How to reduce warehouse costs without cutting staff
The biggest warehouse costs are not staffing problems. They are travel, accuracy, inventory, and information problems. This guide identifies the 6 cost levers that produce the biggest savings for Indian manufacturers and distributors — none of which require reducing headcount.
9 min readUpdated June 2026Operations
Where warehouse costs hide
1
Picking travel
50–70% of picking time is walking
Fix: Directed routes + slotting
2
Inventory inaccuracy
Phantom picks, over-orders, stockouts
Fix: Barcode GRN + real-time scan
3
Poor slotting
Fast-movers in wrong bins = extra travel
Fix: Velocity analysis
4
Excess carrying cost
20–30% of inventory value per year
Fix: FSN analysis + reorder points
5
Mispick errors
~$22 per error in rework + re-dispatch
Fix: Dock scan validation
6
Space underutilisation
Average 68% utilisation (WERC)
Fix: Slotting + vertical racking
None of these require cutting staff. All of them require better process and better information.
Where warehouse costs actually come from
Before pulling any cost reduction lever, it helps to understand the full cost map — because warehouse costs have both visible and invisible components, and most cost reduction conversations focus only on the visible ones.
Carrying costs on excess stock (20–30% of inventory value per year — the largest invisible cost for most operations)
Cost of picking errors (rework, re-dispatch, chargebacks, customer credit notes)
Cost of stockouts (emergency orders, expedited freight, lost customer orders)
Cost of inventory inaccuracy (phantom picks, over-ordering, space consumed by ghost stock)
Cost of manual re-entry (staff time entering GRNs and dispatch into Tally or ERP hours later)
The direct costs are what most cost reduction discussions focus on — and staff wages are the largest direct cost, which is why headcount reduction is the first thing people consider. But in most Indian manufacturing and trading warehouses, the indirect costs are larger in total than the direct costs they are trying to cut. A warehouse carrying ₹2 crore in average inventory pays ₹40–60 lakh per year in carrying costs — most of which is invisible in the monthly management accounts.
Cutting staff reduces the most visible cost while leaving the largest costs untouched. The biggest savings in a warehouse come from fixing the invisible costs — and most of them don't require reducing headcount at all.
Why cutting staff is the wrong lever to pull first
In developed markets with high labour costs, headcount reduction is often the most financially impactful warehouse cost lever. In India, the calculation is different.
Three India-specific reasons why headcount reduction is not the right first lever:
Labour cost as a percentage of total cost is lowerIndia's warehouse labour cost per employee is significantly lower than in the US or Europe. Cutting one store man saves ₹18,000–₹35,000 per month in direct wages. The same reduction in picking travel time (by fixing slotting) saves the equivalent of that across a larger team without losing anyone. The savings from fixing process inefficiencies consistently outweigh the savings from headcount reduction at Indian wage levels.
Institutional knowledge walks out with the personIn most Indian manufacturing warehouses, key store men know where everything is — not because the WMS tells them, but because they have worked in the warehouse for 5–10 years. Cutting these people doesn't just reduce headcount — it eliminates the only bin-location system the warehouse has. Before reducing headcount, you need a WMS that captures institutional knowledge in a system. After that, the warehouse is resilient to staff changes. Before that, it is not.
The real cost is not wages — it is wasted timeA store man spending 50–70% of their shift walking between widely spaced bins is not a cost problem. It is a process problem that looks like a cost problem. Fixing the process (directed routes, correct slotting, wave picking) turns the same employee into a 40% more productive one — without paying more or employing fewer.
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India logistics cost context: India's logistics costs represent 13–14% of GDP — more than double the global average of 8%. The National Logistics Policy (2022) targets reducing this to single digits by 2030. For individual businesses, the opportunity is significant: a manufacturer or distributor that reduces internal warehouse costs by 20% contributes to this national target while improving their own competitiveness. The reduction doesn't come from fewer people — it comes from better process.
Cost Lever 01
Fix picking travel
The cost
Travel time accounts for 50–70% of total picking time in most warehouses (Georgia Institute of Technology research). Picking itself accounts for 55% of total warehouse operating costs. This means travel consumes 27–39% of all warehouse operating costs — as wasted motion. The picker is on the payroll for the full shift. Only 30–50% of that shift is producing picks.
