Summer scheduling with AI: use history and weather carefully

A sunny Friday and a rainy Friday can create different demand on a terrace. Weather alone does not tell you how many people should work. The menu, reservations, opening hours and staff experience also affect the workload.

Plan with several sources of information and clear alternatives. The aim is service the team can deliver with a reasonable workload, including when demand differs from the forecast.

Start with your actual staffing

Review comparable weekdays and times. How many people worked, which roles were covered and where did waiting occur? Sales indicate demand but do not capture every task: preparation, closing, washing up and training take time even when the till is quiet.

In Vendion Staff, AI schedule suggestions use the restaurant’s own staffing history, alongside sales and booking information. They require historical data and provide a proposal to review. Previous schedules can contain both good practices and recurring staffing problems.

Treat weather as a scenario

Review what happened on similar days and add the local forecast. For example, prepare a main scenario with an open terrace and an alternative where some guests need indoor seating. Check capacity, workstations and staffing responsibilities in both situations.

Forecasts contain uncertainty, particularly further ahead. SMHI explains why weather forecasts can differ. A given temperature therefore does not provide a reliable percentage increase in drinks sales or an exact staffing requirement.

Review roles, not just headcount

Five people on a shift can deliver very different results depending on experience and responsibilities. Make kitchen, bar, dining room and training responsibilities clear. Do not add several new starters’ training to an experienced employee’s already full workload.

Check breaks, rest and other working-time conditions before publication. Rules can come from legislation and collective agreements; see the Swedish Work Environment Authority’s working-time guidance. A changed weather forecast is not blanket permission to cancel agreed shifts.

Learn from the result

After the week, compare scheduled and worked hours, sales and issues reported by the team. Note why outcomes differed: bad weather, a group booking, absence or a more labour-intensive menu item.

A low labour cost percentage is not a useful achievement if it comes with excessive workload or poor service. Use AI to organise information and explore proposals; management decisions and follow-up remain necessary.

See Staff pricing or book a demo using an actual summer schedule from your restaurant.