Start with historical demand and adjust it for the things you already know are coming, seasonality, events, opening hours, planned changes. Turn that demand into workload, divide by the productive time each employee actually has, then add shrinkage, skills, and a buffer for uncertainty before you build the schedule.
“We schedule based on gut feel.”
“Demand changes, but staffing does not keep up.”
“We need a simple way to forecast staffing.”
A staffing forecast answers one practical question: how many people, with which skills, should be on at each point in the day? It begins with demand, but it only earns its keep when it ends in a schedule a manager can actually staff.
Collect historical demand by interval
Adjust for seasonality and known events
Convert demand into workload
Divide workload by productive time
Add shrinkage, skills, and uncertainty
The most common mistake is forecasting demand and stopping there. A demand chart is interesting; what a manager needs is a number of people by shift, role, and time.
The second is hiding uncertainty behind a single figure. When demand swings, show a range and plan how you will respond at each end of it, rather than pretending one number is a sure thing.
If this problem sounds familiar, these are the next places worth reading.
Historical demand by day and time, average work duration, opening hours, known events, absence assumptions, and required skills. Most of it is already sitting in your past schedules and timesheets.
Every schedule cycle. Compare what you forecast against what actually happened, then update the assumptions before the next schedule, that feedback loop is what makes the forecast better over time.
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