The fix
Reducing picking travel does not require automation or capital investment. Three changes, in order of ease:
1
Directed pick routesGenerate pick lists sorted by bin location, not by order. The picker travels the warehouse in the shortest possible sequence. Fast WMS does this automatically for all pick list modes — wave, batch, route-wise. A directed route can reduce travel per pick by 25–40% (industry estimate) without moving any inventory.
2
Slotting optimisationMove fast-moving items to bins closest to dispatch. Prologis research shows velocity-based slotting improves picking efficiency by up to 40%. See Cost Lever 3 for the full slotting methodology.
3
Wave or batch pickingInstead of completing one order per warehouse walk, batch multiple orders into a single pass. The Picker Accuracy Report in Fast WMS shows picks per hour per picker before and after — a measurable benchmark for the travel reduction.
The measurement
Before implementing directed routing or slotting changes, establish the baseline: picks per picker per hour from the Picker Accuracy Report. After changes, measure against the same metric. Travel time reduction should appear as an increase in picks-per-hour without any increase in pace or headcount.
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Manufacturing scenario: An automotive components manufacturer in Pune with 400+ bins across 3 bays was spending 20 minutes locating each raw material. After implementing Fast WMS with directed put-away and pick lists, the same task takes 30 seconds. That 19.5-minute reduction multiplied across 40 picks per shift = 13 hours of productive time recovered per shift — equivalent to 1.5 additional staff members of output from the same team.
Cost Lever 02
Fix inventory accuracy
The cost
Inventory inaccuracy creates costs in multiple places that compound over time:
Phantom picksA pick list directs a picker to a bin that shows 10 units but physically has 0. The picker walks to the bin, finds nothing, returns to the supervisor, the order is delayed while a manual search begins. This is a double cost: the time of the failed pick, and the time of the manual resolution.
Over-orderingWhen stock that is physically present isn't recorded in the system (because GRN hasn't been entered yet), procurement orders more. The new stock arrives and the warehouse is overstocked — paying carrying costs on inventory that wasn't needed.
Stockout costsWhen stock falls below reorder level but the system shows it as adequate (because picks haven't been recorded yet), replenishment is not triggered. The stockout is only discovered when production stops or a customer order cannot be fulfilled.
Year-end surpriseAnnual stocktake reveals a variance that has been accumulating for 12 months. Adjusting it is painful, time-consuming, and provides no information about where it went or when.
The fix
Real-time inventory accuracy — where every physical movement is recorded by barcode scan at the point of action — eliminates all four problems simultaneously. Research consistently shows barcode-based perpetual inventory systems improve accuracy by approximately 35% compared to periodic manual counting. The improvement comes not from better counting but from eliminating the time lag between physical event and system record.
In Fast WMS: every GRN scan posts stock to the system at the moment of receipt. Every put-away confirmation moves stock to the bin at the moment the bin is physically reached. Every pick confirmation removes stock from the bin at the moment of pick. There is no lag. The system always reflects what is physically in the warehouse — within seconds of the last scan.
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The Tally time lag problem: In most Indian warehouses, GRN is done on paper at the dock and entered into Tally the next morning. For those 12–18 hours, received stock exists physically but not in the system. If a pick order arrives for that stock overnight, it shows as unavailable — causing a phantom stockout. With Fast WMS, every GRN scan posts to your ERP immediately. There is no overnight lag. The stock is available in the system within seconds of the GRN confirmation.
Cost Lever 03
Fix slotting
The cost
Most warehouses slot items once — when the warehouse is set up — and never revisit the decision. Demand patterns change. New items are added. Customers shift what they order. But the bin assignments remain from 3 years ago.
The result: fast-moving items are stored in distant bins because they were slow-moving when originally slotted. Slow-moving items occupy prime bins near dispatch because they were fast-moving when originally slotted. Every pick is less efficient than it could be, every day.
The fix — a 4-step process
1
Run the Fast/Slow Moving Stock Report in Fast WMS for the last 90 daysThis shows actual picks per item over the period — the real velocity data for your current demand pattern, not historical assumptions.
2
Rank items by dispatch frequencyCreate three groups: Fast (picked multiple times per week), Slow (picked less than once per week), and Non-moving (zero dispatches in 90 days). This is your current FSN classification.
3
Map your "golden zone" binsIdentify which bins are closest to the dispatch dock and packing area. These are the most valuable locations for frequent picks. Waist-to-shoulder height on the nearest rack row is the ideal zone.
