What is distribution curve in SAP CA-DDF-RT - Demand Data Foundation for Retail?

SAP Term: distribution curve

• Component: CA-DDF-RT

• Component Name: Demand Data Foundation for Retail

• Description: The expected proportional distribution of sales in a multidimensional matrix along all possible color and size combinations of a specific product in a specific location. Distribution curves are calculated by analyzing the historical sales data of the following: one specific product or all products of a specific product hierarchy node and one specific location or group of locations and, optionally, up to two product attributes such as, fashion grade or brand. For example, the results of the distribution curve analysis can be used to support the manual or automatic allocation of products to locations.

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• Key Concepts: 
  A distribution curve is a graphical representation of the probability of a certain event occurring. In the context of SAP's CA-DDF-RT Demand Data Foundation for Retail, it is used to represent the probability of a certain demand being fulfilled. It is used to help retailers make decisions about how to allocate resources and plan for future demand. 
  
  How to use it: 
  The distribution curve can be used to identify trends in demand and forecast future demand. It can also be used to identify areas where resources should be allocated in order to meet customer demand. The curve can be used to identify areas where there is a high probability of demand being fulfilled and areas where there is a low probability of demand being fulfilled. 
  
  Tips & Tricks: 
  When using the distribution curve, it is important to consider the data that is being used to create the curve. The data should be accurate and up-to-date in order to ensure that the curve is an accurate representation of the current demand. Additionally, it is important to consider any external factors that may affect the demand, such as seasonality or changes in customer preferences. 
  
  Related Information: 
  The distribution curve can be used in conjunction with other tools, such as predictive analytics, in order to gain a better understanding of customer demand and make more informed decisions about resource allocation. Additionally, it can be used in conjunction with other SAP components, such as CA-DDF-RT Demand Data Foundation for Retail, in order to gain a better understanding of customer demand and make more informed decisions about resource allocation.