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 Frontline Employee
This is real demand-based planning: forecasts built from previous weeks' revenue and Shopify sales data, automatic schedules optimised for hourly rates, qualifications and my availability, and a live dashboard of wage cost against demand. I found no public information on cross-location staff sharing or on the planner accepting or adjusting the auto-built roster, and the AI Scheduling Agent is named without its forecasting method being documented. 2 3 10