Inventory Accuracy – Making System Stock Match Physical Reality, Every Time

This topic is part of the SG Systems Global regulatory & operations glossary.

Updated October 2025 • Warehousing & Materials Control • Traceability / Compliance • See also: Goods Receipt, Bin / Location Management, Cycle Counting, Barcode Validation

Inventory accuracy is the degree to which recorded stock in your system of record (ERP/WMS/MES) equals the physical stock on the floor—by item, lot/serial, unit of measure, location, and status. It underpins planning, capacity, cash, and compliance. For regulated industries, accuracy is not merely financial housekeeping; it is a prerequisite for lot-level genealogy, label correctness, FEFO/FIFO execution, expiry controls, and release decisions. Inaccurate records cascade into missed picks, rework, line stoppages, overproduction, service failures, and audit findings. Achieving sustainable accuracy is less about annual stocktakes and more about error-proofed, real-time transaction capture across receiving, put-away, picking, production consumption, backflush, labeling, transfers, adjustments, and shipping—each bound to identity, timestamp, location, lot/serial, and audit trail.

“Inventory doesn’t go missing; it goes unrecorded. If a physical move occurs without a digital move, accuracy is already broken.”

1) What It Is

Inventory accuracy spans five dimensions: identity (the correct SKU/GTIN and description), quantity (count or weight in the correct unit of measure), time (effective dating for receipts, consumption, and adjustments), place (the correct bin/location/zone), and status (quarantine, released, blocked, expired). In traceability-driven sectors, a sixth dimension matters: provenance—the linked lot/serial, supplier batch, and process steps that produced the on-hand item (see Batch Genealogy and EPCIS). Accuracy is the alignment of these dimensions between the warehouse floor and your digital truth. Many organizations measure it as a percentage match during cycle counts; mature teams supplement with first-pass yield of transactions and pick success rate as earlier warning signals.

2) Why It Fails (and How to Design It Out)

Uncaptured micro-movements. Unlogged bin-to-bin moves, kitted pre-staging, and temporary “parking” are classic accuracy killers. The fix is scan-to-move with enforced location verification, plus Dual Verification for high-risk transfers. Label drift. Reprinted or duplicated labels without reconciliation create phantom stock. Prevent with approved templates, GS1/GTIN-based barcodes, and scan-back at print/apply. Receiving shortcuts. Bypassing Goods Receipt detail (wrong UoM, missed lots/expiries) poisons data at the source; use Dock-to-Stock with quality-gated put-away and Component Release. Consumption mismatch. Hand-entered backflush or manual decrements diverge from reality; integrate scales and production signals and tie consumption to eBMR steps. Status leakage. Picking from quarantine or expired stock occurs when WMS status is wrong or ignored; enforce Hold & Release and FEFO logic in the picker’s handheld.

Unit-of-measure (UoM) inconsistencies. Receiving in kilograms, consuming in pounds, and counting in eaches will erode trust quickly. Standardize UoM per item, convert at the transaction layer, and capture tare for variable-weight goods (see Gravimetric Weighing). Inadequate location governance. Overloaded bins, ambiguous staging zones, and ad-hoc overflow destroy “place” accuracy. Implement Bin / Location Management with capacity rules, zoning (ambient/chilled/allergen/clean vs. not), and directed put-away. Paper islands. Paper pick tickets and tally sheets delay or replace system postings; swap for handheld workflows with immediate confirmation and audit trails. Unchecked adjustments. “Fix it in the system” adjustments mask root causes; require reason codes, photos, and route variances to Deviation / NC and, if systemic, CAPA under Change Control.

3) Controls That Create Accuracy (End to End)

Quality-enforced receiving. At inbound, capture supplier, PO line, item/GTIN, lot/serial, UoM, quantity, expiry/retest, and attachments like CoA. Apply license-plate labels (pallet IDs) and quarantine status until Component Release or test results post. This is the source of truth for Batch-to-Bin Traceability.

