Staff and labor
Staff records, schedules, tip pools, and labor reporting.
Openfront Restaurant already has more than a basic user table. Staff records include restaurant-specific fields, and there are working screens for scheduling, tip pooling, and labor analysis.
Staff data that already exists
A user record can store:
- restaurant staff role
- employee ID
- hourly rate
- phone number and photo
- PIN field for quick workflows
- onboarding status
- emergency contact details
- certifications
- active or inactive status
That gives you a decent base for real operations, not just login management.
Main labor surfaces
Weekly schedule
The schedule screen is a weekly roster view where managers can:
- assign shifts by day
- attach a staff member and role
- set start and end times
- store hourly rate per shift
- edit or delete shifts later
Tip hub
Tip pools are already modeled and have a dedicated screen for:
- house pool distribution by hours worked
- role-based weighted pools
- settled and unsettled batches
- viewing calculated distributions before marking a batch distributed
Labor report
The labor report pulls together time entries and completed-order sales to show:
- total hours
- payroll cost
- labor percentage
- sales per labor hour
- total tips
- role-level breakdowns
How teams usually use it
Create and maintain staff records
Start with the user record. Add the staff role, hourly rate, phone, and any emergency or certification data you want to keep close.
Build the schedule
Use the weekly schedule screen to assign shifts and keep the roster visible by day.
Record worked time
Time-entry data and shift clock fields are already part of the model layer and feed reporting. That is what the labor and tip views depend on.
Review labor after service
Use the labor report and tip hub to understand whether the shift made sense financially, not just whether it felt busy.
Current limitations
- The reporting side of labor is stronger than the staff-clock experience right now.
- Permissions around who can manage people, roles, and wage data still need a cleanup pass.
The staff module is already useful for scheduling and labor visibility. The next big win here is polishing the operational clock-in and permissions story.