How To Fix /SAPAPO/AMON_LIST072 - MLR: Durbin Watson upper limit exceeded by &UNI_PERCENT %

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_LIST -

• Message number: 072

• Message text: MLR: Durbin Watson upper 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_LIST072 - MLR: Durbin Watson upper limit exceeded by &UNI_PERCENT % ?

  The SAP error message /SAPAPO/AMON_LIST072 MLR: Durbin Watson upper limit exceeded by &UNI_PERCENT % is related to the statistical analysis performed during the Multi-Level Regression (MLR) process in SAP Advanced Planning and Optimization (APO). This error indicates that the Durbin-Watson statistic, which tests for the presence of autocorrelation in the residuals from a regression analysis, has exceeded the acceptable upper limit.
  Cause:
  
  Autocorrelation: The primary cause of this error is the presence of autocorrelation in the residuals of the regression model. Autocorrelation occurs when the residuals (errors) from the regression model are correlated with each other, which violates the assumption of independence in regression analysis.
  Model Specification: The model may be incorrectly specified, meaning that important variables are omitted, or the functional form of the model is not appropriate.
  Data Issues: There may be issues with the data itself, such as outliers, non-stationarity, or trends that have not been accounted for.
  
  Solution:
  
  Check Residuals: Analyze the residuals of your regression model to identify patterns or correlations. You can plot the residuals to visually inspect for autocorrelation.
  Model Adjustment: Consider adjusting your regression model. This may involve:
  
  Adding lagged variables to account for autocorrelation.
  Including additional independent variables that may explain the variance in the dependent variable.
  Transforming the data (e.g., differencing) to remove trends or seasonality.
  
  
  Use Alternative Models: If autocorrelation persists, consider using time series models (like ARIMA) that are designed to handle autocorrelation.
  Review Data Quality: Ensure that the data used for the regression analysis is clean and free from outliers or anomalies that could affect the results.
  Consult Documentation: Refer to SAP documentation or support for specific guidelines on handling this error in the context of your APO implementation.
  
  Related Information:
  
  Durbin-Watson Statistic: The Durbin-Watson statistic ranges from 0 to 4, where a value around 2 indicates no autocorrelation. Values below 1 or above 3 suggest positive or negative autocorrelation, respectively.
  Statistical Analysis in SAP APO: Understanding the statistical methods used in SAP APO can help in diagnosing and resolving issues related to forecasting and planning.
  SAP Notes and Community: Check SAP Notes for any known issues or patches related to this error, and consider reaching out to the SAP Community for insights from other users who may have encountered similar issues.
  
  By addressing the underlying causes of the autocorrelation and adjusting your model accordingly, you should be able to resolve the error and improve the performance of your regression analysis in SAP APO.