A buyer rings on a Tuesday and asks whether the 25-person kit is moving or sitting. The distributor answers from memory, names a rough number, and the call moves on. Four months later the same kit appears on a clearance list, and nobody can say which month the turn started.
Distributor sell through data does not require a dashboard, a distributor management system or a paid data feed. Six signals can be built from records a distributor already writes every week: supplier invoices received, invoices issued to customers, dispatch notes, and physical stock counts. Together they answer the two questions behind every reorder decision. How much of what arrived has actually left the building, and how many weeks of cover remain at the current rate of movement.
What Distributor Sell Through Data Means Without a Platform
Three labels are used as though they describe the same number. They do not.
- Sell-in is what a supplier invoices to you. It is a shipment.
- Sell-through is what you invoice onward to your own customers. It is a movement.
- Sell-out is what the end user buys at the counter. It is demand.
A distributor lives between the first two. The distance between them is the channel stock you are financing, and it is the number that quietly decides whether the next order is a replenishment or a write-off. Practitioners who model this describe channel stock as an identity rather than an estimate: on-hand at the distributor, plus on-hand at your customers, plus goods in transit, minus returns still moving back up the chain (Cleverence channel inventory guide).
The practical consequence for a distributor with no software is narrower than it sounds. You do not need the full identity. You need three of its terms, all of which sit in your own files: units received, units dispatched, and units counted on the shelf at month end. Everything below is a ratio built from those three numbers, and the whole of your distributor sell through data sits inside them.
The Six Signals Inside Your Distributor Sell Through Data
Each signal below has one job: it flags a decision. Read as a set, distributor sell through data turns a shelf you can only see once a month into a weekly reading. A number that does not change a decision is a hobby, not a metric.
| # | Signal | Formula | What it flags |
|---|---|---|---|
| 1 | Sell-through rate | Units sold ÷ units received × 100 | Whether a delivery is being absorbed or accumulating |
| 2 | Weeks of supply (WOS) | Stock on hand ÷ average weekly sales | How long cover lasts if the current rate holds |
| 3 | Stock days on hand (DSOH) | Stock on hand ÷ average daily sales over 30 days | The reorder trigger, in days |
| 4 | Order interval drift | Days between your own repeat purchases, versus three cycles earlier | Demand change before it reaches a forecast |
| 5 | Fill rate | Units dispatched complete ÷ units ordered by your customers × 100 | The part of your stock problem that is actually a picking problem |
| 6 | Near-expiry share | Units inside the final months of shelf life ÷ total units on hand × 100 | Capital that will be lost rather than sold |
Signal 3 is the one worth calculating first, because it converts a vague worry into a date. Distributors holding 2,400 units with onward sales averaging 80 a day are holding 30 days of cover. That figure sits inside a normal operating band. Below roughly 14 days the next replenishment arrives after the shelf is already empty, and above 60 days the stock starts carrying expiry exposure rather than service value (Rework supply chain visibility library). Both failures are visible weeks in advance from the same three numbers.
Signal 4 is the one most distributors already sense but never write down. If your own reorder interval for a line stretches from 30 days to 45, your customers have slowed by a third, whether or not anyone has told you. It is an early warning that arrives before a formal forecast would notice, and it costs nothing to record because the dates are already in your purchase history.
How to Calculate Sell-Through and Weeks of Supply From Your Own Records
Two formulas carry most of the load, and both are short enough to run on a single sheet.
Sell-through rate measures how much of what arrived has sold:
Units sold ÷ units received × 100
A store that received 200 units and sold 124 has a sell-through rate of 62 percent, which is the first figure most distributors can assemble from their own distributor sell through data. If stock was already on hand when the period opened, add it to the units received so the rate covers everything that was available to sell (ModaFlow sell-through calculator). Count units after returns, not before.
Weeks of supply measures how long the remainder lasts:
Stock on hand ÷ average weekly sales
Take 400 units on hand against average weekly sales of 100, and you hold four weeks of supply. The benchmark that matters depends on movement speed rather than on your sector label: fast-moving consumable lines are typically measured in a handful of weeks, while slower, higher-value lines are managed over a longer horizon. Retail planners commonly place fashion at 8 to 12 weeks and fast-moving consumer goods at 2 to 4 weeks as reference bands, and judge their own position against plan rather than against a single industry figure (Retail Formulas reference library).
One discipline makes the whole exercise trustworthy. Write the formula, the period and the data source next to every number you report. A weeks-of-supply figure quoted without its window is not a signal, it is an opinion.
The Two Traps That Corrupt a Home-Made Channel Number
Distributors who abandon home-made reporting usually do so after a review meeting where two people quoted different numbers from the same distributor sell through data. Both traps are arithmetic, and both are avoidable.
Trap one: averaging percentages. Take a line that received 4,000 units and sold 2,400, and another that received 400 and sold 360. The first runs at 60 percent, the second at 90 percent, and the simple average of those two figures is 75 percent. The actual category sell-through is 2,760 divided by 4,400, which is 62.7 percent. Averaging the rates overstates the position by more than twelve points. Roll percentages up by summing the numerators and the denominators separately, never by averaging the rates themselves (RetailNorthstar merchandise planning KPIs).
Trap two: a promotion inside the denominator. Weeks of supply divides stock by average sales. If the average contains a launch discount or a seasonal peak, it will understate cover during every ordinary week that follows. Use a rolling window long enough to absorb one-off spikes, four to eight weeks is a common choice, and say which window you used.
