SAP Analytics Cloud has many planning features that help you plan simpler and faster. These features include the following:
Validation driver trees
Let's go through each planning feature in detail.
Data entry needs to be efficient and easy, whether you are a finance expert booking values to forecasts, or a line-of-business employee providing input for a bottom-up planning process. Get a familiar experience for data entry using a table that shares many functions with common spreadsheet applications.
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. You can use the Planning Panel to quickly adjust proportions between members and move values along multiple dimensions.
When there is a data change, notice the asterisk (*) in the affected column. This and the yellow markup means 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.
- Roll a private version back to a previous state if you need to take a different direction.
You can use the Version Management panel, or just right-click the version header to access these options.
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.
Copy operations 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 then run data actions in a story. Alternatively, you can schedule them to run automatically in the Calendar.
SAP Analytics Cloud data actions are like planning functions and data manager packages in other SAP planning solutions.
Planning processes can get complicated. You can use the Calendar to keep track of tasks, stay on schedule, and collaborate with your team. Create, assign, and work on tasks, and add files, approval workflows, and processes that link tasks together. Create multiple tasks at once using recurrence, or generate tasks automatically based on model data. You can also use the calendar to schedule data locking and automatic data actions, and to view your input tasks and publications.
With predictive forecasting, you do not have to rely on your intuition alone. Back up your forecasts by selecting a value and calculating the likely outcomes for future periods based on historical data. You can then add the predicted values directly to your table.
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.
Validation rules let you define allowed 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 that certain products are allowed to be sold in limited 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
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.
When your plan needs input from a group of coworkers, such as regional managers, you can assign an input task to them.
These managers can be assigned to their areas within the model, so that you just need to choose the regions and send the input task. Each manager adds their input in a story that is filtered to their own region, and then sends the task back for review. At the end of the process, the results are booked to your version of the data and you can continue your work.
Currency conversion features make it easy to work with data from multiple currencies, and to predict the effects of exchange rate shifts. Exchange rate tables can be applied to more than one model, and swapped out as required. They can also contain multiple rates for different dates and categories of data, and for specific scenarios. From within a story, you can view your data in different currencies, apply a different set of exchange rates, or analyze multiple exchange rate scenarios side-by-side.
You can use structured allocations to 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 sales revenue.
You build allocation steps using a visual tool that does not require scripting expertise, but that covers a range of different allocation workflows.