Warehouse replenishment is the job of moving stock from bulk or reserve storage into the pick faces that pickers work from, before those pickers need it. When replenishment runs well, a picker finds stock where the system says it is and keeps moving. When it runs badly, the picker finds an empty location, walks back to the racking and the order waits. This guide covers what replenishment is, the methods warehouses use, how to size pick faces, how FIFO and FEFO affect the job, the step-by-step process, and how a warehouse management system (WMS) raises replenishment tasks without anyone watching the shelves.
Replenishment is an old problem, and well-run operations still get caught out by it. Modern Materials Handling’s 2015 piece Replenishment: The next big target observed that although replenishment happens right behind the pick face, it is “painfully divorced from picking processes” in many warehouses. Safety is part of the picture too. The HSE’s logistics guidance includes a warehousing section on the main causes of injury and ill health in storage and warehousing, and replenishment puts forklifts into the same aisles as the people picking.
What warehouse replenishment is
In most warehouses, stock sits in two places. Bulk storage, usually racking or floor stacks, holds full pallets or cases. The pick face is the smaller, more accessible location where pickers collect individual units or case quantities for orders. Replenishment is the move between the two. A pallet comes down from racking, or a case comes out of reserve, and goes into the pick face so the next order can be picked without a detour. Getting stock into reserve in the first place is a separate job, and Clarus’s suggestion de mise en stock rules steer each pallet to a suitable location when it arrives.
Modern Materials Handling’s 2017 guide to replenishment describes the simplest version. A task is created when a forward pick location drops to its minimum, and the quantity moved should fill the location up to its maximum. That threshold-and-top-up pattern is the starting point for most replenishment set-ups, even where the trigger comes from live order data rather than a stock count.
Why replenishment matters for picking speed and accuracy
Replenishment is invisible when it works. It only shows up when it fails, and the failures are predictable. A picker reaches a location, finds it empty, stops, walks back to the racking, finds the pallet, brings it down and carries on. Every one of those trips is time not spent picking. Across a shift the lost time adds up, and it often lands on the orders that were already the most urgent.
Short picks are the second cost. If a pick face runs out part way through an order, the order is shorted, delayed or completed later in pieces. Each outcome creates admin for the customer team and the despatch desk, and it makes the picker’s afternoon harder. Picking routes also depend on replenishment. If you have read our guide to préparation des commandes en entrepôt, you’ll know a route is only as efficient as the stock sitting in each location along it.
Safety is the other reason to get replenishment right. The HSE’s Warehousing and storage: A guide to health and safety (HSG76) names mechanical handling and site transport among its special attention topics, and both are involved each time a pallet moves from racking to a pick face. Lancaster City Council’s warehousing and storage guidance says racking should be inspected regularly, and that where damage affects safety, the racking should be taken out of use until it is repaired. Inspection belongs in the replenishment routine, not only in a periodic check.
Replenishment methods and when to use each
There is no single right method. The best fit depends on how fast each product moves, how many products share a pick face, and whether the team will act on a trigger consistently. The table sets out the common approaches.
| Méthode | What raises the task | Best suited to | Watch for |
|---|---|---|---|
| Min/max | The pick face falls to its minimum, and the task fills it to the maximum | Steady movers on fixed pick faces | A minimum set too low leaves pickers waiting for stock |
| Demand (top-off) | Open orders need more stock than the pick face holds | Fast movers and mixed order profiles | Needs accurate, up-to-date order data |
| Order-volume | Pick demand is checked when pick tasks are created, before stock runs short | Pick faces with uneven demand | Depends on the WMS seeing orders as they arrive |
| Wave-based | Replenishment is batched ahead of each wave of picking | High-volume operations that release orders in waves | Stock can run short between waves |
| Opportunistic | A worker tops up a face when passing it, or when a nearby pallet is put away | Smaller sites with spare labour on the floor | Hard to measure, and the first task dropped on a busy shift |
| Scheduled | Replenishment runs at fixed times through the shift | Predictable, planned volumes | Misses demand that arrives outside the schedule |
Most warehouses combine methods. A fixed min/max rule can cover the slow movers, while demand-driven replenishment handles the fast lines where a static rule would either overfill the face or let it run out.