4
Move items to match velocity to locationFast movers go to golden zone bins. Slow movers move to mid-warehouse. Non-movers go to the back — or are reviewed for disposition (return, discount, write-off). Update bin assignments in Fast WMS simultaneously.
Prologis research shows velocity-based slotting can improve picking efficiency by up to 40%. For a warehouse with 10 pickers at 8 hours per day, a 40% efficiency improvement is equivalent to 4 additional pickers' output from the same team — with zero change in headcount.
When to do it
Slotting optimisation should be done at minimum quarterly — because demand patterns change seasonally. A quarterly velocity review in Fast WMS takes one person one day. The travel time saving compounds for the next three months until the next review.
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First slotting review finding: The first time most Indian warehouses run a velocity analysis, they discover that items in prime locations include products that haven't moved in 60–90 days. In one distributor's case, 3 of the 8 bins closest to the dispatch dock held non-moving stock that had been sitting since the previous year. After moving fast-movers to those bins, picks per hour improved by approximately 25% in the first week — with no change in technology, process, or staffing.
Cost Lever 04
Reduce carrying costs on excess stock
The cost
Inventory carrying costs — the total annual expense of holding stock — run 20–30% of average inventory value per year (APQC benchmark data). For a business with ₹1 crore in average inventory, this is ₹20–30 lakh per year in direct holding cost. The largest component is capital opportunity cost — money tied up in inventory that cannot be invested in growth, equipment, or working capital.
The most expensive form of carrying cost is stock that never moves. Dead stock — inventory with zero dispatch in 90+ days — pays 100% of its carrying cost with zero revenue return. It consumes bin space, contributes to insurance premiums, and ties up capital that could be generating returns.
The fix — FSN analysis + action
Fast WMS produces fast-moving and slow-moving stock reports by date range — the basis of FSN (Fast, Slow, Non-moving) classification. Running this monthly, with a defined action for each category:
Fast-moving items
Ensure reorder level is set correctly — prevent stockout of your highest-turnover items. Check that pick list allocation is FIFO — oldest lot dispatched first. Slot to golden zone near dispatch.
Slow-moving items
Review reorder quantity — if you're ordering 1,000 units at a time for an item that moves 100 per month, reduce order quantity. Increase review frequency. Consider whether safety stock is correctly sized for the actual lead time and demand variability.
Non-moving items (90+ days zero dispatch)
This is your priority action list. For each item: Can it be returned to the supplier? Can it be transferred to another location where it moves? Can it be sold at a discount? If none of the above, write it off. Leaving it in the warehouse costs 20–30% of its value per year to hold.
The compounding benefit: reducing excess inventory also reduces space requirements. A warehouse that reduces average inventory by 15% through better reorder point management and FSN-driven disposition may find it can defer or eliminate a planned facility expansion — saving substantially more than the holding cost reduction alone.
Cost Lever 05
Eliminate mispick error costs
The cost
Each picking error costs approximately $22 (roughly ₹1,800–5,500) when accounting for return logistics, restocking labour, replacement dispatch, and customer service time (InSitu Sales, 2026). This is the average — high-value items, perishable goods, or wholesale orders to retail chains carry much higher per-error costs, including chargebacks and penalties.
The aggregate impact: 100 orders per day at a 2% error rate produces 2 mispicks per day. At ₹1,800 minimum cost per error, that is ₹3,600 per day = ₹13.14 lakh per year in avoidable direct cost, before accounting for the customer relationship damage.
An additional consequence: 94% of businesses cover the cost of picking and shipping errors when they are at fault (Fulfillment Advisor, 2025). The mispick cost is not passed to the customer — it is absorbed by the business.
The fix — two scan validations
Mispick costs are eliminated through two scan confirmation points that Fast WMS provides:
Validation 1: Pick confirmation — at the bin
HowPicker scans the item barcode at the bin. Fast WMS compares against the pick list. Wrong item or wrong lot → scan rejected. Picker cannot confirm the pick until the correct item is scanned.
What this catchesWrong item picked from wrong bin. Wrong lot picked when FIFO requires a different lot.
Cost eliminatedThe mispick is caught before the item leaves the bin — no rework, no re-dispatch.
Validation 2: Dock scan validation — at loading
HowEvery item is scanned against the delivery challan before loading onto the truck. Wrong item or wrong quantity → loading is halted. Dispatch cannot be cleared until every scan matches.
