In the settings of the mapping it's possible to define how to map the source data into timescale. Select Periods in specific year and define the year you'd like to have the monthly percentages imported in. In the printscreen you can see the settings to select.
Thank you for your response! Only I need some more guidance to resolve my question:
The data I want to import has the months in the rows, which have to be imported on the time dimension for all the years that are in the model (see attachment). Meaning that for all January columns the Seasonality should be equal to 8.33%, etc.
The way I import it now, that is shown on the picture in the attachement, Anaplan is importing the rows as rows and therefore, no data is imported.
In case you'd like to import a source (1 for Jan in your case) to multiple targets (Jan 16, Jan 17, etc.), this is not possible. But, in case your assumption is that distributions are defined by month and equal over years, why don't you:
1. create a list (Jan-Dec with code 1-12)
2. build a module with this dimensionality to load the distributions once for all periods
3. link it to the module with time dimensionality with a look up for further calculations in your model?
If your load is purely a prepopulation of data which can be manually adjusted by the end-user, you can consider to:
1. make two line items called Seasonality input and Seasonality final
2. make a formula which says: if year total of Seasonality input = 0 then Seasonality input else 1/12
3. enable the user to change the input and use the final values for calculations. In case the user doesn't input, the value is defaulted by 8.33%
4. optionally for the final value: divide the input value of the user by the year total value to make sure the value always adds up to exactly 100%