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 both item forecasting and demand planning in S&OP.
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 is enabled, the outlier may be applied to demand planning and may also be used to remove spikes for safety stock calculations.
Sigma Threshold: Sets the number of standard deviations for DemandCaster to identify an outlier.
Recent Period Weight (in months): Used as part of the aggregation calculation. The distribution of the aggregate forecast is weighted by the periods selected. We recommend 6 months because the distribution will be weighted in favor of items that have the most activity in the last 6 months.
Bucket Size Selection: The default historical period aggregation basis for forecasting when S&OP is not enabled. 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)
Forecast Source: The options are Approved Demand Plan (S&OP) or Requirement Plan Override
- Statistical: Applicable when S&OP add-on is not enabled. Statistical is a forecast derived by DemandCaster as a best fit or user specified statistical model against the items history. The user may adjust the settings to apply different statistical models against the history.
- Approved Demand Plan (S&OP): Applicable when S&OP add-on is enabled. The defaulted forecast for requirement planning comes from the approved demand plan.
- Requirement Plan Override: The forecast source is a user defined forecast that is uploaded directly to the DemandCaster requirement plan via a tab delimited text file or via automation though the data hub. The forecast overrides a statistical forecast or demand plan. in favor or the uploaded requirement plan forecast.
Include Returns and Credits in History: Enables the option to include return and credits in history for forecasting purposes. Some users choose to exclude since the forecast may be understated if the volume of returns is high.
Re-Forecast Frequency (in months): This ensures there is a forecast values for a particular period of time during requirement planning if a new forecast is not generated at least once a month. The next time you run a requirement plan the forecast generation time frame is calculated as a sum of the longest lead time of all items within a BOM plus the re-forecast frequency value. For example, if new forecasts are generated quarterly, the value entered would be 3. In turn, if the longest lead time is 3 months and the frequency is 3 months the generated forecast time-frame will be for 6 months.
Forecast History Length (months): The number of months of history to use for forecasting as a default. Applies to both item forecasting and demand planning forecasting. Default is 48 months for demand planning.
Seasons per year: Defining the seasons per year helps the forecast engine select the correct algorithm to account for seasons.