A pharmacy can receive thirty units without selling thirty. It can also sell this week products that were delivered last month. To understand replenishment you therefore have to separate deliveries, sales to the end customer and stock. That is the basis of sell-out tracking.
Sell-in and sell-out: name the level you observe
Sell-in means sales into the distribution channel: from the brand to the wholesaler, or to the pharmacy when it buys direct. Sell-out here means the pharmacy’s sales to the end consumer. A file of despatches from a warehouse to pharmacies is still data about supplying pharmacies.
These sales are measured in units or in value. To compare levels of the channel, use the same product, the same pack size, the same dates and the same unit. A brand’s revenue excl. VAT cannot be subtracted from retail revenue incl. VAT: the prices and the margins are different.
Reconstruct sales from two stock counts
Fictional example: a pharmacy starts the month with 24 units, receives 36 and ends with 18. It returns four units to the supplier and removes two that have become unsaleable. There are no customer returns in the period. Estimated gross sales are 24 + 36 − 18 − 4 − 2 = 36 units. Leaving out those six outbound units would wrongly report 42 sales.
For net sales, subtract from gross sales every customer return recorded at the till, including those that never go back into stock. For example, 10 units to start with, 3 sold and 1 return put back into stock leave 8 units at the end: the stock reconciliation reconstructs 3 gross sales, but the till shows 2 net sales. A stock count on its own is therefore not enough to know net commercial sales.
This reconciliation assumes accurate stock figures and complete movements. A count taken on the Monday cannot be compared, without adjustment, to deliveries cut off on the Friday. Keep till data as the reference whenever it is available.
Opening stock and inbound60 units
- Estimated gross sales36 units
- End-of-month stock18 units
- Returns to the supplier4 units
- Unsaleable goods removed2 units
The six units returned or removed are not sales. Every movement covers the same period.
Choose a source that fits the question
Till data (EPOS)
This is the most direct source for tracking retail sales. Check access permissions, granularity, lag, returns and how many pharmacies are covered. A brand does not need the consumer’s identity to track sales of a product.
Panels and aggregated data
These help you place a range within a market. Scope and method matter: exhaustive data or a panel, participating pharmacies, extrapolation, refresh frequency. GERS and IQVIA offer several data products; their ranges should not be reduced to a single figure for accuracy or lag. Ask for the documentation of the series you use.
Deliveries and field observations
Deliveries show what entered the channel, not what left the counter. A rep can record stock on the shelf and note an out-of-stock; facings alone do not measure stockroom quantities. Without an opening stock figure and complete movements, keep the term “replenishment indicator” and avoid presenting a precise sell-out estimate.
Read a variance without jumping ahead
A rise in deliveries before the summer may simply be normal stock-building. A promotion can pull purchases forward without creating as much extra consumption. Conversely, a month of low orders may follow a large replenishment. Look at several periods and at stock cover before changing field targets.
Act on an identified problem
- →Out-of-stock: check the stockroom, the delivery lead time and the quantity to reorder.
- →Overstock: understand the last purchase, the season and the assortment before pushing new volume.
- →Poor visibility: agree a suitable shelf position with the pharmacist and check it on the next visit.
- →Team unsure of the product: answer questions about its use and its limits with approved materials.
- →Insufficient coverage: target relevant new pharmacies, then track rotation after the first order.
Assess a merchandising action
To test a display unit, measure sales before and after over a comparable length of time. If you can, also observe similar pharmacies with no intervention. Record promotions, out-of-stocks and seasonal variation. An increase after a visit does not, on its own, prove that the visit caused it.
Keep a simple table: product, pharmacy, period, units sold, stock, days out of stock and the origin of the data. Rows that are not covered stay “unknown”. Replacing them with zero would artificially lower average rotation.
Numeric distribution (DN) completes this picture: it measures where the product is present. The two indicators let you tell a need to open new accounts from a rotation problem at existing customers.
Find the sell-in figure for each pharmacy
Salesia brings together the available orders and their history. That base helps you prepare visits and reconcile deliveries with your other data sources.
On the supply side, observed demand and lead times feed the safety stock and reorder point calculation, allowing for periods when the product was out of stock.
By Anatole Briant
By Anatole Briant
By Anatole Briant
CEO of Salesia
Anatole Briant is CEO of Salesia. He is your contact for demonstrations, pricing and partnerships.