What this catchesAny item that reached packing incorrectly. A second layer of validation.
Cost eliminatedThe mispick is caught before the truck leaves — no return freight, no customer credit note.
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The before and after: A steel and pipes trading company in Pune was processing 60–80 orders per day with a handwritten pick list system. Occasional wrong-item dispatches to customers required a credit note and a replacement delivery — adding 1–2 days to resolution and approximately ₹2,000–8,000 per error in combined cost. After implementing Fast WMS with pick confirmation and dock scan: zero wrong-item dispatches since go-live. The scan confirmation doesn't add time to picking — it replaces the mental effort of checking, which is slower and less reliable than a scan.
Cost Lever 06
Improve space utilisation
The cost
The 2025 WERC DC Measures Report benchmarks average warehouse space utilisation at just 68%. This means most warehouses are using barely two-thirds of their available capacity — yet paying 100% of the rent, rates, and utilities for the full footprint. For a warehouse on a ₹8 lakh monthly lease, 32% underutilisation represents approximately ₹2.56 lakh per month in space that is paid for but not productive.
Why warehouses are typically underutilised
Not because there isn't enough inventory — usually the opposite. Specific areas feel congested while others are empty. This happens because:
Uneven slottingFast-moving items in distant bins and slow-movers in prime locations (the slotting problem from Lever 3) creates congestion near dispatch while the back of the warehouse empties.
Non-moving stock occupying premium spaceDead stock that should have been disposed of months ago is sitting in a bin that a fast-moving item should occupy. The space is "full" with stock that generates no revenue.
Inconsistent put-awayWithout directed put-away in a WMS, goods go wherever there is space. This creates fragmented inventory — the same item in 6 different bins, none of them efficiently located. The WMS shows 68% utilisation but the picker walks to 6 locations to collect what should be in 1.
The fix — three no-capital improvements
1
Run the Warehouse Utilisation Report in Fast WMSShows capacity vs used per bin in kg and cubic metres. Identifies both overcrowded bins (overflow risk) and underutilised bins (wasted space).
2
Consolidate fragmented inventoryItems spread across multiple bins should be consolidated to fewer bins in the correct zone for their velocity. This frees up empty bins for new stock or better organisation. Update Fast WMS bin assignments simultaneously.
3
Dispose of non-moving stock firstBefore any racking investment or facility change, clear the non-moving stock identified in Lever 4. In most warehouses, disposing of 90-day non-movers recovers 10–20% of total bin capacity — at zero capital cost.
If space remains genuinely insufficient after slotting optimisation and non-mover disposition, the next step is vertical racking — using building height rather than floor area to increase capacity within the existing footprint. Vertical racking investment is substantially less expensive than additional lease space.
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Space utilisation and the expansion decision: Many Indian businesses sign longer or larger warehouse leases because the current space "feels full." In most cases, the space is not genuinely full — it is poorly organised. A velocity analysis, non-mover disposition, and slotting update typically recover 15–25% of apparent capacity without any additional space. Before committing to a new lease or expansion, run these three steps. The expansion decision looks very different after the inefficiency is removed.
Which cost lever is biggest in your warehouse?
Fast WMS provides the data for every lever in this guide: Picker Accuracy Report (travel and accuracy), Warehouse Utilisation Report (space), Fast/Slow Moving Report (carrying costs), and cycle count (inventory accuracy). A 30-minute demo shows all of them on your actual warehouse data.
The India context: why these levers matter more here
India's logistics costs at 13–14% of GDP are more than double the global average of 8% (World Bank / National Logistics Policy 2022). The gap exists because of fragmented infrastructure, multi-modal inefficiencies, and — crucially — operational inefficiencies within individual warehouses. The National Logistics Policy targets single-digit logistics costs by 2030. For individual businesses, the gap between India's current cost and the global benchmark is not a fixed cost of doing business. It is an opportunity.
Post-GST, the Indian warehouse landscape has already demonstrated what happens when operational efficiency is improved at scale: transport lead times fell by up to 40% as companies consolidated from many small state warehouses to fewer, larger distribution centres. FMCG companies that ran this consolidation report reduced safety inventory needs and improved capital turns directly as a result.
