Smart Discovery in SAC

Purpose of the article: To analyze KPI’s (Key Performance Indicators) and How each dimension plays a vital role in the Data set.

Intended Audience: Who has background knowledge of Planning.

Tools and Technology: SAP Analytics Cloud (SAC).

Keywords: Business Intelligence (BI), Version, Page Filters, Dimension, Measure, KPI, SAC Story.


  • One of the SAC (SAP Analytics Cloud) Story smart feature provided by SAP using Machine learning Algorithms.
  • This main motive is to give a clear picture of what type of Data set uses in the SAC Model.
  • This feature explores insights using Transactional Data and how each dimension and measure plays a vital role in the Data Set.

Here are the steps to follow and create a smart discovery story:

Step -1: Create a model and load the transactional data to the model and save it.

  • In this scenario, take the BI (Business intelligence) Content Sales Planning model to represent the Smart Discovery. For this SAP BI content Model, there is no need to map Transactional Data as all objects and Stories predefined by SAP.

Step -2: Create a Story and select the Smart Discovery option and select the model on which the smart discovery should Run on as shown below:

Step -3: This opens a Smart discovery Tab where need to select three factors that are highlighted in the Details Tab as shown below:

3.a. Discovery Settings:

This option needs to mention which Dimension or Measure the innovative discovery should run and analyze the information.

3.b. Version:

This is a much-needed advance option on which version the analysis should be done whether it is the Actual or Plan version. It predicts the graphs based on the version selected.

3.c. Page Filters:

Page filters are used in the story tab for user Convenient and reduce the data set analysis based on combinations; therefore, the performance of that Story increases.

Step -4: After clicking on Run Button and this gives three tabs of Smart Discovery results.

4.a. Overview of the Measure/Dimension Tab: This gives general information about dimension or measure and does the predictive analysis and Forecasting for next year how much value increased/decreased as shown below:

4.b. Key Influencer Tab:

The tab where the overall analysis will show where the deeper insights of the data set will be analyzed and show how each dimension is impacting the measure and what are top N values will show as below images:

4.c.  Simulation Tab: The tab used for changing our actual data and explore on how the results would impact the overall result, as shown below:

References / Sources of the information referred:

Referred Link:

Which MOURI Tech service, this article relates to- (please refer to website service section) –


This is a simple use case of how SAP Analytics Cloud provides predictive & forecasting results in few clicks by running its AI Algorithms.

Kanthimahanti Venkata Tejaswi
Associate Software Engineer, Analytics-EPM.

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