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Message type: E = Error
Message class: /SAPAPO/PFCS_MESS -
Message number: 061
Message text: Product/location &1/&2&3: Historical demand in DDF model is increasing
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/SAPAPO/PFCS_MESS061
- Product/location &1/&2&3: Historical demand in DDF model is increasing ?The SAP error message
/SAPAPO/PFCS_MESS061
indicates that there is an issue with the historical demand in the Demand Planning (DP) module of SAP Advanced Planning and Optimization (APO). Specifically, it suggests that the historical demand for a product at a specific location is increasing, which may not be expected or desired in the context of your planning model.Cause:
- Data Quality Issues: The historical demand data may contain anomalies, such as spikes or outliers, that are causing the demand to appear to be increasing.
- Model Configuration: The Demand Planning model may not be configured correctly, leading to incorrect calculations or interpretations of historical demand.
- Seasonality or Trends: There may be genuine seasonal trends or changes in consumer behavior that are causing an increase in demand.
- Data Entry Errors: Incorrect data entry or updates in the demand planning process can lead to inflated historical demand figures.
Solution:
- Review Historical Data: Analyze the historical demand data for the product/location combination to identify any anomalies or outliers. Use statistical methods to smooth out the data if necessary.
- Adjust Planning Parameters: If the increase in demand is not justified, consider adjusting the planning parameters or settings in the DDF (Demand Driven Forecasting) model to better reflect expected demand.
- Check Model Configuration: Ensure that the DDF model is configured correctly, including the selection of appropriate forecasting methods and parameters.
- Consult with Stakeholders: Engage with sales, marketing, and supply chain teams to understand any changes in market conditions or promotions that may be affecting demand.
- Use Forecasting Techniques: Implement advanced forecasting techniques that can account for seasonality, trends, and other factors that may influence demand.
- Data Cleansing: Perform data cleansing to remove any erroneous entries or correct any data quality issues that may be inflating historical demand.
Related Information:
By addressing the underlying causes and implementing the suggested solutions, you can resolve the error message and improve the accuracy of your demand planning processes.
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