How To Fix /SAPAPO/AMON_LIST413 - MLR using POS: MAPE upper limit exceeded

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_LIST -

• Message number: 413

• Message text: MLR using POS: MAPE upper limit exceeded

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/AMON_LIST413 - MLR using POS: MAPE upper limit exceeded ?

  The SAP error message /SAPAPO/AMON_LIST413 MLR using POS: MAPE upper limit exceeded typically occurs in the context of Advanced Planning and Optimization (APO) when the Mean Absolute Percentage Error (MAPE) for a particular planning object structure (POS) exceeds the defined upper limit. This can indicate that the forecast accuracy is not meeting the expected standards, which can lead to issues in supply chain planning and inventory management.
  Cause:
  
  
  Forecasting Issues: The underlying cause is often related to poor forecasting accuracy. This can be due to:
  
  Inaccurate historical data.
  Seasonal fluctuations not being accounted for.
  Changes in market conditions or demand patterns that were not anticipated.
  Inadequate statistical models being used for forecasting.
  
  
  
  Configuration Settings: The upper limit for MAPE may be set too low for the specific characteristics of the data being analyzed.
  
  
  Data Quality: Issues with data quality, such as missing values or outliers, can also lead to inaccurate forecasts and high MAPE values.
  
  
  Solution:
  
  
  Review and Adjust Forecasting Models:
  
  Analyze the forecasting models being used and consider switching to a more appropriate model that can better capture the demand patterns.
  Use advanced statistical techniques or machine learning models if necessary.
  
  
  
  Data Quality Improvement:
  
  Ensure that the historical data used for forecasting is clean, complete, and accurate.
  Address any outliers or anomalies in the data that could skew the results.
  
  
  
  Adjust MAPE Upper Limit:
  
  If the current upper limit for MAPE is too stringent for the specific context, consider adjusting it to a more realistic value based on historical performance and business requirements.
  
  
  
  Monitor and Analyze Forecast Performance:
  
  Regularly monitor the performance of forecasts and analyze the reasons for deviations.
  Implement a feedback loop to continuously improve forecasting accuracy.
  
  
  
  Collaboration with Stakeholders:
  
  Engage with sales, marketing, and other relevant departments to gather insights on market trends and customer behavior that may affect demand.
  
  
  
  Related Information:
  
  MAPE Definition: MAPE is a measure of forecast accuracy that expresses the accuracy as a percentage. It is calculated as the average of the absolute percentage errors of forecasts.
  SAP APO: Advanced Planning and Optimization is a component of SAP that helps organizations optimize their supply chain processes.
  Transaction Codes: Familiarize yourself with relevant transaction codes in SAP APO for monitoring and adjusting forecasting settings, such as /SAPAPO/AMON for analysis and monitoring.
  
  By addressing the underlying causes and implementing the suggested solutions, you can mitigate the occurrence of this error and improve the overall forecasting accuracy in your SAP APO environment.