How To Fix /SAPAPO/PR446 - Outlier correction performed; &1 outlier(s) corrected

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/PR -

• Message number: 446

• Message text: Outlier correction performed; &1 outlier(s) corrected

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/PR446 - Outlier correction performed; &1 outlier(s) corrected ?

  The SAP error message /SAPAPO/PR446 Outlier correction performed; &1 outlier(s) corrected is related to the SAP Advanced Planning and Optimization (APO) module, specifically in the context of demand planning or forecasting. This message indicates that the system has detected outliers in the data and has performed a correction on them.
  Cause:
  Outliers in forecasting data can occur due to various reasons, such as:
  
  Data entry errors (e.g., incorrect sales figures).
  Unusual events (e.g., promotions, stockouts, or market changes) that significantly affect demand.
  Seasonal fluctuations that are not accounted for in the forecasting model.
  
  The system identifies these outliers based on predefined criteria and thresholds. When it detects outliers, it automatically corrects them to ensure that the forecasting model remains accurate and reliable.
  Solution:
  
  
  Review the Outlier Correction Settings: Check the settings in the forecasting profile to understand how outliers are defined and corrected. You may want to adjust the thresholds or criteria used for identifying outliers.
  
  
  Analyze the Data: Investigate the data that was flagged as outliers. Look for patterns or reasons behind the outliers. This may involve checking historical data, promotional activities, or any other factors that could have influenced demand.
  
  
  Manual Adjustments: If the automatic correction does not align with your expectations or business knowledge, consider manually adjusting the outlier values or the forecast.
  
  
  Training and Calibration: If outliers are frequently being corrected, it may indicate that the forecasting model needs to be recalibrated or that additional training data is required to improve its accuracy.
  
  
  Consult Documentation: Refer to SAP documentation or help resources for more detailed information on how outlier detection and correction works in your specific version of SAP APO.
  
  
  Engage with SAP Support: If the issue persists or if you need further assistance, consider reaching out to SAP support for guidance tailored to your specific situation.
  
  
  Related Information:
  
  Forecasting Profiles: Understand how to configure forecasting profiles in SAP APO to better manage outlier detection.
  Data Quality: Ensure that the data being fed into the forecasting model is clean and accurate to minimize the occurrence of outliers.
  User Exits and Enhancements: Explore the possibility of implementing user exits or enhancements to customize how outliers are handled in your specific business context.
  
  By addressing the underlying causes of outliers and refining your forecasting processes, you can improve the accuracy of your demand planning efforts in SAP APO.