The system calculates your forecasts on a monthly basis based on your sales history. The algorithm creates a specific forecast model for each product, or product grouping, then uses this to make a prediction of future sales. It's based on a machine learning algorithm, so that when new sales data is imported, the forecast models are readjusted and your forecasts calculated in real time.
The lead demand is then calculated from this based on your lead time (or overridden forecast period if that is set).
For component items, the sales history is calculated from your finished goods' sales multiplied by the BOM quantity.
You can also manually set your forecasts, so if this is set then that will take precedence.
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