## Principles of sector reallocation

Each subscription on the HUB platform provides for the implementation of a panel extrapolation configuration which is either static or dynamic.
Some of our customers choose a static setting, as part of some custom options. In particular for monitoring a "CUSTOMER TYPE". For more information, you can consult the following article: http://success.openhealth.fr/fr/articles/3304106-comprendre-ce-qu-est-le-panel-openhealth-de-pharmacies

To calculate sales to the sector, OpenHealth reallocates national sales to the sector. The reallocation of national sales to the sector makes it possible to overcome the geographical dimension by being more specific to the sector (your network or targeting no longer depends on the UGA because all the pharmacies of a UGA do not have the same potential).

We use reallocation coefficients:

• a product coefficient
• a market coefficient

Why use 2 coefficients, a product coefficient and a market coefficient? The advantage of having 2 coefficients, product and market, is to better represent the sales of products with low Distribution Digital Sales, improve the accuracy of geographic coverage of products in launches, take into account price variations and have finer temporal granularity, with daily and weekly data. For more information, you can consult the following article: http://success.openhealth.fr/fr/articles/3545561-calcul-des-ventes-au-secteur-ce-qu-il-faut-savoir

## Methodological lines

For the product coefficient , the following parameters are taken into account in the reallocation:

• The weight distribution in number of pharmacies of the sectors or customer-type modalities in the OpenHealth panel

Example: Let be 1 customer type with 2 modalities "A" and "B".
The "A" method of this customer-type lists 6,700 pharmacies in the OpenHealth panel and the "B" modality with 5,000 pharmacies.
Then the weight in number of pharmacies of modality "A" is 57% (6.700 / [6.700 + 5.000]) and the weight of modality "B" is 43% (5.000 / [6.700 + 5.000] )

• The weight distribution in total turnover of the sectors or customer-type modalities in the OpenHealth panel

Example: Let be 1 customer type with 2 modalities "A" and "B".
The "A" modality of this customer-type identifies weighs 15.6 billion € and the "B" modality 9.3 billion €.
So the total turnover weight of modality "A" is 63% (15.6 / [15.6 + 9.3]) and the weight of modality "B" is 37% (9.3 / [15.6 + 9.3])

• The representativeness in number of pharmacies of each sector or customer-type modality in the panel vs. the total France

Example:
Modality A lists 6,700 pharmacies in the panel vs. 12,200 in total France.
The representativeness rate in terms of number of modality “A” pharmacies in the panel is 55% (6,700 / 12,200).

• The representativeness in total turnover of each sector or customer-type modality in the panel vs. the total France

Example:
The total value sales of modality A weighs € 15.6 billion in the vs. panel. € 23.3 billion in total France.
The representativeness rate in total turnover of modality A in the panel is 67% (15.6 / 23.3).

For the market coefficient , it is calculated from sales reallocated with the application of product coefficients, as well as a segmentation of your market according to your product hierarchy.
This includes as standard a segmentation discriminating the levels: market, segment, laboratory and brand in each sector.

## Static sector reallocation

The static reallocation is based on an exhaustive census of all pharmacies in the territory.
To these pharmacies are added the information of assignments to the sectors or customer-type modalities.
This list of pharmacies constitutes a fixed list of pharmacies which will be monitored and which are controlled by the customer.
This list will be the sole source of information on all the periods processed.

Illustration of the coefficients used in static reallocation within the framework of a customer-type with 2 modalities "A" and "B":

## Dynamic sector reallocation

The dynamic reallocation is based on the one hand on the exhaustive inventory of all the pharmacies in the territory used in the static reallocation, crossed on the other hand with the sales of pharmacies on your market over each period.

This method makes it possible to be based on information criteria taking into account the sales data processed over each period, thus ensuring an evolving follow-up.

If the number of pharmacies is smaller, this method nevertheless has advantages:

• The relative weight of the modalities distribution of the big makers in your market will be better taken into account,
• The representativeness rates are directly based on the data processed and consequently allow finer readjustments at the level of products, brands and laboratories,
• Brands with low DN products and launches will be better considered with this method.

The market coefficient being based on these dynamically reallocated sales, this is why the brands' market shares are likely to move compared to the static reallocation.

Illustration of the coefficients used in dynamic reallocation within the framework of a customer-type with 2 modalities "A" and "B"