Roster building & demand planning
How this is scored
How a plan gets built across locations, roles and qualifications — templates, staffing requirements, forecasting from sales or occupancy, and whether the product proposes a roster or only draws one.
0 — A shared calendar of shifts; no templates, no roles or qualifications, and no notion of how many people a shift needs.
3 — Shift templates and a weekly grid per location, with roles attached, but staffing needs and qualifications are the planner's memory rather than the system's.
5 — Templates, roles and qualifications, staffing requirements per shift, open shifts, multiple locations and departments, and coverage gaps shown before publication.
8 — Demand-based planning from a named data source (POS revenue, footfall, occupancy or bookings), automatic roster proposals the planner can accept or adjust, labour cost shown against budget while planning, and cross-location staff sharing.
10 — Planning closes the loop: forecast, proposed roster and actual hours compared in one place, the proposal explains which rule or demand figure drove each assignment, and the vendor documents the forecasting method rather than calling it AI.
The Operations Director
The captured pages promise AI-supported demand forecasting, automated scheduling optimisation and a central view of labour costs across sites and regions, but we found no public information on templates, roles, qualifications, staffing requirements per shift, open shifts or coverage gaps, and nothing on cross-location staff sharing. No data source behind the forecast is named — no POS revenue, footfall or occupancy figure — and the method behind the AI claim is undocumented, so demand-based planning and cost-against-budget-while-editing cannot be verified at all. 1 2