Leaving Stocky is a starting point, not the whole job. If you are a Shopify merchant, operations manager, or founder who used Stocky to keep an eye on what was running low, you now need a way to estimate, inside the Shopify admin, roughly how long your current stock will last. The days of inventory remaining figure in Shopify’s inventory remaining report is built for exactly that read. It is an estimate based on recent average sales, not a demand forecast and not an automatic reorder trigger. This article walks through what the number is, how it is calculated, what its special cases mean, and how to use it sensibly alongside your other reports. If you are still mapping out the move, the Stocky migration checklist is a good companion read.
What days of inventory remaining is
Since Stocky will not be available after August 31, 2026, and was removed from the Shopify App Store on February 2, 2026, merchants now handle inventory tasks like restocking and purchase orders in the Shopify admin, and the days of inventory remaining figure is part of how you estimate stock timing there.
The inventory remaining report estimates how long your tracked inventory will last, based on average sales rates and the stock you have left. The days of inventory remaining column is a per-product (per-variant) estimate of roughly how many days your current stock will cover at your recent pace of sales.
Read it as an estimate, not a forecast. It does not know about an upcoming promotion, a season change, or a viral moment. It looks at how fast a variant has been moving lately and at how much is on hand, and it expresses the relationship between those two as a number of days. That framing is the point: a rough sense of timing, useful for prioritisation, not a precise prediction. For broader context on putting that signal to work, see the inventory replenishment hub.
The days of inventory remaining formula
Days of inventory remaining is calculated as the ending quantity divided by the average quantity sold per day. Written as a simple inline expression: days of inventory remaining = ending quantity ÷ average quantity sold per day.
There are two inputs, and both are worth understanding plainly.
- Ending quantity is how much of the variant you have left at the end of the reporting period. It is the stock on hand that future sales will draw down.
- Average quantity sold per day is your recent daily sales pace for the variant. It reflects how fast units have been leaving over the window the report covers.
Dividing the stock you have by how fast it leaves gives you a rough number of days that stock can cover. As a generic example, if the ending quantity is 60 units and the average quantity sold per day is 3 units, the days of inventory remaining is 20. If the ending quantity is 60 and the average is 6, it is 10. The formula is deliberately simple. That simplicity is what makes it easy to read and also why it should be treated as an estimate built from a past average, not a prediction of what will happen next.
When the result is N/A
If the average quantity sold per day is zero, days of inventory remaining is shown as N/A. With no recent sales in the window, the denominator is zero and a days-of-cover number cannot be computed, so Shopify shows N/A instead of a numeric value.
Practically, N/A is a signal in its own right. It points to a variant with no recent sales activity in the window the report covers. That is worth a separate look rather than a calculation: the product might be dead stock, it might be newly added with no sales history yet, or it might be seasonal and currently dormant. The estimate cannot speak to any of those situations, but seeing N/A tells you which products to investigate by hand.
When the result is 0
If the ending quantity is negative, days of inventory remaining is shown as 0. A negative ending quantity can happen with oversells or with counting issues between locations. Either way, there is effectively nothing left on hand to cover future sales, so the figure is shown as 0.
Treat a 0 as a flag, not just a number. It usually means it is time to check the underlying stock count, look at recent activity for the variant, and reconcile what the system thinks you have with what is actually on the shelf. Acting on the 0 as if it were a clean reading would skip past a counting problem that is worth fixing.
How to use days remaining after Stocky
The everyday use of days of inventory remaining is prioritisation. Sort or scan the report and you can see which variants are likely to run low soonest at the current pace. That gives you a shortlist of products where the timing of your next order matters most, before you actually run out.
Pair the estimate with how long your suppliers usually take to deliver. A short days-remaining estimate combined with a long typical supply time is a clear prompt to act sooner; a short estimate with a quick supplier is less urgent. A larger days-remaining number on a variant with a slow supplier may still deserve attention earlier than its number suggests. The estimate gives you the timing axis; your knowledge of suppliers gives you the buffer.
Be explicit with yourself about what the figure does and does not do. It helps you think about when to reorder. Setting a reorder point turns that timing read into a specific level to act on; see Shopify reorder points after Stocky. It does not tell you how many units to order. Order size remains your decision, informed by your budget, your storage, your minimum order quantities, and your read of demand.
What days of inventory remaining does not tell you
This is the most important boundary to keep clear. Days of inventory remaining is an estimate built from your recent average sales. It is not a demand forecast. It does not predict shifts in demand, the impact of a sale or campaign, seasonality, or anything that has not already shown up in recent sales data.
It is not an automatic reorder trigger. Nothing happens in your store when the number gets small. No purchase order is created, no supplier is notified, and no quantity is calculated for you. The figure does not recommend or calculate reorder quantities, and it does not tell you how many units to order.
It assumes your recent pace continues. If demand is steady, the estimate tracks reality reasonably well. If sales jump or fall off suddenly, the estimate becomes less reliable, because the average behind it lags the change. The honest read is that days of inventory remaining estimates timing from a past average. It does not make the reorder for you, and it does not size the reorder for you. Both of those remain your judgment calls.
Combine days remaining with ABC and sell-through
Days of inventory remaining gets more useful when you read it next to the other inventory reports rather than on its own.
Pair it with ABC product analysis so you can focus your timing attention on the variants that carry the most revenue. A short days-remaining number on an A-category product is a different priority from the same number on a C-category product. ABC analysis is itself a categorisation of past sales, not a forecast, so use it to weight where your attention goes, not as a prediction of where revenue will come from next.
Pair it with the products by sell-through rate report to see how fast stock has actually been moving relative to what you received. A high sell-through alongside a low days-remaining estimate paints a consistent picture; a mismatch is a hint to check inputs or transfers. Again, sell-through is a past-data measurement, not a forecast.
All three are signals informed by what has happened, not statements about what will happen. Used together, they help you focus on the right variants and form a sensible view of timing. They do not make the decision for you, and they do not replace your read of the business.
Where supplier performance fits before reordering
Once days of inventory remaining has helped you see what may run low and roughly when, the next practical step before placing a reorder is to consider how the suppliers behind those products have actually performed. Your purchase order records in Shopify are the natural place to look back from: what you ordered, when it arrived, and how that compared with what you expected.
Keep the comparison qualitative. For a given supplier, ask plain questions. Have past orders arrived close to when they were promised. Have quantities and items matched the order. Have there been recurring problems on specific SKUs. Is this supplier a steady partner for a fast-moving variant, or has reliability been uneven enough that you should plan more buffer with them.
There is no need to invent a scoring system or assign numeric weights to do this well. The point is to combine the timing read from days of inventory remaining with a sober view of who you are actually buying from, so the reorder you place reflects both. Days remaining tells you when stock may get tight. Your supplier judgment tells you how much lead time and buffer that signal really demands.
Limitations
Kijun is not a full Stocky replacement. It does not forecast demand, recommend reorder quantities, provide low-stock alerts, manage inventory transfers, or replace Shopify’s native inventory reports and workflows.
Use kijun to review supplier performance before your next reorder, based on supported supplier and vendor records and purchase orders recorded in kijun. Review suppliers before your next reorder.
This article was drafted with AI assistance and checked against cited sources through kijun’s editorial workflow. Last updated: 2026-05-27.
Stocky and Shopify are trademarks of Shopify Inc. kijun is not affiliated with or endorsed by Shopify.