The next forecast period is upcoming and as always, several actions are needed to make sure everything is ready for planning. Is the data ready and loaded? Is the baseline data prepared and are the calculations correct? How nice would it be if every forecast could be prepared with the press of a button.
This blog describes how to prepare every forecast cycle in no-time, using SAC Planning Data Actions and dynamic properties as a key to forecasting efficiency.
With SAP Analytics Cloud Planning you are able to create highly dynamic, yet relatively easy, data action scripts. These scripts can be reused for each forecast with little to no maintenance. You create the basis for dynamic data actions by making smart use of properties in your version dimension. After using this set-up, only a few small changes are needed for every new forecasting cycle. Setting the baseline with the press of a button.
Data actions are a flexible planning tool for making structured changes to model data in SAP Analytics Cloud, including copying data from one model to another. Data actions are designed by modelers and then run by planners in stories or analytic applications, or scheduled to run in the calendar. Examples are copying data, running allocation steps, and executing scripted calculations.
No need to manually adjust dates in the back-end or setup elaborate and/or prone to error filters in the front end. Simply add the correct properties in the dimensions and introduce a parameter in your script to read the property. This reduces manual work, reduces the risk of incorrect entry and is more pleasant for the end user.
A common practice in forecasting is that you want to upload only the actuals for that specific year that are available and relevant. Meanwhile, every new forecast will have new date ranges; the April forecast will have actuals available until march. The July forecast will have actuals available until June.
Making sure that the data action considers the correct data set, without smart properties, you will have to set them manually and fixed. When the period is fixed, it means you would need to manually adjust the data action every year or even every month, depending on time windows. A parameter, on the other hand, introduces the risk of incorrect entry and in general is more pleasant for the end user.
Add the start of the forecasting cycle, and the latest month with actual data as properties of the version dimension
Another use case is that for each forecast, certain actuals are or are not available. For FC10, done in October, we don’t want any calculations for January-September, since actuals are available for that. With use of the smart property ‘latest actual month’ the calculations will be automatically limited to all months later than the ‘latest actual month’.
There are many more options to use smart properties. In case you would like to read on how to set them up, please read ‘How to set-up data actions with smart properties’.