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 Payroll Officer
Demand-based planning is genuinely evidenced: forecasts built from prior revenue and shift data, schedules generated automatically and optimised for hourly rates, qualifications and availability, labour budgets as a planning input, a live wage-cost dashboard, and a Shopify integration that imports sales data to predict demand. We found no public information on cross-location staff sharing or on any loop comparing forecast, proposed roster and actual hours, so this sits just under the top band. 1 2 3 10