Some items sit in inventory for several weeks, even several months, without selling. When a product no longer matches its usual sales rate, it can start tying up cash unnecessarily.
Dead stock is therefore an item still in inventory whose sales have dropped to zero or become abnormally low over a significant period. That period can't be the same for every product: it depends in particular on how often the item usually sells and on its seasonality.
The problem isn't just the space taken up. Stock that no longer sells ties up money that could be used elsewhere in the business.
Dead stock, slow turnover, overstock: what's the difference?
These three notions are related, but they don't describe exactly the same situation.
Dead stock
An item whose sales have dropped to zero or very low for an abnormal length of time given its usual behavior.
Slow turnover
A product that renews slowly: it may keep selling, but at a low rate compared with the stock held.
Overstock
A quantity of stock durably above foreseeable needs. A product can be overstocked while still recording regular sales.
A product can therefore be overstocked without being dead stock, or become dead stock when only a few units remain. These situations can overlap, but they aren't analyzed in the same way.
How do you define dead stock?
There is no universal length of time after which an item becomes dead stock. A product that sells several times a day may become a concern after a few weeks without a sale, whereas a seasonal item can go several months without movement without that being abnormal. Several criteria therefore need to be combined:
- Last sale: how long has the item gone without a sale?
- Usual sales frequency: did it sell regularly before, or has its rate always been low?
- Quantity in stock: how many units remain available?
- Tied-up value: what is the value of the units still held?
- Turnover: is the product's renewal rate slowing down?
- Seasonality: does the lack of sales simply match a normal slow period?
A filter such as “no sales in 60 days” is therefore a good way to surface items to review, but it isn't enough on its own to define dead stock. The relevant threshold depends on the product and its usual behavior.
Why track dead stock?
Imagine 100 items, each representing €200 of goods that almost never sell. That adds up to:
€20,000 of tied-up inventory.
Even if each item seems minor on its own, together they can weigh heavily on cash flow. Dead stock can also lead to other consequences:
- needless use of storage space;
- aging or obsolescence of products;
- risk of write-downs;
- more and more discounts needed to clear items;
- continued orders for products that no longer match demand.
Identifying these items therefore restores visibility over a part of your inventory that can easily go unnoticed.
How do you calculate the tied-up value?
For a simple operational analysis, you can multiply the remaining quantity by the product's unit cost. For example:
Estimated tied-up value = quantity in stock × unit cost
An item with 100 units left, bought at €20, thus represents about €2,000 of tied-up value. This estimate is mainly useful for ranking which items to deal with. It shouldn't be confused with the accounting valuation of inventory, which depends on the methods the company uses.
A practical method to identify dead stock
Not all dead stock is equally urgent. A simple method is to proceed in several steps:
- Spot items with no recent salesStart by searching for products that have recorded no sales over a given length of time. For example, no sales in 60 days. This length of time is a starting filter and should be adapted to the business.
- Compare with the product's usual rateA lack of sales doesn't mean the same thing for a product sold daily and for an item sold only a few times a year. The period without sales therefore needs to be put in the context of the item's usual behavior.
- Check the remaining quantityTwo products with no sales for the same length of time don't necessarily pose the same issue. An item with 2 units left is generally less worrying than another with 150 units still filling the stockroom.
- Estimate the tied-up valueQuantity alone isn't enough either. 150 low-cost items may tie up less cash than a dozen high-value products. Combining quantity and value therefore helps you rank priorities better.
- Check seasonalityBefore treating an item as truly dead stock, check that the lack of sales isn't simply part of its normal cycle. A seasonal product can go several months without a sale before demand naturally returns.
Prioritize rather than treat every product the same way
Once the items are identified, the goal isn't necessarily to act on each of them immediately. It is more useful to rank them.
An item with no sales for three months and two units left may be a very minor issue. Conversely, a product with no sales for two months and 150 units still available may tie up a significant amount. Priorities can therefore be set according to:
- time without a sale;
- remaining quantity;
- tied-up value;
- past turnover;
- available margin;
- whether or not the product is seasonal.
This ranking lets you focus actions on the items that truly affect inventory and cash flow.
What actions can you take on dead stock?
Once items are identified and prioritized, several solutions are possible.
Reduce or stop restocking
This is often the first step to take. It would be counterproductive to keep ordering an item whose current stock already isn't selling through.
Improve its display
A product sometimes sells poorly simply because it lacks visibility. Changing its location, improving its presentation or placing it near complementary products can let you test its potential before applying a discount.
Offer a promotion or a targeted discount
When the margin allows, a markdown can speed up clearing the stock. The aim isn't necessarily to apply the same discount to all dead stock: the remaining quantity, the margin and the age of the stock can justify different treatment.
Transfer the stock
In a network of several stores, a product that is dead stock in one location may well keep selling in another. Before cutting its price, it can therefore be worth considering a transfer to a point of sale where demand still exists.
Clear it out
When the item no longer has enough sales potential, a clearance can recover cash and free up space.
The choice therefore depends less on the “dead stock” label than on the real situation of each item. These actions can then be managed from Gillia's inventory management.
The multi-location dimension
In a business with several points of sale, the analysis should ideally be done by location before being consolidated at network level. A product may no longer sell in one store while keeping good turnover in another. This can be explained, among other things, by differences in customers, product range, location or seasonality.
Before launching a discount or a clearance, it is therefore worth checking whether part of the stock can be reallocated to a location where demand remains sufficient. This approach sometimes lets you sell the product at full price rather than immediately cutting your margin.
What AI can bring
Identifying dead stock manually becomes tedious when the catalog holds hundreds or thousands of items. An AI agent connected to the store's data can help with several steps.
Detection
Search for the items that match the defined criteria.
Analysis
Cross-reference their sales history, their stock and other available data.
Prioritization
Bring out the items representing the biggest stakes.
Action proposal
Prepare an action suited to the situation.
Execution or approval
Depending on the tools available and the rules set for the operation concerned.
The merchant can ask, for example:
“Which items have recorded no sales in 60 days, and how much do they represent in stock?”
Then refine:
“Of those, which still have more than €1,000 of tied-up stock?”
Once the items are identified:
“Set up a promotion on the dead stock where the margin allows it.”
The benefit is being able to go from detection to analysis to action without manually rebuilding several filters or exporting different tables.
Preventing dead stock from building up again
Dealing with products that are already dead stock solves the existing problem. But the longer-term goal is to detect the signs of a slowdown early enough.
A gradual drop in inventory turnover, rising coverage or an unusual period without sales can signal that an item is starting to lose pace. Sales analysis puts these changes in context. An automated task can also regularly monitor certain criteria so you don't have to redo the same search by hand every week.
The goal isn't just to clear out stock that no longer sells, but to identify early enough the items that are starting to slip.
How can Gillia help?
Gillia lets you query the store's available data directly in natural language. The merchant can search for their dead stock, compare its stock, sales history and value, then dig into the items that really need action. The agent can then prepare certain operations compatible with the available functions, for example a promotion on a selection of products.
This approach illustrates how an AI agent for retail works: using the business's data to understand a situation, then making the corresponding action easier — the principle of an AI agent for retail. To put this analysis in the context of the whole supply cycle, also see our guide to in-store inventory management. Among Gillia's use cases, you can also find out how to prepare sales from dead stock or find out the value of your inventory.