Smart Scheduling Saves 15 hrs/week for Restaurant Group
The Problem
An Oshawa restaurant group with three locations was spending 4–5 hours per week per location manually building staff schedules. Managers were working from memory and gut feel — no connection to actual sales forecasts or historical traffic data. The result was predictable: over-staffed on Monday nights, slammed and understaffed on Friday evenings, and staff frustrated by unpredictable hours.
Key Pain Points
- 12–15 hours/week spent manually building schedules across 3 locations
- No connection between scheduling and POS sales data or busy/slow patterns
- Chronic over/under-staffing driving up labour cost and hurting service
- Staff dissatisfaction and high turnover partly tied to unpredictable scheduling
Our Approach
We deployed an AI scheduling tool that pulls historical sales data from the POS system and generates optimized staffing recommendations for the upcoming week — broken out by day-part and station. Managers review and approve in minutes instead of building from scratch. A simple shift-swap portal for staff eliminated back-and-forth manager texting.
POS Data Integration
Connected the POS system to pull 12 months of hourly sales data per location for baseline modelling.
Demand Pattern Modelling
Built hourly demand profiles per day-of-week, season, and local event calendar for each location.
Auto-Schedule Generation
Configured the system to generate a draft schedule each Monday morning — managers review and publish in under 20 minutes.
Staff Shift Portal
Set up a simple shift-swap portal so staff can trade shifts directly without manager involvement.
Results Dashboard
Weekly Scheduling Hours — Manager Time Reclaimed
Key Outcomes
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