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Component: EPM-BPC
Component Name: Business Planning and Consolidation
Description: In Insight you can perform KPI on-demand predictions by setting up algorithms. When the predicted values are unfavorable compared to the budgeted values, the Predictor icon is displayed next to the corresponding KPI. When you click the icon, the Predictor window is displayed.
Key Concepts: Predictor is a component of SAP EPM-BPC Business Planning and Consolidation (BPC) that enables users to create predictive models for forecasting future trends. It uses historical data to generate forecasts and provides users with the ability to adjust the model parameters to get more accurate results. The predictor also allows users to compare different scenarios and make decisions based on the results. How to use it: To use the predictor, users must first select the data they want to use for forecasting. This can be done by selecting a range of dates, selecting specific data points, or using a combination of both. Once the data is selected, users can then create a predictive model by adjusting the parameters such as the number of periods, the type of model, and the confidence level. After the model is created, users can then run simulations to see how different scenarios will affect the forecast. Tips & Tricks: When creating a predictive model, it is important to consider the accuracy of the data being used. If there are any outliers or missing values in the data set, these should be addressed before running simulations. Additionally, it is important to consider how different parameters will affect the results of the simulation. For example, increasing the number of periods in a simulation may result in more accurate forecasts but may also increase processing time. Related Information: For more information on SAP EPM-BPC Business Planning and Consolidation (BPC), please visit https://www.sap.com/products/business-planning-consolidation.html. Additionally, for more information on predictive modeling and forecasting, please visit https://en.wikipedia.org/wiki/Predictive_modeling.