The 5 (6) most essential warehouse management reports

What it shows

The Stock Reconciliation Report compares what the WMS says is in stock (system quantity, per item, per bin, per lot) against what a physical count finds is actually present. The difference — the variance — is the accumulated result of every GRN error, picking error, unrecorded transfer, and system entry mistake since the last count.

Why it matters in India

In Indian warehouses without a WMS, the stock reconciliation is done once a year at the annual stocktake — a 2–3 day shutdown that reveals variances that have been accumulating for twelve months. By the time the variance is found, the cause is untraceable. Was it a short delivery in May? A picking error in August? A transfer that was never recorded? The annual reconciliation tells you the number. It cannot tell you why — or where the same error is happening right now.

A WMS-driven reconciliation report changes this completely. Cycle counts happen continuously — one bin group per day or week — and variances appear immediately, while the cause is still recent and traceable.

What the report looks like in Fast WMS

The report shows every line where physical count and system count disagree. Positive variances (more physically than system shows) suggest unrecorded receipts or returns. Negative variances (less physically than system shows) suggest picking errors, unrecorded issues, damage, or theft. Fast WMS generates this report from cycle count data — the adjustment is then manually reviewed and posted (not automatic) to maintain human control over stock changes.

The benchmark

World-class warehouses achieve 97% or higher inventory accuracy (WERC 2025 research). The average is meaningfully lower — most operations that transition from manual record-keeping discover significant variances in their first WMS cycle count, simply because the WMS captures movements that previously went unrecorded.

What it shows

The Picker Accuracy Report tracks, for each individual picker and for the warehouse team as a whole, what percentage of picks were completed correctly — correct item, correct lot, correct quantity — out of all picks attempted.

Store Man B at 96.18% is significantly below team average and benchmark — this is a coaching signal, not a performance review.

Why it matters in India

In most Indian warehouses, picking accuracy is invisible until a customer complains. A wrong item dispatched to a customer triggers a return, a credit note, a re-dispatch, and a customer relationship conversation — all of which cost significantly more than catching the error at the dock.

The Picker Accuracy Report makes accuracy visible at the individual level — before errors reach the customer. A picker at 96% accuracy is generating three to four times more errors than the industry average. That signal appears in the weekly report, not in a customer complaint two weeks later.

The benchmarks

The 2025 WERC DC Measures Report benchmarks average picking accuracy at 99.49% for warehouse operations. Improving from 96% to 99.5% accuracy can reduce returns processing costs by up to 88% — because the cost of a picking error cascades through rework, re-dispatch, and customer relationship cost. Each return costs $15–45 (approximately ₹1,250–₹3,750) to process in a typical operation.

Individual vs team report

Fast WMS produces both. The team report shows the warehouse's overall accuracy — useful for management reviews and customer SLA discussions. The individual report identifies which specific pickers are generating disproportionate errors — useful for targeted coaching, training, and process review. The data is by date range (day, week, month) and by item or order category.

What it shows

The Warehouse Space Utilisation Report shows, for every bin in the warehouse, the current stock vs the defined capacity — expressed as a percentage in both weight (kg) and volume (cubic metres). At the warehouse level, it shows overall utilisation: how much of the total warehouse capacity is currently in use.

The report also shows at the warehouse level: total capacity, total used, overall utilisation percentage. And it produces the Graphical Stock Report — a colour-coded visual grid of the warehouse layout showing which bins are full, available, empty, or in hold status at a glance.

Why it matters

The 2025 WERC DC Measures Report shows the average warehouse space utilisation is just 68%. This means most warehouses are using barely two-thirds of their available space — while simultaneously feeling "full" because specific popular areas are overcrowded and unpopular areas are empty.

The utilisation report surfaces both problems: bins that are overloaded (accuracy risk, damage risk, safety risk) and bins that are empty or underutilised (slotting inefficiency, wasted capacity). The combination drives better slotting decisions — moving fast-moving items to accessible empty space, and moving slow-movers away from premium locations.

What it shows

The Lot Expiry Dashboard shows every lot of stock in the warehouse that has an expiry date — organised by how close each lot is to expiry. Fast WMS uses 9 time bands:

Each band is clickable — drilling down to the specific lots, quantities, bin locations, and supplier details for stock in that time window.

Why 9 bands matter — and why a binary flag doesn't

Most WMS products offer an "expiry alert" — a flag that appears when a lot is within X days of expiry, typically 30 or 60 days. This is binary: either the alert is on or off. It doesn't help procurement answer the questions that actually matter: how much stock is expiring in the next three months? In the next six months? What's the total value of stock expiring within 90 days across all bins?

The 9-band dashboard answers all of these. A cold storage operator looking at ₹14 lakh of stock in the "Next 3 Months" band can take action — promote the items, negotiate a return with the supplier, apply a price reduction — three months before expiry. With a binary flag, they find out 30 days before it's too late.

The enforcement layer

The dashboard is the visibility layer. The enforcement layer is what happens at picking: lots in the "Previous" band (already expired) are automatically excluded from pick lists in Fast WMS. They cannot be scanned and confirmed for dispatch — regardless of what the picker attempts. Near-expiry lots are prioritised in pick lists via FEFO (First Expired First Out) — the system picks the lot closest to expiry first, without the picker needing to check dates.

What it shows

The Fast Moving Stock Report identifies which items are being dispatched at the highest rate over a selected date range — by volume, by value, or by number of transactions. The Slow Moving Stock Report (its counterpart) identifies items with minimal or no dispatch activity over the same period.

Why both reports matter

Fast-moving items drive two actions: reorder (ensure reorder level in Fast WMS triggers a replenishment before stockout) and slotting (fast movers belong in the most accessible bins near dispatch — see Tip 5 of the warehouse management tips guide).

Slow-moving items drive three actions: working capital review (₹2.04 lakh tied up in items that haven't moved in 3–10 months), obsolescence check (will these items move at all, or should they be returned, discounted, or written off), and space reclamation (slow-movers in premium bins should make way for faster-moving items).

The combination most businesses overlook

The most dangerous category in any warehouse is a slow-moving item with an expiry date. It combines two risk factors: capital tied up, and a ticking clock. Running the Slow Moving Stock Report filtered by items that also appear in the "Next 3 Months" or "Next 6 Months" band of the Lot Expiry Dashboard identifies this category precisely. This combination report is the one that should drive urgent procurement and sales team conversations.