Your Sell-in data each month, at the pharmacy and product level, is a necessary input to the calculation of sales data at the UGA.
Sell-in is an integral part of the Sell-out calculation for a breakdown as fine as the UGA, as some UGAs have less than 15 pharmacies.
Sell-in analysis is the only way to capture/identify certain atypicalities in the UGAs. This is true regardless of which pharmacies are panelists.
Atypicalities can be, for example, a particularly high Sell-in level or a very strong evolution.
We use an existing industrial method, proven and validated by all our customers.
It is the method of reallocation of sales data to the region and to the sector, and it can be applied to any other type of breakdown, geographical or not.
Once the sales are reallocated to the sector, we integrate your Sell-in to calculate the weight of the different UGAs within the sectors, which allows us to ensure that the sales of the sum of the UGAs correspond to the sales of the sector, in the same way that the sales of the sum of the sectors correspond to the sales of the country.
To learn more about the calculation of sector sales: http://success.openhealth.fr/fr/articles/3545561-calcul-des-ventes-au-secteur-ce-qu-il-faut-savoir
Business case: A sell-out is observed on a UGA while none of my pharmacy clients have made a purchase (sell-in)
If the sell-in that you provide us corresponds to direct sales to identified pharmacy customers, it is nevertheless possible for a pharmacy to obtain supplies in other ways, from a wholesaler-distributor for example.
This corresponds to the supply of pharmacies through indirect sales.
In this case, we do not have sell-in data identifying the pharmacy in the sector, but the pharmacy can still dispense the product without being identified as a client.