What is aggregation in SAP SCM-IBP - Integrated Business Planning?

SAP Term: aggregation

• Component: SCM-IBP

• Component Name: Integrated Business Planning

• Description: A function by which key figure values on the lowest level of detail undergo specific calculations and are displayed at a higher level. Types of aggregation in IBP are sum, average, minimum, and maximum calculations. For example, you define a key figure on the planning level representing the lowest level of detail base planning level, which has the attributes period and location. You also define another planning level containing the attributes period and region. The system can then aggregate values of the key figure along the attribute of location, for example, to the level of region.

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• Key Concepts: 
  Aggregation is a process in SAP SCM-IBP Integrated Business Planning (IBP) that combines multiple data points into a single value. This allows for more efficient analysis and decision-making. Aggregation can be used to calculate the total demand for a product, the total cost of a project, or the total sales of a region.
  
  How to use it: 
  In SAP SCM-IBP, aggregation is used to combine multiple data points into a single value. This can be done by selecting the desired data points and then selecting the “aggregate” option. This will then calculate the total value of the selected data points.
  
  Tips & Tricks: 
  When using aggregation in SAP SCM-IBP, it is important to ensure that all of the data points being aggregated are related to each other. This will ensure that the resulting value is accurate and meaningful. Additionally, it is important to consider how the aggregation will affect other calculations and decisions that are based on the aggregated value.
  
  Related Information: 
  Aggregation is closely related to other processes such as forecasting and optimization. Forecasting uses historical data to predict future trends, while optimization uses mathematical algorithms to determine the best course of action for a given situation. Both of these processes rely on accurate aggregation in order to produce meaningful results.