How to use /SAPAPO/SPPNEWFCST - SPP Forecast for New Products

SAP Transaction Code - Details

• Transaction Code: /SAPAPO/SPPNEWFCST

  Description: SPP Forecast for New Products

  Release: S/4HANA only

  Menu Path:

  • Logistics > Extended Service Parts Planning > Planning > Forecasting > Phase-In Forecasting

• • Program:

    Screen: 0

    Authorization Object:

  • Development Package: /SAPAPO/PUIA_FORECASTING

    Package Description: UI: Forecast

    Parent Package: /SAPAPO/PUIA

  • Module/Component: SCM-APO-SPP-SFC

    Description: Service Parts Forecast

Smart SAP Assistant

• SAP Tcode: /SAPAPO/SPPNEWFCST - SPP Forecast for New Products

  
  Overview: 
  The SAP transaction code /SAPAPO/SPPNEWFCST is used to create a statistical forecast for new products in the SAP Advanced Planning and Optimization (SAP APO) system. This transaction code is part of the Supply Chain Planning (SCP) module of SAP APO. 
  
  Functionality: 
  This transaction code allows users to create a statistical forecast for new products in the SAP APO system. The forecast is based on historical data and can be used to plan for future demand. The forecast can be used to plan production, inventory, and other supply chain activities. 
  
  Step-by-step How to Use: 
  1. Enter the transaction code /SAPAPO/SPPNEWFCST into the command field. 
  2. Select the product for which you want to create a forecast. 
  3. Enter the start date and end date of the forecast period. 
  4. Select the forecasting method you want to use (e.g., exponential smoothing). 
  5. Enter any additional parameters needed for the forecasting method (e.g., smoothing constants). 
  6. Click “Execute” to generate the forecast. 
  7. Review the results of the forecast and make any necessary adjustments. 
  8. Click “Save” to save the forecast in SAP APO. 
  
  Other Recommendations: 
  It is recommended that users review their forecasts regularly to ensure accuracy and adjust them as needed based on changing market conditions or other factors that may affect demand for a product. Additionally, users should consider using other forecasting methods in addition to statistical forecasting, such as causal forecasting, which takes into account external factors that may affect demand for a product.