Forecasting & smart scheduling
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Forecasting projects your own history forward; smart scheduling turns that projection into a rota.
Demand forecasting
Analytics โ Forecasting predicts sales and product demand from trading history, allowing for trend and the weekly and seasonal shape of your business. Use it to plan purchasing, spot a category turning down, and set expectations for a period before it starts.
Reorder points
Forecast demand plus supplier lead time gives a sensible reorder point โ the level at which ordering now means arriving before you run out. Feed those into Auto Reorder rules so purchase orders are drafted for you when stock hits the line.
Demand Planning takes the same idea across the range for a buying cycle.
Smart scheduling
AI Tools โ Smart Scheduling forecasts demand by hour and recommends cover against it. The output is a suggestion: quiet mid-week mornings usually turn out overstaffed, and one predictable peak usually turns out under-covered.
Peak analysis shows the busiest hours by day, which is often more actionable than the headline weekly total.
How much history it needs
Forecasts improve with data. A few weeks gives a rough shape; a full year lets it see seasonality. Treat early forecasts as directional and expect them to sharpen.
Where it will be wrong
A forecast only knows what already happened. It cannot see a bank holiday moving, a road closure, a competitor opening, or the weather. Take the projection, apply what you know, and adjust โ that combination beats either alone.
Closing the loop
Compare forecast against actual afterwards. The gap tells you both how much to trust the model and which of your own assumptions were off.
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