected intake, continuing-student behavior, elective choices, capacity targets, cancellation rules, instructor implications, and the scenario assumptions applied.
Review and scheduling handoff
Assign academic ownership, compare forecast scenarios, record approved adjustments, and define when the resulting course and section plan becomes the scheduling baseline.
Scheduling principle
Rules remain institutional. Results remain reviewable.
Forecasting supports planning judgment; it does not replace academic ownership. Every recommendation remains traceable to approved data and assumptions, and authorized teams decide what becomes the official offering plan.
Questions
Frequently asked questions
Does Course Forecasting generate the timetable?
No. It prepares and approves the future course-offering plan. The deterministic Course Scheduler then generates the timetable from the approved scheduling inputs.
What information can be used in the forecast?
The implementation can use agreed data such as curriculum requirements, program structures, registrations, historical demand, academic progression, student groups, section capacities, and staffing assumptions.
Can departments compare scenarios?
Yes. Authorized users can compare alternative demand, section, capacity, and staffing assumptions before approval.
Can forecasts be reviewed by program or department?
Yes. Forecast information can be organized across the institution’s approved academic and organizational structures.
How does AI fit into forecasting?
AI can add insight, pattern recognition, explanation, and scenario interpretation. It does not replace the institution’s approved forecasting rules or the deterministic scheduling engines.
Next step
See Course Forecasting in the context of your institution
A focused demonstration can use your program structures, historical demand, registration data, progression logic, planning assumptions, and scheduling handoff to show how Course Forecasting would support your cycle.