| Plan Items - Forecast Settings (cpdsp1110m000) |  |
| Use this session to maintain the forecast parameters ERP LN must use to compute the demand forecast based on historical demand data of the specified plan item. The Generate Demand and Inventory Plan (cpdsp1210m000) session uses these parameters to generate demand forecasts. Related topics To compute the demand forecast Demand forecasting in Enterprise Planning To use an overview session To maintain records in an overview session
Fields | Description
Average Forecast Error | The mean forecast error that is computed during the demand forecast calculation for generating a demand plan for a plan item. Related topics To compute the demand forecast Forecast errors and seasonal correlation
Automatic Update of Forecast Parameters | If this check box is selected, you can recalculate the forecast parameters by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. You can recalculate the following fields: The Type of Trend Influence field The Type of Seasonal Influence field The Seasonal Cycle Time field The Smoothing Factor for Demand field The Smoothing Factor for Trend field The Smoothing Factor for Season field The Smoothing Factor for Forecast Error field The Degree for Polynomial Regression field If this check box is cleared, you must manually maintain the forecast parameters. Related topics To compute the demand forecast
Channel | Specify one of the channels that you defined for the plan item in the Plan Item - Channels (cpdsp5100m000) session. Related topics Channels in Enterprise Planning
Critical Tracking Signal | If you selected the Tracking Signal for Demand Forecast check box, enter the critical value that the tracking signal for the demand forecast should not exceed. Allowed values Enter a value in the range 0 to 1. If the Tracking Signal for Demand Forecast check box is selected, ERP LN uses the tracking signal for the demand forecast during a demand calculation according to the exponential smoothing method. If the tracking signal exceeds the critical tracking signal, the exponential smoothing method uses an increased value of the smoothing factor for demand instead of the value of the Smoothing Factor for Demand field. The greater the value of the critical tracking signal, the less nervously the exponential smoothing method reacts to forecast errors. A reasonable value for the critical tracking signal is between 0.5 and 8. To have an effect, the critical tracking signal must be substantially greater than the Smoothing Factor for Demand field. Related topics To compute the demand forecast Forecast method: exponential smoothing
Degree for Polynomial Regression | This field is only available if you selected Polynomial Regression in the Forecast Method field. Allowed values Enter a whole number in the range of 0 to 9. The degree of the polynom that is used in demand forecast calculations based on the polynomial regression method. Related topics To compute the demand forecast Forecast method: polynomial regression
Forecast Method | The mathematical method that ERP LN uses to compute the demand forecast. Each forecast method uses the historical demand data of the time period between the scenario start date and the current plan period. ERP LN retrieves the historical demand data from the Customer Deliveries field in the Item Master Plan (cprmp2101m000) session. Related topics To compute the demand forecast Forecasting methods
Mean Absolute Deviation | The mean absolute deviation or forecast error is the average difference between the demand forecast and the actual demand. Note This forecast error is not the mean absolute forecast error on which the tracking signal for demand forecast is based. Related topics To compute the demand forecast Forecast errors and seasonal correlation
Moving Average Offset | This field determines the starting point for the calculation of the moving average, and it is only available if you selected Moving Average in the Forecast Method field. The moving average offset is the number of calendar days between: The starting point for the calculation of the moving average The forecast period Related topics To compute the demand forecast Forecast method: moving average
Moving Average Period | This field is only available if you selected Moving Average in the Forecast Method field. Allowed values Enter a value that is less than or equal to the value of the Moving Average Offset field. The length of the period for which the moving average must be computed (in calendar days). The starting date of this period is determined by the Moving Average Offset field. Related topics To compute the demand forecast Forecast method: moving average
Mean Relative Deviation | The mean relative deviation or forecast error of the forecast demand against the actual demand. Related topics To compute the demand forecast Forecast errors and seasonal correlation
Scenario | The scenario for which you set the plan item's forecast parameters in this session. Related topics Scenarios in Enterprise Planning
Scenario | The description or name of the scenario.
Plan Item | The plan item for which you maintain the forecast settings. This can be the normal plan item, or the channel-related plan item. Note If you specify the special demand on plan item level and not on channel level, then the special demand is input for the Special Demand field in the Item Master Plan (cprmp2101m000) session.
