How To Fix /SAPAPO/TSM118 - MAPE: &1 MSE: &2 RMSE: &3 MPE: &4

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/TSM -

• Message number: 118

• Message text: MAPE: &1 MSE: &2 RMSE: &3 MPE: &4

Self-Explanatory Message

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Smart SAP Assistant

• What is the cause and solution for SAP error message /SAPAPO/TSM118 - MAPE: &1 MSE: &2 RMSE: &3 MPE: &4 ?

  The SAP error message /SAPAPO/TSM118 is related to the Advanced Planning and Optimization (APO) module in SAP, specifically in the context of the Time Series Management (TSM) functionality. This error message typically indicates issues with the statistical forecast model used in the planning process.
  Cause:
  The error message provides four metrics:
  
  MAPE (Mean Absolute Percentage Error): A measure of prediction accuracy.
  MSE (Mean Squared Error): A measure of the average of the squares of the errors.
  RMSE (Root Mean Squared Error): The square root of the MSE, providing a measure of how spread out the errors are.
  MPE (Mean Percentage Error): A measure of the average of the percentage errors.
  
  The error message indicates that the statistical forecast model has produced results that are not acceptable based on the defined thresholds for these metrics. This could be due to:
  
  Poor historical data quality.
  Inappropriate forecasting model selection.
  Seasonal patterns not being captured correctly.
  Insufficient data for the model to generate reliable forecasts.
  
  Solution:
  To resolve this error, consider the following steps:
  
  
  Review Historical Data: Check the quality and completeness of the historical data used for forecasting. Ensure there are no missing values or outliers that could skew the results.
  
  
  Adjust Forecasting Model: Evaluate the forecasting model being used. If the current model is not suitable for the data characteristics (e.g., seasonality, trends), consider switching to a different model that better fits the data.
  
  
  Parameter Tuning: If applicable, adjust the parameters of the forecasting model to improve accuracy. This may involve changing settings related to seasonality, trend adjustments, or other model-specific parameters.
  
  
  Data Volume: Ensure that there is enough historical data for the model to generate reliable forecasts. If the dataset is too small, consider aggregating data over a longer period or including additional relevant data.
  
  
  Threshold Settings: Review the thresholds set for MAPE, MSE, RMSE, and MPE. If they are too strict for the specific context, consider adjusting them to more realistic levels based on historical performance.
  
  
  Consult Documentation: Refer to SAP documentation or help resources for specific guidance on the statistical forecasting models and their configurations.
  
  
  Testing: After making adjustments, run the forecasting process again to see if the error persists. Monitor the output metrics to ensure they fall within acceptable ranges.
  
  
  Related Information:
  
  SAP Notes: Check for any relevant SAP Notes that may address known issues or provide additional guidance on this error message.
  SAP Community: Engage with the SAP Community forums to see if other users have encountered similar issues and what solutions they have found.
  Training and Documentation: Consider additional training on SAP APO and statistical forecasting to better understand the tools and techniques available for improving forecast accuracy.
  
  By following these steps, you should be able to identify the root cause of the error and implement a solution to resolve it.