Describing Planning Features

Planning is all about setting strategic goals for a business and then determining how to meet those goals by creating annual budgets, tracking progress in forecasts, and simulating scenarios to find new opportunities. These plans are formed by projecting historical data (known as Actuals) into the future, by gathering input from different departments, and by considering trends, risks, and opportunities in the market.

Because planning activities are a collaborative effort, SAP Analytics Cloud provides many options and utilities to make the entire planning process run smoothly. Let's take a look at how SAP Analytics Cloud can help with enterprise planning activities.

SAP Analytics Cloud has many planning features that help you plan simpler and faster.

In this lesson, we provide an overview of the following:

• Data entry
• Version management
• Data locking
• Data actions
• AI-assisted features for planning
• Validation rules
• Value driver trees
• Allocations

Planning features are covered in detail in the Performing Manual Planning with SAP Analytics Cloud and Leveraging Advanced Features in SAP Analytics Cloud for Planning courses.

In addition, SAP Analytics Cloud can be integrated with on-premise SAP planning systems, allowing you to maintain your investment in an existing planning system and use SAP Analytics Cloud as the front-end for planning activities.

Let's go through each of the planning features in more detail.

Data entry is based around the table, where you can type relative or absolute values into individual cells. You can copy cell values, along with all the data that aggregates up to the copied value. You can plan at any level of a hierarchy, and the data will automatically be rolled down to the lowest level.

When then data changes, the affected cells are shaded yellow, indicating the data entry function is being used but not saved. Data entries can be tested before you save and publish them.

You can type an absolute value in a cell, or type a relative value such as *2 or +500 to perform simple mathematical calculations on existing data. For example, if the data value in a cell is 100, and you type *2 in the cell, the value will change to 200.

When you are planning for all possibilities, it helps to understand how different plans relate to each other and to your actuals data. Version management helps you to complete tasks such as the following:

• Carry out variance analysis, such as making sure that your working forecast is on budget.
• Quickly explore, share, and publish different scenarios without losing sight of the original data or introducing unnecessary complexity.
• Work on your own data until you are ready to publish.
• Try a change and undo/redo.
• Use the history to see what happened with the data.
• Roll a private version back to a previous state if you need to take a different direction.
• Revert all changes to the original values.

With data locking, you can choose sections of data to lock when you are getting ready to close your books. Each section can also be delegated to owners who can lock the data themselves, or set the data to a restricted state where only the owners can edit it. You can then schedule changes to data locks in the Calendar.

With data actions, you can model sequences of copy-paste operations, allocation steps, and advanced formulas. With advanced formulas, you model complex processes such as cash flow planning, depreciation, and carry-forward operations. You can build these formulas using a visual editor that does not require scripting knowledge, although a scripting engine is also available for fine-tuning.

The following data action steps are available to you:

• Copy Step
• Cross-Model Copy Step
• Allocation Step
• Conversion Step
• Fact Deletion Step
• Embedded Data Action Step
• Advanced Formulas Step

Copy steps make it easy to move data from one part of a model to another, or to a different model. For example, if you have separate models for headcount and expense planning, you can use a data action to copy data from those models into a central finance model.

To make your data actions more flexible and easier to update, you can also add parameters that can be set while designing or running the data action. You can also run other data actions as steps within your data action, letting you quickly reuse common calculations.

Planning users can run data actions in a story. Alternatively, you can use the calendar to schedule them to run automatically.

SAP Analytics Cloud data actions are like planning functions and data manager packages in other SAP planning solutions.

The AI-assisted features, if enabled by your administrator, can help you plan more efficiently.

1. The SAP Analytics Cloud, AI-assisted prompt insights feature can be used to accelerate your data analysis and decision-making process. By adding the widget to your SAP Analytics Cloud planning story, you can to analyze your planning data in context, alongside your existing visualizations and tables.
2. SAP Analytics Cloud, AI-assisted data actions can make the script writing process in an advanced formulas step more efficient and can also simplify the process of adding comments to document scripts. When working in the Script tab of an advanced formulas step from a data action, you can generate scripts or comments.
3. The AI-assisted data action documentation feature can be used to generate data action documentation based on the data action steps.

These topics are covered in more detail in the Planning Using SAP Analytics Cloud lesson in the Performing Manual Planning with SAP Analytics Cloud course and the Using the Script Editor to Create an Advanced Formula Data Action lesson in the Leveraging Advanced Features in SAP Analytics Cloud for Planning course.

Validation rules let you define valid member combinations across dimensions to prevent improper data entry and planning operations in stories based on a specific planning model. For the dimensions you define in a dimension combination rule, only the member combinations that you specify as allowed combinations can pass validation.

For example, you might want to increase sales of certain products in specific locations. You create a validation rule between the product dimension and location dimension members. Planning users can do planning only for the allowed combinations of products and locations.

Value driver trees let you take a driver-based planning model and turn it into a streamlined visualization for running simulations and making strategic decisions. For example, you might be discussing how vulnerable your business is to raw material prices, or which product line to grow over the next few years to increase profitability the most. Value driver trees allow you to book values to drivers and inputs, visualize the flow of value through the accounts, and see the overall impact on KPIs now and in the future.

You create value driver trees directly in the story. The option to add nodes automatically based the model’s account structure can help you get started quickly, but you can still add and customize nodes as needed. Features like undo and redo, search, and drag-and-drop node linking make it easy to get set up.

Using data actions, you can create structured allocations and establish reusable steps for allocating costs, such as allocating the cost of IT support across different departments by support hours used, or the cost of travel across different product groups based on cost-of-living rates for the customer location.

You build allocation steps using a visual tool that does not require scripting expertise, but that covers a range of different allocation workflows.