How To Fix /SAPAPO/AMON_LIST067 - Upper RMSE limit exceeded by &UNI_PERCENT %

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_LIST -

• Message number: 067

• Message text: Upper RMSE limit exceeded by &UNI_PERCENT %

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/AMON_LIST067 - Upper RMSE limit exceeded by &UNI_PERCENT % ?

  The SAP error message /SAPAPO/AMON_LIST067 Upper RMSE limit exceeded by &UNI_PERCENT % is related to the Advanced Planning and Optimization (APO) module in SAP, specifically in the context of demand planning or forecasting. This error indicates that the Root Mean Square Error (RMSE) of the forecast exceeds a predefined upper limit by a certain percentage (&UNI_PERCENT).
  Cause:
  
  Forecasting Model Issues: The forecasting model being used may not be suitable for the data, leading to poor predictions.
  Data Quality: There may be issues with the historical data used for forecasting, such as missing values, outliers, or incorrect data entries.
  Parameter Settings: The parameters set for the forecasting process may not be optimal, leading to excessive error in the forecasts.
  Seasonality or Trends: If the data has strong seasonal patterns or trends that are not being captured correctly by the forecasting model, it can lead to high RMSE values.
  
  Solution:
  
  Review Forecasting Models: Analyze the forecasting models being used and consider switching to a different model that may better fit the data characteristics.
  Data Cleansing: Ensure that the historical data is clean and free from errors. Address any missing values or outliers that could skew the results.
  Adjust Parameters: Review and adjust the parameters used in the forecasting process. This may involve changing the RMSE limits or other settings in the forecasting profile.
  Analyze Trends and Seasonality: If applicable, ensure that the model accounts for any trends or seasonal patterns in the data. You may need to use seasonal decomposition techniques or other methods to capture these effects.
  Run Diagnostics: Use the diagnostic tools available in SAP APO to analyze the forecast performance and identify specific areas for improvement.
  
  Related Information:
  
  RMSE Definition: RMSE is a measure of the differences between predicted values and observed values. A lower RMSE indicates a better fit of the model to the data.
  Forecasting Profiles: In SAP APO, forecasting profiles can be configured to set various parameters, including RMSE limits. Review these settings to ensure they align with your business requirements.
  SAP Notes and Documentation: Check SAP Notes for any known issues or updates related to this error message. SAP's official documentation may also provide insights into best practices for forecasting in APO.
  
  By addressing the underlying causes and implementing the suggested solutions, you should be able to resolve the error and improve the accuracy of your forecasts in SAP APO.