Days on hand and days of inventory: how many days of stock do you have
Who it is forGrocery chain inventory planning, buying, store operations
The question "how many days of stock do we have" has two separate answers and both are correct. One gives the average of the period just past, the other says how long today's stock will last. For the same store the first can read 91 days and the second 24; they do not contradict each other, they answer different questions. This guide separates the two calculations, shows the weeks of supply method and explains how target days on hand is derived from lead time.
What days on hand is and how it is calculated
Days on hand — also called days of inventory, days sales of inventory or DSI — shows how long one turn takes. It is inventory turnover expressed in days.
It is calculated two equivalent ways. If turnover is already known, divide 365 by it; if not, divide average inventory at cost by daily COGS. Both routes always give the same answer.
This measure looks backwards and it is an average. It does not answer "how long will what I have last"; that question needs the calculation in the next section.
- Days on hand
365 ÷ Inventory turnover- Equivalent form
Average inventory at cost ÷ (Annual COGS ÷ 365)- For a monthly period
30 ÷ Monthly turnover
Days of cover: the forward-looking calculation
Ordering decisions are not made on a historical average but on how long today's stock will last. This calculation runs on units and never touches cost.
The choice of denominator matters. A seven-day average catches sudden change but mistakes a single promotion day for lasting demand; a twenty-eight-day average is steadier but sees a new trend late. In practice both are kept side by side and the gap between them is read as a warning signal.
For seasonal products, forecast daily sales replace the historical average. Between April and June the daily sale of ice cream differs several times over; an order placed on the historical average runs out in June.
- Days of cover
Current stock in units ÷ Average daily unit sales- Weeks of supply (WOS)
Current stock in units ÷ Average weekly unit sales- Season-adjusted
Current stock in units ÷ Forecast daily unit sales
For SKUs close to zero cover the average sale has already fallen: a product that stopped selling because it was out of stock looks like a slow seller. Days with no stock have to be excluded when calculating the denominator.
How to set target days on hand
Target days on hand is not a matter of judgement; it is derived from lead time. It has three components and all three are measurable.
The first is lead time: the days between placing the order and the goods reaching the shelf. Order confirmation, production, shipping, customs and goods receipt are all inside that window; most businesses count only the shipping leg and assume a lead time shorter than the real one.
The second is safety days: the buffer held against variation in demand and lead time. The third is half the order interval; if you order weekly you carry an extra 3.5 days of stock on average.
- Target days on hand
Lead time + Safety days + (Order interval ÷ 2)- Target stock in units
Target days on hand × Average daily sales
| Supply | Lead time | Safety days | Order interval | Target days |
|---|---|---|---|---|
| Local supplier, weekly order | 3 days | 4 days | 7 days | 10.5 days |
| Domestic central warehouse | 7 days | 7 days | 14 days | 21 days |
| Import, container | 45 days | 21 days | 30 days | 81 days |
The gap between target and actual days on hand is a direct measure of excess stock or out-of-stock risk. No ordering process that fails to keep both numbers on one screen can correct itself.
When the two measures diverge and what that means
When overall days on hand and SKU-level days of cover move apart, the problem is not the amount of stock but its distribution. There is enough goods in total, but it is in the wrong place.
Two patterns are typical. First: average days on hand high, with a large number of SKUs showing low cover. That means a few slow items are inflating the stock while the fast movers starve — too much assortment, not enough depth.
Second: average days on hand low, yet cover is high on most SKUs. That usually means a large buy was made in a handful of lines and that buy is distorting the average. Neither can be spotted by looking at the average; you have to look at the distribution.
- Average high + most SKUs low → too much assortment, not enough depth
- Average low + most SKUs high → a few bulk buys are dragging the average
- Both high → capital locked in stock, a markdown plan is needed
- Both low → service level risk, order frequency must increase
Frequently asked questions
- How are days of inventory calculated?
- 365 days is divided by inventory turnover. A business with a turnover of 4.0 has days on hand of 365 ÷ 4.0 = 91. The equivalent route is dividing average inventory at cost by daily cost of goods sold.
- What is the difference between days on hand and days of cover?
- Days on hand is the average of the period just past and is calculated on cost. Days of cover shows how many more days today's stock will last and is calculated on units. Ordering decisions use the second, stock policy uses the first.
- What is weeks of supply?
- Current stock divided by average weekly sales, showing how many weeks the stock will last. It is a practical planning unit for grocery stores supplied by weekly deliveries from the distribution centre: once cover falls below the lead time plus the time left until the next delivery, the shelf empties before the goods arrive.
- How do you set target days on hand?
- Add lead time, safety days and half the order interval. For a product with a 7-day lead time, 7 safety days and a 14-day order interval, target days on hand is 7 + 7 + 7 = 21.
- What should I do if days of inventory is too high?
- Look at the distribution first: which lines are lifting the average. If stock older than 180 days makes up a large share, the problem is not order quantity but ageing stock, and the fix is a planned markdown. If the distribution is even, increase order frequency and reduce batch size.