Forecast History Type: Select either the customer order ship date or original order due date (Actual) as the basis for history used for forecasting. Applied in Item Forecasting, S&OP, and Advanced Planning.
Auto Remove Outliers: The number of iterations specifies how many times the system will attempt to smooth history. The more iterations the smoother the history and the lower the standard deviation becomes. If the use of this feature is desired, we do not recommend more than two iterations. Setting the value to 0 disables the outlier setting. If S&OP or Advanced Planning is enabled, the outlier may be applied to demand planning and will also be used to remove spikes for safety stock calculations. With Item Forecasting (No S&OP or Advanced Planning) the outliers are used for both the item forecast and safety stock settings.
Sigma Threshold: Sets the number of standard deviations for DemandCaster to identify an outlier.
Forecast History Length (months): The number of months of history to use for forecasting as a default. Default is 48 months for demand planning. The Advanced Planning app has an additional functionality that automatically sets the proper history length by removing leading 0's for forecasting.
Ignore last N buckets: Provides the capability to ignore a set number of the most recent forecasting buckets. This is at times necessary when the most recent sales data is not available when running a new forecast. By ignoring the last period, for example, your forecast will not be influenced by a very low demand period. At present this option is an all or nothing setting meaning it is applied to all forecasts.
ADI Threshold: The threshold set to establish the historical demand profile based on the measure of frequency of demand. To learn more read the article Forecast Structure.
CoV Threshold: The threshold set to establish the historical demand profile based on the measure of volatility of demand. To learn more read the article Forecast Structure.
Force Average forecast algorithm when history length equal or less than: This global system setting enables the user to force the use of the Average forecast algorithm when the number of periods of history (the period is tied to the forecast bucket type) is less than or equal to the specified number. For example, if the number of periods is 3, then the average algorithm is used when there are only 3 or fewer recent periods of history.
Force Zero forecast algorithm if last period of demand is older than: This setting is used to specify the number of periods with zero demand in the immediate past that will trigger the application of a zero forecast to a context. For example, if a value of 6 is entered, if there is no demand over the last 6 months or 6 weeks (depending on the forecast buckets applied), the forecast for that context will be 0.
Legacy S&OP Specific System Forecast Settings
The following measure is unique to the legacy S&OP application. Those measure covered above but not visible below are not applicable.
Recent Period Weight (in months): Used as part of the disaggregation calculation. The distribution of the aggregate forecast is weighted by the percentage contribution as calculated over the number periods selected. Applicable only when S&OP is enabled.
Item Forecasting Specific System Forecast Settings
The following measures are unique to Item Forecasting when S&OP and Advanced Planning are not enabled. Those measure covered above but not visible below are not applicable.
Bucket Size Selection: Applicable to Item Forecasting. The default historical period aggregation basis for item based forecasting. The options are weeks or months.
- Weekly Buckets Logic: The historical buckets are all weeks and conform to the following rules. Nevertheless which day of the week the forecast is generated, the data series start date is the Sunday (1st day of the week) of that week. A starting zeros check is performed. In case there are one or more weeks with zeros (no invoices) in the beginning of the history data period, then these weeks are removed and the first week which has invoices becomes the first week of the history data period. The end date is chosen to be the Saturday of the last week (the week before the current week when the forecast is generated)
- Monthly Buckets Logic: The historical buckets are all calendar months and conform to the following rules. Nevertheless which day of the week the forecast is generated, the data series start date is the 1st day of each month. A month is defined by the type of calendar selected in system settings: calendar, 4-4-5, or 5-4-4. Starting zeros check is performed. In case there are one or more months with zeros (no invoices) in the beginning of the History data period then these months are removed and the first month which has invoices becomes the first month of the forecast history basis. The end date is chosen to be the last day of the last month (the month before the current month when the demand analysis is generated)
Re-forecast frequency (in months): Sets how often new forecasts are generated to ensure the forecast time frame is long enough to cover cumulative lead team.
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