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The three primary methods of forecasting orders—qualitative, time series, and causal forecasting—each serve distinct purposes. Qualitative methods leverage expert judgment and insights, making them ideal for new products or markets with limited historical data. Time series methods analyze historical data patterns to predict future orders, suitable for stable markets with consistent trends. Causal forecasting links order predictions to specific variables, such as economic indicators, helping businesses understand the impact of external factors on demand.

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You can compare forecasting methods by one of these methods: 1- MAD(mean absolute deviation) 2-MSE (mean square error) 3-MAPE(mean absolute percentage error) Notes: 1-MAD is the preferred method since it does not require squaring the errors and this is the only difference between MAD and MSE . 2-If you want to relate the error relative to the actual demand use MAPE that is because in MAPE you will divide the error by the actual demand.


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