How To Fix /SAPAPO/AMON_LIST071 - MLR: Durbin Watson lower limit not reached by &UNI_PERCENT %

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_LIST -

• Message number: 071

• Message text: MLR: Durbin Watson lower limit not reached 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_LIST071 - MLR: Durbin Watson lower limit not reached by &UNI_PERCENT % ?

  The SAP error message /SAPAPO/AMON_LIST071 MLR: Durbin Watson lower limit not reached by &UNI_PERCENT % is related to the statistical analysis performed in the context of the SAP Advanced Planning and Optimization (APO) module, specifically in the area of demand planning and forecasting.
  Cause:
  The Durbin-Watson statistic is a test for autocorrelation in the residuals from a regression analysis. In the context of SAP APO, this error indicates that the autocorrelation of the residuals from a regression model is too high, which suggests that the model may not be adequately capturing the underlying data patterns. The message indicates that the lower limit for the Durbin-Watson statistic has not been reached by a specified percentage, which means that the model's fit is not satisfactory.
  Solution:
  To address this error, consider the following steps:
  
  
  Review the Model: Check the regression model being used. Ensure that the variables included in the model are appropriate and relevant to the data being analyzed.
  
  
  Data Quality: Examine the input data for any anomalies, outliers, or missing values that could affect the regression analysis. Clean the data as necessary.
  
  
  Adjust Forecasting Parameters: Modify the parameters used in the forecasting model. This may include changing the time series settings, adjusting seasonal factors, or using different forecasting methods.
  
  
  Increase Data Volume: If possible, increase the amount of historical data used for the analysis. More data can help improve the model's accuracy and reduce autocorrelation.
  
  
  Use Different Forecasting Techniques: If the current model is not performing well, consider using alternative forecasting techniques or algorithms that may better capture the data patterns.
  
  
  Consult Documentation: Refer to SAP documentation or help resources for specific guidelines on improving model performance and understanding the Durbin-Watson statistic.
  
  
  Seek Expert Help: If the issue persists, consider consulting with a data analyst or an SAP APO expert who can provide insights and recommendations based on the specific context of your data and forecasting needs.
  
  
  Related Information:
  
  Durbin-Watson Statistic: A value between 0 and 4, where a value around 2 indicates no autocorrelation. Values below 1 or above 3 indicate positive or negative autocorrelation, respectively.
  Regression Analysis: A statistical method used to model the relationship between a dependent variable and one or more independent variables.
  SAP APO: A component of SAP's supply chain management suite that focuses on advanced planning and optimization.
  
  By following these steps, you should be able to address the error and improve the performance of your forecasting model in SAP APO.