The same logic applies within individual warehouse operations. A manufacturer or distributor that reduces picking travel by 30%, improves inventory accuracy to 98%+, eliminates mispick costs through scan confirmation, and acts on non-moving stock monthly is operating at a fundamentally different cost structure than one that hasn't — with the same number of staff, in the same building.
India's logistics cost is 13–14% of GDP. Global best-in-class is 8%. The difference is not primarily infrastructure — it is operational efficiency within each warehouse in the supply chain. Every business that closes this gap in their own operation contributes to the national target and gains a competitive cost advantage.
The sequence — which lever to pull first
All 6 cost levers work. Not all of them are equally quick to pull or equally impactful in every operation. The recommended sequence prioritises levers that deliver immediate visible improvement with minimal disruption:
Lever
Time to implement
Capital required
Typical impact
Measure with
Lever 3 — Slotting
1–2 weeks
Zero
25–40% picking efficiency gain (Prologis)
Picks per hour — Picker Accuracy Report
Lever 4 — Dispose of non-movers
2–4 weeks
Zero
10–20% bin capacity freed
Non-Moving Stock Report
Lever 1 — Directed pick routes
At WMS implementation
WMS software
25–40% travel time reduction
Picks per hour before/after
Lever 2 — Inventory accuracy
At WMS implementation
WMS + Android scanner
~35% accuracy improvement
Stock Reconciliation Report
Lever 5 — Scan validation
At WMS implementation
WMS + scanner
Near-zero mispick cost
Picker Accuracy Report; zero mispicks dispatched
Lever 6 — Space utilisation
Ongoing — quarterly
Zero (slotting); low (racking)
Close the 68% → 85% utilisation gap
Warehouse Utilisation Report
Levers 1, 2, and 5 all depend on WMS implementation — because they require barcode scan confirmation that a manual system cannot provide. Levers 3, 4, and 6 can begin immediately, before any technology investment, with a velocity analysis and a decision about non-moving stock.
The recommended first week, before any technology: run the velocity analysis (from whatever data is available — dispatch records, Tally ledger), identify the top 20 fastest-moving items, move them to the 20 bins closest to dispatch. Review non-moving stock and make a disposition decision on items over 90 days. Measure picks per hour before and after. This establishes the baseline and demonstrates the impact of process improvement without any capital outlay.
Part of the Warehouse Management GuideA series covering every aspect of warehouse management for Indian businesses.
How can I reduce warehouse costs without cutting staff?
The largest warehouse costs are not staffing problems — they are process and information problems that cause your existing staff to spend time unproductively. Six cost levers produce the most significant reductions without headcount cuts: (1) Reduce picking travel — directed picking routes and wave or route-wise picking reduce travel time, which accounts for 50–70% of picking time. (2) Improve inventory accuracy — inaccurate stock data causes phantom picks, emergency purchase orders, and carrying costs on stock that shouldn't be there. Real-time barcode scanning improves accuracy by approximately 35%. (3) Optimise slotting — fast-moving items near dispatch can improve picking efficiency by up to 40% with no capital investment. (4) Reduce carrying costs on excess inventory — identifying and acting on slow and non-moving stock frees working capital and reduces the 20–30% annual carrying cost burden. (5) Eliminate mispick errors — each mispick costs approximately $22 (roughly ₹1,800–5,500) in rework, re-dispatch, and customer cost. Dock scan validation eliminates dispatching of wrong items. (6) Improve space utilisation — average warehouse utilisation is 68%; most operations can absorb more inventory in the same footprint through better slotting and vertical space use.
What are the biggest warehouse cost drivers?
Warehouse costs break into two categories. Direct costs (visible in accounts): labour wages, lease or depreciation, equipment, utilities, technology, and insurance. Indirect costs (often absorbed into overhead or inventory): carrying costs on excess stock (20–30% of inventory value per year), cost of picking errors (rework, re-dispatch, customer credit), cost of stockouts (emergency orders, lost sales, expedited freight), and cost of inventory inaccuracy (phantom orders, overbuying, space waste). The most impactful indirect cost in most Indian manufacturing and trading warehouses is inventory carrying cost — holding too much of the wrong stock and not enough of the right stock. A business carrying ₹1 crore in average inventory at a 25% carrying cost rate is spending ₹25 lakh per year to hold it.
How does slotting reduce warehouse costs?