Seasonal Correlation Factor | The seasonal correlation factor is a relative factor, which indicates to what extent there is a seasonal cycle for a given demand pattern. The maximum value of the seasonal correlation factor is 1.0. ERP LN calculates the factor on the basis of the historical demand figures and the Seasonal Cycle Time field. Related topics To compute the demand forecast Forecast errors and seasonal correlation
Seasonal Cycle Time | The cycle time of the seasonal demand pattern, expressed in calendar days. Allowed values Enter a value of more than 0 and less than 1000 calendar days. If the demand for the plan item has a yearly recurring variation, the seasonal cycle time is 365 days. If the Type of Seasonal Influence field is not Not Applicable, you cannot modify this field. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine the seasonal cycle time by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast
Standard Deviation | The standard deviation of the forecast error. The standard deviation of the forecast error is the difference between the forecast demand and the actual demand, compared to the mean forecast error. Related topics To compute the demand forecast Forecast errors and seasonal correlation
Smoothing Factor for Demand | This field is only available if you selected Exponential Smoothing in the Forecast Method field. Allowed values Enter a value in the range 0 to 1. The Smoothing Factor for Demand field is a factor in the computation of the demand forecast according to the exponential smoothing method. If the smoothing factor increases, the influence of demand data from the recent past on the demand forecast also increases. In other words, an increase of the smoothing factor will cause a stronger reaction of the demand forecast to recent demand fluctuations. Values between 0.1 and 0.3 usually give satisfactory results. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine the smoothing factor by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast Forecast method: exponential smoothing
Smoothing Factor for Forecast Error | This field is only available if you selected Exponential Smoothing in the Forecast Method. Allowed values Enter a value in the range 0 to 1. The Smoothing Factor for Forecast Error field is a factor in the computation of the mean forecast error during the demand forecast calculation according to the exponential smoothing method. If this factor increases, the influence of recent forecast errors on the mean forecast error also increases. You must enter a value close to 1 (for example 0.8) in order to obtain a fast response of the mean forecast error to fluctuations in the demand. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine this smoothing factor by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast Forecast method: exponential smoothing
Smoothing Factor for Season | The Smoothing Factor for Season field is a factor in the computation of the demand forecast according to the exponential smoothing method. Allowed values Enter a value in the range 0 to 1. If the smoothing factor increases, the influence of demand data from the recent past on the seasonal influence also increases. In other words, an increase of the smoothing factor causes a stronger reaction of the demand forecast for a following seasonal cycle on recent demand fluctuations in the current seasonal cycle. A reasonable value is something between 0.1 and 0.3. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine this smoothing factor with the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast Forecast method: exponential smoothing
Smoothing Factor for Trend | This field is only available if you selected Exponential Smoothing in the Forecast Method field. Allowed values Enter a value in the range 0 to 1. The Smoothing Factor for Trend field is a factor in the computation of the demand forecast according to the exponential smoothing method. If the smoothing factor increases, the influence of demand data from the recent past on the trend influence also increases. In other words, an increase of the smoothing factor causes a stronger reaction of the demand forecast to recent forecast errors. A value of 20% of the value of the Smoothing Factor for Demand field usually gives satisfactory results. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine this smoothing factor by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast Forecast method: exponential smoothing
Type of Seasonal Influence | This field determines to what extent there is a seasonal influence on the demand forecast. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine the seasonal influence by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast
Type of Trend Influence | This field determines to what extent there is a trend influence on the demand forecast. Note If the Automatic Update of Forecast Parameters check box is selected, you can determine the trend influence by using the Generate Demand and Inventory Plan (cpdsp1210m000) session. Related topics To compute the demand forecast
Tracking Signal for Demand Forecast | You can only select this check box if you selected Exponential Smoothing in the Forecast Method field. If this check box is selected, the smoothing factor for the demand must be linked to a tracking signal during a demand forecast calculation, according to the exponential smoothing method. The tracking signal is the ratio between the mean absolute forecast error and the mean forecast error. If the tracking signal exceeds the value of the Critical Tracking Signal field, ERP LN automatically adjusts the smoothing factor for the demand. Related topics To compute the demand forecast Forecast method: exponential smoothing