There is a third failure that is behavioural rather than mathematical. A distributor who reports only sell-in is measuring their own purchasing, not the market. Shipments look strong right up to the week a partner stops ordering, and the correction then arrives all at once.
A Cadence That Fits a Distributor’s Order Cycle
Reporting cadence should follow the decision it supports, not the calendar of a software product.
| Cadence | Recalculate | Decision it supports |
|---|---|---|
| Weekly | Sell-through rate by line; fill rate | Which customer orders to chase this week |
| Monthly | Weeks of supply; stock days on hand; near-expiry share | What to replenish, what to slow down |
| Quarterly | Order interval drift; sell-through versus plan | Assortment mix for the next buying cycle |
A distributor running this cadence on their distributor sell through data spends under an hour a month on the arithmetic. The value comes from the comparison across periods, so record the numbers in the same layout every month. A single month of sell-through data tells you almost nothing. Six consecutive months tell you which lines are drifting and how fast.
Working the Signals With a Supplier
These numbers change the shape of a reorder conversation, because they replace a request with a case. A distributor who can say that a line has moved from eight weeks of cover to three, and that dispatch volume rose by a fifth in the same period, is describing demand rather than asking for a favour.
Three practical points apply when those numbers go to a supplier.
- Separate the replenishment order from the range review. Replenishment is arithmetic. Range decisions involve lead time, tiered quantities and, for private-label work, minimum order quantities that start from 1,000 pieces. Mixing them slows both.
- Ask what the supplier can hold constant. For repeat orders the useful question is not price alone, but whether the carton configuration, component specification and artwork remain identical between batches. Continuity is what makes your own stock planning repeatable.
- Send the period with the figure. A supplier reading “sell-through 62 percent” will ask which months it covers. Send the window, the units and the source in the same line.
The same logic applies to the consumable side of the range, where replacement cycles are shorter and cover runs down faster than on durable bags or boxes. Lines that turn in weeks should carry tighter triggers than lines that turn in quarters, and the first aid consumables category is where a distributor’s working capital usually moves fastest.
Two further references help when the figures raise a wider question. Where the planning question is which products deserve a place in the range at all, first aid product demand testing for distributors covers the testing method that sits in front of these numbers. Where the question is how a set of measures becomes a repeatable review, distributor channel metrics shows how the same figures roll into a scorecard.
Distributors reviewing a mixed range of stocked and empty formats will also find the assortment discussion in wholesale first aid product assortment useful, and those planning a refill programme can connect the cover figures to the recurring model described in first aid consumable refill revenue.
For the broader channel design question, first aid distribution strategy sets out how assortment and channel roles fit together.
FAQ
How often should a distributor recalculate distributor sell through data?
Weekly is the practical minimum for lines that turn in weeks, because a fortnight of unnoticed movement is often the whole margin on the line. Monthly is adequate for slower, higher-value items. The useful rule is to match the cadence to the cover: if a line carries six weeks of stock, recalculating it monthly gives you roughly six opportunities to act before the shelf empties. If it carries two weeks, monthly reporting means you are always reading history rather than planning.
What is a good sell-through rate for first aid products?
There is no single target, and any source quoting one figure for the whole category is describing a different business. A consumable that is bought to run down steadily should be judged over its own selling window, while a durable bag or a hard case is held longer and turns more slowly. The workable standard is internal: compare this month against the same month last year, against your own plan, and against the weeks of cover remaining. A rate falling while cover rises is the pairing worth acting on, regardless of the absolute percentage.
Can these signals work without a stock count?
Three of the six can, and the three that cannot are worth the count. Sell-through rate and order interval drift come from documents you already generate, so they can be calculated at any time. Weeks of supply, stock days on hand and near-expiry share all depend on knowing what is physically on hand, and a perpetual inventory that has never been verified drifts from the shelf. A monthly count of high-turn lines is usually enough. Count the lines that move fastest first, because that is where an error in the stock figure changes the decision.
Should weeks of supply use sales value or units?
Use units for replenishment decisions and value only for financial reporting, then keep the two clearly labelled. Units drive the physical decision: whether the next carton arrives before the shelf empties. Value is distorted by mix, by tiered pricing on larger quantities and by any currency movement between order and sale. A distributor who reports cover in value alone can end up replenishing a cheap, fast-moving line while a high-value line with the same cover figure is left to run dry.
How do these numbers change the conversation with a supplier?
They convert a request into a description of demand, which is the difference between being placed in a queue and being planned for. A supplier who receives units moved, cover remaining and the period covered can align a production slot, confirm whether the specification stays identical between batches, and flag whether the quantity crosses a tier. Suppliers cannot plan around a distributor who orders late and in unpredictable sizes. They can plan around one who sends the same three numbers every month.
The Point of the Exercise
Home-made channel reporting is not a substitute for a platform. It is the layer that tells you whether a platform would be worth buying, and it often removes the question entirely.
Start with stock days on hand on the ten fastest-moving lines. Add sell-through rate at the end of the next delivery cycle. Record both in the same file each month, with the window and the source written beside them. Within two quarters your distributor sell through data shows which lines are absorbing stock and which are accumulating it, and the reorder conversation stops being a guess.
For the wider picture of how assortment, channel role and replenishment interact across a distribution business, first aid distribution strategy is the starting point.
Read together with range depth decisions, sell-through tells you not only what moves but how much stock belongs behind it.