Slotting — the decision about where in the warehouse each item is stored — directly controls how far pickers walk. Research from Prologis shows that velocity-based slotting (placing fast-moving items nearest to dispatch) can improve picking efficiency by up to 40%. If 50–70% of picking time is travel (the industry benchmark), and you reduce travel by 40%, you recover 20–28% of total picking time — without automation, without headcount changes, and without infrastructure investment. The only cost is the time to run a velocity analysis (Fast WMS Fast/Slow Moving Report) and physically move inventory to better-positioned bins. Slotting should be reviewed at minimum quarterly, because demand patterns change and the items that move fastest in Q1 may not be the same in Q3.
How much does inventory inaccuracy cost a warehouse?
Inventory inaccuracy costs warehouses in multiple ways that accumulate invisibly. First, phantom stock: items that show as available in the system but are not physically present cause failed picks that require reprocessing — the picker walks to the bin, finds nothing, returns to the WMS, and the order is delayed. Second, over-ordering: when stock that is physically present isn't recorded correctly, procurement orders more than needed — increasing carrying costs. Third, stockouts: when stock runs below reorder level but the system shows it as above, replenishment is not triggered until the physical shortage is discovered. Research shows a 1% improvement in inventory accuracy produces measurable gains in gross margin, working capital, and cash flow. Real-time barcode scanning improves inventory accuracy by approximately 35% compared to periodic manual counting — eliminating the lag between physical events and system records that creates most inaccuracies.
What is the cost of warehouse picking errors?
Each warehouse picking error costs approximately $22 (roughly ₹1,800–5,500 at current exchange rates) when accounting for return shipping, restocking, reshipment, and customer service time (InSitu Sales 2026). At 100 orders per day with a 2% error rate, that is approximately ₹13–40 lakh per year in avoidable mispick costs. For wholesale distributors and manufacturers, the stakes are higher: a single mispicked pallet to a retail chain customer can trigger chargebacks, compliance deductions, and penalties that dwarf the cost of the original order. Barcode scan confirmation at pick — where the wrong item scan is physically rejected before the item leaves the bin — eliminates this cost category almost entirely. This is not a headcount solution; it is a process solution that makes the same number of pickers dramatically more accurate.
How does a WMS reduce warehouse operating costs?
A WMS reduces warehouse operating costs through five mechanisms: (1) Directed picking routes — the pick list shows the optimal path through the warehouse, reducing travel time per pick by 25–40%. (2) Pick confirmation by scan — wrong items rejected at the bin before dispatch, eliminating mispick cost. (3) Real-time inventory accuracy — every scan updates stock balances, preventing phantom picks, over-ordering, and carrying costs on inaccurate stock. (4) Automatic ERP posting — every GRN and dispatch posts to accounts immediately, eliminating manual re-entry labour and time lag. (5) Reorder level alerts — the WMS flags items below reorder point, enabling just-in-time purchasing that reduces safety stock carrying costs. Companies adopting a WMS typically cut labour costs by 30% and improve order accuracy to 99%. For Indian manufacturers and distributors, the most immediate cost saving is the elimination of manual re-entry — GRN entered next morning in Tally, pick lists written by hand, dispatch challan entered separately — all replaced by a single scan that updates every system.
How can I reduce inventory carrying costs in my warehouse?
Reducing inventory carrying costs requires two parallel actions: right-sizing stock levels and identifying and acting on slow and non-moving inventory. Right-sizing: set reorder points based on actual lead times and demand, not on gut feel or historical ordering patterns. Use EOQ (Economic Order Quantity) to calculate optimal order quantities that balance ordering frequency against holding cost. Set minimum and maximum inventory levels in the WMS Item Master so the Reorder Level Dashboard alerts procurement before stockout without ordering excess. Slow and non-moving stock: run the FSN analysis (Fast/Slow/Non-moving) monthly. Non-moving items — stock with zero dispatch in 90+ days — represent pure carrying cost with no return. Each non-moving item consumes bin space, insurance, handling cost, and the opportunity cost of the capital tied up in it. Return to supplier (if possible), discount to sell, or write off. Leaving non-moving stock in the warehouse because 'we might need it' is a choice to pay 20–30% of its value in carrying costs every year it sits.
The data for all 6 cost levers is in Fast WMS
Picker Accuracy Report for travel and mispick costs. Warehouse Utilisation Report for space. Fast/Slow Moving for carrying costs. Stock Reconciliation for accuracy. All standard — no add-ons. A 30-minute demo shows every one of them on your warehouse data.