Min/max replenishment
Min/max is the most familiar method because it is simple to explain to a supervisor. A minimum is set for each pick face. When stock falls to that level, a task brings the face back up to its maximum. MMH’s 2017 guide works through a simple case: a seven-case lane with two cases left triggers a task to move five cases, which fills the lane to its maximum.
The weakness is that min/max reacts to the stock count, not to the orders waiting to be picked. If a large order arrives just after a task is raised, the face may not hold enough to cover it. A sensible starting point is to set the minimum so it covers the demand you expect while a refill is on its way, rather than a comfortable but arbitrary buffer.
Demand and top-off replenishment
Demand replenishment checks what open orders need, rather than waiting for the face to cross a threshold. The pick face is topped up when the orders show it will run short. This suits fast movers and the mixed order profiles most 3PL and ecommerce sites run, because the stock that gets moved is the stock that is needed.
It is also more sensitive to the quality of order data. If orders reach the WMS late, or only after picking has started, the replenishment task arrives late too.
Wave-based and scheduled replenishment
Wave-based replenishment groups the moves ahead of each batch of picking. It works well where orders are released in waves, because the team can estimate what each wave will draw from each pick face. The risk is the gap between waves, when a face can run dry with no one scheduled to notice. Scheduled replenishment works the same way on a clock, with fixed runs sized for the day’s expected volume. It is easy to plan and easy to explain, but it misses demand that arrives outside the timetable.
Opportunistic replenishment
Opportunistic replenishment asks a worker to top up a face when they pass it, or when a pallet being put away happens to sit close to a pick face that needs stock. It costs little to set up, and on a small site with spare labour it can work. The trouble is control. Without a clear trigger you cannot tell how often faces run empty, and the task is the first to be dropped when the floor gets busy.
Sizing minimums, maximums and pick faces
Pick face size and replenishment frequency are linked. A small face that is replenished many times a day ties up labour on moves. A large face holds stock that sits and ages, and takes up space that faster lines could use. MMH’s 2017 guide offers practical rules of thumb. It recommends keeping 10% to 15% of forward slots available, on the basis that productivity suffers once the forward area passes 85% capacity. It also suggests that a face replenished ten times a week may be better sized for one or two replenishments a week on average.
Those are guides, not laws, and the right numbers depend on your order profile and racking. A practical method is to take a sample of recent picks for each product, work out how much the face needs to hold between refills, and set the maximum so a refill brings the face to that level without overfilling it. Then check the results. If a face runs out every shift, the minimum is too low or the refill is too slow. If it sits half empty for days, the face is oversized.
Fixed pick faces that always hold a pallet, whether or not there are orders for it, are a common source of waste. They tie up a location that could be serving the orders that matter. Demand-led faces, filled as the orders require, make better use of the same space.
FIFO, FEFO and replenishment
Which stock moves into the pick face matters as much as when it moves. First in, first out (FIFO) means the oldest stock goes forward first. First expiry, first out (FEFO) means the stock with the earliest best-before or sell-by date goes first. Both rules depend on the replenishment task selecting the right source pallet. If it doesn’t, the picker ends up working through stock that should already have left the building.
Bulk storage is where those rules tend to break. The oldest pallet in a floor stack is usually at the back, and it is also the hardest to reach. If you rely on sell-by dates, avoid bulk stacking and keep each pallet easy to reach. For the wider principles, see our guide to rotation des stocks.
In Clarus, the pick rule decides which pallet moves forward. FIFO selects the oldest received stock, based on the creation date of the stock record, down to the millisecond. Sell by date selects the pallet with the shortest remaining shelf life within the product’s configured range. Where a pick needs stock that meets a specific shelf-life requirement and the pick face cannot supply it, the pick is held and released once qualifying stock has been moved in. Clarus’s rotation rules et suivi des dates de péremption control this.
The replenishment process, step by step
A reliable process makes replenishment predictable. The steps below apply whether the work is done by hand, on paper or on a handheld device.
- Set a trigger for each pick face, either a minimum level or a demand rule.
- Raise a replenishment task when the trigger is reached, or when open orders need more stock than the face holds.
- Select the source stock using your rotation rule, FIFO, FEFO or sell-by date, and check it meets any shelf-life requirement.
- Send the task to the person who will move it, with the source location, destination and quantity on screen.
- The operator moves the stock, scanning the source location, the pallet and the destination, so the system knows what has moved.
- Confirm the quantity and update both locations, so the records match what is physically there.
