How To Fix /SAPAPO/AMON_ALERTS442 - MLR: Shortfall below adjusted R**2 lower limit

SAP Error Message - Details

• Message type: E = Error

• Message class: /SAPAPO/AMON_ALERTS -

• Message number: 442

• Message text: MLR: Shortfall below adjusted R**2 lower limit

Self-Explanatory Message

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• What is the cause and solution for SAP error message /SAPAPO/AMON_ALERTS442 - MLR: Shortfall below adjusted R**2 lower limit ?

  The SAP error message /SAPAPO/AMON_ALERTS442 MLR: Shortfall below adjusted R**2 lower limit is related to the Multi-Level Regression (MLR) analysis in SAP Advanced Planning and Optimization (APO). This error indicates that the adjusted R-squared value of the regression model is below an acceptable threshold, which suggests that the model does not explain the variability of the data well enough.
  Cause:
  
  
  Poor Model Fit: The regression model may not be capturing the underlying patterns in the data effectively. This can happen due to:
  
  Inadequate selection of independent variables.
  Non-linearity in the relationship between dependent and independent variables.
  Presence of outliers or influential data points that skew the results.
  
  
  
  Insufficient Data: There may not be enough historical data points to create a reliable model, leading to a low adjusted R-squared value.
  
  
  Data Quality Issues: Missing values, incorrect data types, or inconsistencies in the dataset can adversely affect the regression analysis.
  
  
  Overfitting or Underfitting: The model may be too complex (overfitting) or too simple (underfitting), which can lead to poor predictive performance.
  
  
  Solution:
  
  
  Review Model Variables: Check the selection of independent variables used in the regression model. Ensure that they are relevant and have a logical relationship with the dependent variable.
  
  
  Data Quality Check: Clean the dataset by addressing missing values, correcting data types, and removing outliers or influential points that may distort the analysis.
  
  
  Increase Data Volume: If possible, gather more historical data to improve the robustness of the model.
  
  
  Model Re-evaluation: Consider using different modeling techniques or transformations (e.g., polynomial regression, logarithmic transformations) to better capture the relationships in the data.
  
  
  Consult Documentation: Review SAP documentation or guidelines on regression analysis to ensure that best practices are being followed.
  
  
  Adjust Thresholds: If the business context allows, consider adjusting the acceptable limits for the adjusted R-squared value, but this should be done with caution and a clear understanding of the implications.
  
  
  Related Information:
  
  Adjusted R-squared: This statistic provides an indication of how well the independent variables explain the variability of the dependent variable, adjusted for the number of predictors in the model. A higher value indicates a better fit.
  SAP APO: Advanced Planning and Optimization is a component of SAP that helps organizations with supply chain planning and optimization.
  Regression Analysis: A statistical method used to model the relationship between a dependent variable and one or more independent variables.
  
  If the issue persists after trying the above solutions, it may be beneficial to consult with an SAP expert or support team for further assistance.