Every cafe has a 90-minute window where transaction volume doubles, the queue backs up, and the difference between a smooth team and a struggling one shows. Staff it wrong and you lose sales, lose reviews, and lose the regulars who left because the line didn't move.
The common mistake is not understaffing the rush. It's overstaffing the full day to cover it.
Finding the Real Peak
Most cafe managers believe their peak runs from 12:00 to 13:00. Pull 30 days of POS data by hour and the picture shifts. Transaction volume peaks at 12:15 and holds through 13:30. That 15-minute offset changes the schedule.
If staff arrive at noon and the rush starts at 12:15, the first 15 minutes of peak run with a team still getting settled. Starting shifts at 11:30 costs one extra hour of labour and prevents 45 minutes of degraded service. That trade is worth making.
Cafes that run this analysis find their actual peak is 15 to 30 minutes later than assumed. The reason: managers build schedules from memory, not transaction data.
Split Shifts and Staggered Starts
A split shift structure - arrive at 10:30, leave at 14:30 - covers morning prep and the lunch rush without paying a full-day employee who stands around from 15:00 to 18:00.
Staggered starts let you ramp coverage before the peak, not during it. Two staff at 08:00 for opening, two more at 10:30 for prep and overlap, one at 11:30 to catch the start of the rush. Total headcount matches demand without a flat staffing line running all day.
Put experienced staff at peak. New hires handle early prep where pace is lower and mistakes cost less. A new barista learning drink sequencing during a 45-minute lunch rush creates problems for the whole team.
A Legal Note on Split Shifts
In some jurisdictions, a split shift with a gap exceeding 1 hour triggers a split shift premium - an additional payment beyond standard hourly wages. Several US states, parts of Canada, and some EU member states include this requirement. Check local rules before making split shifts a standard model.
The Cost of Flat Scheduling
Paying for 8-hour shifts when demand concentrates in 2-hour windows is a structural cost problem. Teams that track hourly revenue against hourly labour cost find that 60-70% of staff time during off-peak hours generates 20-30% of daily revenue.
Scheduling from POS data rather than last week's rota corrects this over time. The first month of data surprises most managers. The second month changes their scheduling approach.
Rezano
Rezano's schedule view shows headcount against projected demand by hour. The gap between coverage and demand is visual and immediate - no spreadsheet required. Coverage decisions become obvious rather than approximate.