What is outlier in SAP SCM-APO-FCS - Demand Planning?

SAP Term: outlier

• Component: SCM-APO-FCS

• Component Name: Demand Planning

• Description: An outlier is a value in the historical data that lies outside the expected range of values. There can a variety of reasons for this, for example, an error in data entry or a freak result. Such data points should not be taken into account when producing a forecast.

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• Key Concepts: 
  Outlier is a term used in SAP SCM-APO-FCS Demand Planning to describe an observation that is significantly different from the other observations in a dataset. Outliers can be caused by errors in data entry, or they can be legitimate observations that are simply far away from the rest of the data. 
  
  How to use it: 
  Outliers can be identified by looking at the data and seeing if there are any points that are significantly different from the rest. In SAP SCM-APO-FCS Demand Planning, outliers can be identified by using statistical methods such as box plots or scatter plots. Once identified, outliers can be removed from the dataset or treated differently in order to get more accurate results. 
  
  Tips & Tricks: 
  When dealing with outliers, it is important to consider the context of the data and determine if the outlier is a legitimate observation or an error. If it is an error, it should be removed from the dataset. If it is a legitimate observation, it should be treated differently in order to get more accurate results. 
  
  Related Information: 
  Outliers can also be identified using other methods such as standard deviation or z-scores. Additionally, there are various techniques for dealing with outliers such as trimming, winsorizing, and capping. For more information on these techniques, please refer to the SAP SCM-APO-FCS Demand Planning documentation.