SAP Analytics Cloud (SAC) promises a one-stop solution to a wide range of enterprise needs ranging from predictive forecasting to BI reporting. Planning, being an integral part of this solution, SAC gains an edge over other standalone planning/reporting solutions in the market. This blog, the first in the series will help you give a holistic idea of what SAC offers as part of the planning module while the entailing blogs will walk you through the actual implementation process.

Best of both worlds – Planning

Single data entry, Mass data entry

Strategic or operational – you name it, SAC has it. SAP analytics cloud provides support for Top-down planning and allows you to enter your data values at any level in your hierarchy. What happens to the data cells in the underlying levels of granularity? Do they remain blank? Will there be a separate tool where I would have to split the parent’s plan data to the underlying children and re-enter the data? Fret not! If data entry is done into unbooked cells, SAC equally distributes it to its child members. On the other hand, if there is existing data in the cells and if a modification is made, SAC automatically spreads the data in the same ratio as the underlying members. This helps to preserve existing patterns in the data while updating the dataset with new plan values. To make the planner’s life easier, SAC supports two modes – Single data entry and Mass data entry. Impatient to wait for the calculations to update while making entries? Mass data entry lets you make a bulk of entries and you can pause the re-calculations until you are ready for it. Unpause, update, publish and share!

That’s data entry for you!

Planning in SAP Analytics Cloud Series 1: Overview
Single data entry

Re-shape data by structured allocation

Spreading, Distribution, Allocation and Execute Allocation

Consider a data blending scenario where data is at different granularities for different accounts. One account is missing line item level information. Will I have to resort to manual entry? No. Structured allocation allows for manual percentage allocation where a value from a cell can be distributed to its children, among its siblings or even pick up the ratio from a separate data source using the eyedropper tool. Tedium too much for manual percentage allocation? Automate it all using Execute allocation process to use a different account as a driver for the percentage distribution.

Planning in SAP Analytics Cloud Series 1: Overview
Allocation example

Dynamic master data maintenance

On-the-fly member creation

Let us assume you view a list of vendors that your company acquires goods from. If a new local retailer comes along and proposes a quote and you would like to see the impact of the purchase on the overall picture. This new retailer need not be present in the master data of the source system for you to perform this ad-hoc analysis. With on-the-fly member creation, you can enter new member values for any given dimension and enter facts corresponding to them. So, if there had ever been a misconception that planning only allows fact-entry, members on the fly is a pleasant surprise for you.

Planning in SAP Analytics Cloud Series 1: Overview
On-the-fly Member

Maintenance and Management

Data Locking, Version Management

You might be wondering by this point, “Anyone can enter anything? Does this all not go against maintaining the sanity of the single source of truth against which a whole team of users is to report on? How can I maintain the data quality while still having the flexibility of ad-hoc analysis?” You can save multiple versions for the same account and for the same category (Actual, Forecast, Plan) and play around with it, forecast on it and keep it local to your account until you are satisfied with your changes and publish it back to the model for usage by all other users in the team. Then comes the question of who gets to edit what. With SAC’s extensive data locking capabilities, you can lock/restrict or grant control to users right down to particular members in driving dimensions with ability assign owners for controlling the same.

Planning in SAP Analytics Cloud Series 1: Overview
Data Locking Options

Simulations and forecasting

Forecasting and Value Driver Tree

SAC allows for forecasting through just a right-click with three different algorithms – Linear regression, Triple Exponential Smoothing and Automatic Forecasting (a proprietary algorithm). Although a multitude of front-end tools allow for forecasting in as less as a click, SAC takes the upper hand by the ability to write-back to the model with the forecasted values, thus enabling reusability. Though forecasting is available as part of the BI module, if the prediction is the need of the hour for your company, the SAC Smart Predict module in conjunction with the planning module is your way to go. One other powerful feature of the BI module that goes hand in hand with planning is the Value Driver Tree process. Allowing for a driver-based modelling of your business, this allows for what-if simulations of one final KPI based on all the driving metrics. Said simulations can be written back to the model for further insights.

Planning in SAP Analytics Cloud Series 1: Overview
Predictive Forecast

Collaboration and delegation

Input Tasks

One underrated hassle in the planning is the actual collection of data. Interaction with a colleague to gather their input happens typically outside the planning system. What if the planning system also encompassed the ability to delegate the data collections tasks? What if it could show the current status of the task, send reminders and all that is required is the maintenance of the person responsible list for the members of the dimension under question. SAC provides input tasks to ease the load on senior-level planners by enhancing collaboration.

Planning in SAP Analytics Cloud Series 1: Overview
Input Task

Data manipulations

Data Action Trigger

SAC simulates an excel-like interaction for copy/paste of data cells. But if the bulk of data is large and repeated a set of copy actions and calculations is to be performed periodically, the set of actions can be saved as a data action trigger. Providing a flow graph like interface, data action triggers can perform a series of actions sequentially. The action can be a simple copy of an account, filtered-out copy of facts within one or between models or even a complex calculation applied on an account for a specific timeframe alone. Each action can either be modelled graphically or through scripts based on your preference. Once configured, data actions can do their magic with a click of a button from your story. The updated values, once written back to the model will affect all the applications in the landscape using the model.

Planning in SAP Analytics Cloud Series 1: Overview
Data Action Trigger

In the blogs that follow, we will step into the shoes of a procurement company and help them plan their SCM through SAC. Make sure to watch out for this space.

Check out our next blog in this series here to learn more about Analytic Applications in SAP Analytics Cloud.

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