How To Fix /SAPAPO/AMON_LIST414 - MLR using POS: Calculated MAPE greater than statistical forecast MAPE


/SAPAPO/AMON_LIST414 - Overview

  • Message type: E = Error

  • Message class: /SAPAPO/AMON_LIST -

  • Message number: 414

  • Message text: MLR using POS: Calculated MAPE greater than statistical forecast MAPE

  • Show details Hide details


  • 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.



    What else can you do?

    First, use our AnswerBot below to get a possible cause and solution (requires a premium subscription).

    Also, review the in-depth Common Questions & Answers listed below; you could discover a solution there or be able to connect with others who have faced similar challenges.

    You can also try searching the SAP support portal (support.sap.com) but you need a special user ID to access it. It is possible that an SAP support note exists that provides additional details about the mistake or even steps for fixing it.


Smart SAP Assistant

  • What is the cause and solution for SAP error message /SAPAPO/AMON_LIST414 - MLR using POS: Calculated MAPE greater than statistical forecast MAPE ?
    The SAP error message /SAPAPO/AMON_LIST414 MLR indicates that there is an issue with the calculated Mean Absolute Percentage Error (MAPE) for a forecast generated using the Multi-Level Regression (MLR) method in SAP Advanced Planning and Optimization (APO). Specifically, it states that the calculated MAPE is greater than the statistical forecast MAPE, which is not expected behavior.
    
    Cause: Data Quality Issues: Poor quality or insufficient historical data can lead to inaccurate forecasts. If the data used for regression analysis is not representative or has outliers, it can skew the results. Model Specification: The MLR model may not be correctly specified. This could include missing important variables, incorrect functional forms, or multicollinearity among predictors. Seasonality and Trends: If the data has strong seasonal patterns or trends that are not accounted for in the MLR model, it can lead to poor forecasting performance. Overfitting: The model may be overfitted to the historical data, capturing noise rather than the

    Already have an account? Login here!




Instant HelpGet instant SAP help. Sign up for our Free Essentials Plan.


Related SAP Error Messages

Click the links below to see the following related messages:

Click on this link to search all SAP messages.


Rating
ERPlingo's SAP support assistant is amazing. Saves me countless hours trying to solve complex SAP issues myself. It's a real game changer!
Rate 1
Thomas Michael
SAP Consultant, Author & Speaker