Planning Capabilities of SAP Analytics Cloud

Planning Capabilities of SAP Analytics cloud

Purpose of the article: This Article explains about Planning capabilities of SAP Analytics Cloud.

Intended Audience: who has background knowledge of Planning.

Tools and Technology: SAP Analytics cloud.

Keywords: Planning, Forecasting, Modelling, Version, Predictive Analysis, KPI, Allocation, Simulation, Data.


A new cloud-based planning tool is being developed by SAP. SAP Analytics Cloud Platform improves the organization’s planning, budgeting, and forecasting capabilities. The tool is ground-based and can be embedded with other SAP applications, including SAP S/4 HANA, BW, Performance Factors, and several others beyond SAP.

SAP Analytics Cloud focuses on three main components: data, modeling, and storytelling. Learning these main elements should help you access the SAP Analytics Cloud and make the most of the system.

Why SAP Analytics Cloud?

SAP Analytics Platform allows data analysts and business decision-makers in a single, cloud-based environment to analyze, prepare and make predictions. SAP states that this varies from other BI systems, where data from multiple sources and users are often combined to switch between various applications in tasks such as reporting. Analytics Cloud users can operate more effectively with all the data sources and predictive functions in one product.

Key Features

  • It is a highly customized product for the user’s sake.
  • It gathers from different data sources without significant environmental changes.
  • Integrate with various business applications seamlessly.
  • SAP Analytics is available for mobile applications.
  • Story design is simple enough to start basic users, but it also has adequate advanced functions for complex dashboards.

Planning Capabilities:

Model: The first step to gain insight from the Analytics Cloud is to link our collected data to the software (SAC) from our business. You can do that by either importing data from .csv or Excel or connecting the on-premises data source or cloud.

Stories: Stories are the places where users explore and visualize data for reporting, planning, and analysis.

Advantages of Story building in cloud Analytics are:

  • Discover feasible real-time insights.
  • Powerful integrated platform for analytics as a service.
  • Collaborative business planning.
  • Support to sophisticated predictive analysis.
  • Quick, reliable, and consistent decisions.

Versioning and Data Locking

A version is a database data set, which is displayed in a table. We can create public, private, or shared versions to restrict who can access a version. The planning process also requires many staff who are responsible for working exclusively with data. SAP Analytics Cloud offers data versions to address this problem:

  • Private and Public

We can make a copy of the public version, save it as a private version, work with it, and do so without the possibility of overwriting the public version of data with errors. The data can be saved in the public version after the indicators have been verified.

Data Locking: If a group of employees collaborates, we can put a lock on editing those data (cells). In this case, only the responsible individual can edit the cells for this data block.

Input Task

The input function is used by colleagues to provide feedback or supplementary information. Input tasks may be allocated to one or more colleagues and used for various tasks. The task is sent to our colleague/managers, who adds the needed information to the story, via a link to your personal story. If the story contains value drivers, the assigned can also change the data in the value driver tree by performing simulations. Once it has done then he or she sends us the task

Our Story needed to update with the following data to create an input task.

  • The model that has single dimension with a responsible user can be identified.
  • Need a Private version
  • The model should be a planning model.

Predictive Forecasting:

SAP Analytics Cloud prediction provides us with knowledge of past patterns in data to forecast any possible metrics. The prediction algorithm classifies existing information, recognizes outlying relationships, and surfaces within your information to help visualize and understand the key influencers of your business.

Predictive analysis for SAP Analytics Cloud:

  • Discover main influencers such as income, churn, and productivity in your KPI.
  • Explore interactive graphs and charts created by your question automatically.
  • Predict future outcomes based on historical data Predictive predictions.


We can add our values in the table in addition to fetching values from model data. To do so, use the SAP Analytics Cloud allocation function that involves the distribution of values and the allocation of the values. Allocation is a method of partition into multiple values of the values from source data and storage of the values in the target values. The allocation mechanism is used to gain insight into the planning and analysis of data. The distribution and assignment of activities are ways to assign values to one or more target cells in a row.

Value-Driven Tree:

The Value Driver Tree method is another important function of the BI module that goes along with planning. It allows the driver to model the business if you calculate a final KPI based on all of the driving metrics. Such simulations can be re-written to the model for further detail.

The Value Driver Tree represents interdependence physically, using measures to generate a simulated effect of changing a measure underlying the parent. SAC enables slider inputs to adjust metrics and recalculates the whole model according to its result. Quite strong and very useful in simulation and preparation.

Data Actions:

SAC simulates an excellent interface for data copying/pasting. But if a large and repetitive amount of data is to be performed regularly and a series of copying actions and measurements, the action set may be stored as a data action trigger. With the support of a process flow, data action triggers will sequentially execute a series of activities. The action can be a simple copy of an account, a filtered copy of facts in one or more models or even a complicated calculation applied on a given timeframe also. Each action can be graphically described or scripted based on your preference. Data behavior once configured will perform its magic with a button in the story.

Reference/Source of the information referred:



Which MOURI Tech service, this article relates to:

Chandrasekhar Gorapalli
Analytics (EPM)

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