What is non-cumulative value in SAP EC-EIS - Executive Information System?

SAP Term: non-cumulative value

• Component: EC-EIS

• Component Name: Executive Information System

• Description: A key figure that is measured in relation to points in time. Such key figures cannot normally be meaningfully summed over time. With non-cumulative values such as "number of employees", for example, it does not make sense to sum the number of employees over different periods, but rather to calculate an average over the periods. With share prices, the maximum, minimum and average within a period are of interest, not the sum. The aggregation behavior of the key figure shows how non-cumulative values should be summarized.

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• Key Concepts: 
  Non-cumulative value is a term used in the SAP Executive Information System (EC-EIS) to describe a type of data that is not cumulative. This means that the value of the data does not increase over time, but instead remains constant. For example, a non-cumulative value could be the number of orders placed in a given month, which would remain the same regardless of how many orders were placed in previous months. 
  
  How to use it: 
  Non-cumulative values can be used to measure performance over a specific period of time. For example, if you wanted to measure the number of orders placed in a given month, you could use a non-cumulative value to track this data. This would allow you to compare the performance of different months without having to take into account any previous months’ performance. 
  
  Tips & Tricks: 
  When using non-cumulative values, it is important to remember that they are not cumulative. This means that any changes in the value over time will not be reflected in the overall value. For example, if you wanted to track the number of orders placed in a given month, any changes in the number of orders placed in previous months would not be reflected in the overall value for that month. 
  
  Related Information: 
  Non-cumulative values are often used in conjunction with other types of data, such as cumulative values or averages. This allows for more comprehensive analysis and comparison of data over time. Additionally, non-cumulative values can be used to compare performance between different periods or locations.