What is mean error variance in SAP CA-DDF-RT - Demand Data Foundation for Retail?

SAP Term: mean error variance

• Component: CA-DDF-RT

• Component Name: Demand Data Foundation for Retail

• Description: Average of the squared observed differences between the historical sales and modeled sales. For example, the mean error variance might be determined across the entire forecast horizon of a specific product in a specific location. In this case, the value is the same for each day of the forecast horizon.

Smart SAP Assistant

• Key Concepts: 
  Mean Error Variance (MEV) is a measure of the accuracy of a forecast in SAP's Demand Data Foundation for Retail (CA-DDF-RT). MEV is calculated by taking the average of the squared differences between the actual and forecasted values. The lower the MEV, the more accurate the forecast. 
  
  How to use it: 
  MEV can be used to compare different forecasting models and determine which one is most accurate. It can also be used to identify trends in demand and adjust forecasts accordingly. Additionally, MEV can be used to identify potential problems with data or processes that may be causing inaccurate forecasts. 
  
  Tips & Tricks: 
  When using MEV, it is important to remember that it is only a measure of accuracy and not a measure of performance. Additionally, it is important to consider other factors such as seasonality and trends when evaluating forecasts. 
  
  Related Information: 
  For more information on MEV and other forecasting metrics, please refer to SAP's Demand Data Foundation for Retail documentation. Additionally, there are many online resources available that provide further information on forecasting metrics and techniques.