- Release any picks that were waiting for the stock, and record exceptions such as damage or a short pallet for follow-up.
Common replenishment problems and how to fix them
- Pickers reach empty faces at peak. The minimum is too low for peak rates, or the task is raised too late. Raise the minimum for peak lines, or move the trigger earlier.
- Replenishment and picking compete for the same equipment. If one operator and one truck are doing both, one slows the other. Separate replenishment from picking where volume justifies it, or give replenishment its own queue.
- Duplicate or stale tasks. Several picks raised at once can trigger several refills for the same face. A WMS that accounts for replenishments already in progress avoids this. Without one, supervisors end up cancelling tasks by hand.
- Wrong unit of measure. If pickers work in units but stock is held in cases, a task that counts cases can leave the face short or overfull. Set the conversion once, and check it whenever a product changes pack size.
- Stock that can’t be reached. Bulk stacks and blocked racking make the right pallet hard to get to. Keep fast-moving and date-controlled stock accessible, and check that racking is in a safe, usable state.
How a WMS triggers replenishment tasks
On paper, replenishment is a rule that someone has to remember to apply. In a WMS it runs every time an order is processed. Clarus checks the pick demand for each pick face at the moment pick tasks are created. If those picks would take the face below its minimum, a replenishment task is created straight away, without waiting for stock to cross the threshold. The system also counts replenishments already in progress, so it does not raise a second task for the same face. The replenishment feature is built around that check.
Mathew Buttar, who works on Clarus implementations and spent years running warehouses before that, points out that replenishment in the system is a standalone function. It can be driven by order volume, or by shelf life, or by both. A warehouse does not need to be connected to a materials planning system to run pick faces and replenishment.
Each pick face has its own minimum trigger and maximum quantity. Top-ups can move exact quantities, or whole storage units. If a face is set to full storage units only, a maximum of 100 units with 60-unit storage units brings in two units, or 120 in total, so the face ends up above its maximum. That is a deliberate trade-off between pallet handling and exact fill. The pickface automation settings control this for each location.
Replenishment tasks are completed on the handheld devices operatives already use for cueillette. If the pick tasks behind a replenishment are cancelled, the linked replenishment is cancelled too. Where a pick has to wait for stock that meets a shelf-life rule, the pick shows as on hold with its reason, and it releases automatically when qualifying stock arrives.
There are limits worth knowing. Continuous replenishment works from the product’s default shelf-life range, so a customer with tighter date rules may still see picks held. That is the case where a separate demand pick face is needed. Demand replenishment moves a full pallet at a time into an empty location. The minimum and maximum have to be set sensibly, and a WMS cannot fix a trigger set at the wrong level. If you are new to WMS software in general, our explainer on what a WMS is covers the basics.
Key performance indicators for replenishment
You cannot improve replenishment without measuring it. Four measures give the clearest picture.
- Replenishment tasks per hour, and labour per task. Shows how much effort the process takes, and whether a rise in tasks reflects more orders or inefficient triggers.
- Short picks caused by empty pick faces. Ties the process directly to the customer outcome.
- Pick face stockouts, by frequency and duration. How often each face runs empty, and for how long, is more useful than a single average.
- Replenishment cycle time. The time from task creation to the pick face being updated. A long cycle time usually means the trigger is firing too late.
Stockout and cycle time figures only mean something if the stock records are right. Regular counts keep the numbers honest, and our guide on how to do a stocktake covers the method. For the software side, see our page on stock control software.
Replenishment and supplier replenishment are different jobs
The word replenishment also covers buying stock from suppliers, and the two are often confused. Supplier replenishment, usually driven by reorder points and forecasts, decides when to buy more of a product and how much. Warehouse replenishment is internal. It decides when to move stock already in the building from reserve into the pick face. A reorder point can tell you the business needs more stock overall. Min/max tells the floor which pallet needs to move next.
Many operations run both, and the two need to agree. If pick faces are replenished from a reserve that the purchasing team believes is empty, the process fails in a way that is hard to see from the floor. Accurate stock records across both are what make them work together. For wider reading on warehouse operations, SCDigest covers warehousing and distribution regularly.
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If you’re evaluating your options and want to see how a purpose-built WMS handles replenishment in practice, Clarus is worth a conversation. We work with 3PLs and distributors across the UK to implement warehouse management software that fits the way you operate, not the other way around.
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