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


/SAPAPO/PR446 - Overview

  • Message type: E = Error

  • Message class: /SAPAPO/PR -

  • Message number: 446

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

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  • Self-Explanatory Message

    Since SAP believes that this specific error message is 'self-explanatory,' no more information has been given.The majority of messages in the SAP system have a message text, however this is frequently insufficient to comprehend or resolve the problem.

    To make things easier, more detailed information is frequently added to describe the issue, how to fix it, and the necessary steps or configuration modifications.

    Unfortunately, there isn't any extra information in this error notice.



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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:

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