Directed put-away and slotting. Use rules based on item families, temperature/allergen zones, turnover (ABC), and capacity. Enforce scans at the destination bin and prevent “unknown” locations. Pair with Directed Picking so put-away logic and pick paths are consistent.

Label and data integrity. Bind labels to approved templates; encode GTIN, lot/serial, expiry, UoM, and SSCC where needed. Require scan-back after print/apply to reconcile serial ranges and prevent clones (see Data Integrity and ALCOA+).

Real-time consumption and production posting. Connect scales, counters, and PLCs to capture material movements as they occur within eBMR steps; enforce tolerances (SPC control limits) and require scans for lot selection. Backflush only where actuals are reliably modeled; otherwise, transact at start/complete with device data.

Expiry and status controls. Enforce FEFO reservations, block expired or on-hold lots at pick-time, and surface shelf-life controls in handhelds. For high-risk allergens, maintain segregated locations and force scans to prove zoning (Allergen Segregation Control).

Cycle counting by risk. Replace annual wall-to-wall counts with perpetual cycle counting—prioritize A items, fast movers, and problem bins; inject triggered counts after variances, location changes, or pick failures. Require reason codes and route patterns to CAPA if repeat behavior emerges.

Shipping and reconciliation. Scan-verify picks to the shipment license plate; reconcile WMS, carrier, and labeling events. Post ASN/EPCIS events where partners require visibility, preserving the chain of custody across the network.

4) Metrics That Matter

• Inventory accuracy % by item and location (count variance within threshold).
• Pick success rate (first-pass, no substitutions) and order OTIF.
• Cycle count hit rate and variance cost (before/after CAPA).
• Transaction latency (seconds from physical move to posted move).
• Status integrity (blocked/expired picks prevented; on-hold picks attempted).
• Label reconciliation (unmatched/reprint exceptions with reasons).

5) Governance, Records & Compliance

Because inventory accuracy feeds release decisions and traceability, its records must be complete, attributable, and reviewable. Handheld transactions should capture user ID, timestamp, device, pre/post values, and location with a secure audit trail. Where electronic records support GMP or food safety outcomes, 21 CFR Part 11 and EU Annex 11 expectations apply—unique identities, role-based access, e-signatures for adjustments, validated integrations, and backup/restore within your CSV/GAMP 5 framework. Inventory changes that affect released product must be reflected in genealogy and, for devices, the DHR. Persistent variance patterns merit CAPA with effectiveness checks and, where process or master data is implicated, Change Control under documented Document Control.

6) How This Fits with V5

V5 by SG Systems Global turns inventory accuracy into an operational default. In V5 WMS, Goods Receipt captures supplier, lots, expiries, UoM, and attachments in one guided flow, applying pallet license plates and quarantine status until Component Release. Directed picking and location rules prevent “place” errors; barcode validation assures item/lot/label correctness; and FEFO/FIFO enforcement blocks risky choices at the handheld. In V5 MES, consumption and backflush are bound to eBMR steps with device-captured weights, tolerances, and Dual Verification for overrides. Adjustments require reason codes and can auto-open Deviation / NC in V5 QMS; systemic issues escalate to CAPA and trigger master data changes under Change Control. Across modules, identity, e-signatures, and secure audit trails support Data Integrity, while analytics expose variance hotspots by user, item, and bin, driving continuous improvement and faster batch release.

7) FAQ

Q1. What accuracy target is realistic?
World-class operations sustain 98–99.8% by line-item/location with strict transaction discipline and perpetual cycle counts. Targets should vary by item criticality and risk.

Q2. Do I still need annual stocktakes if we cycle count?
Many auditors accept risk-based cycle counting in lieu of full counts if the program is documented, statistically sound, and results are trended with corrective action.

Q3. How do FEFO/FIFO relate to accuracy?
They rely on correct lot/expiry and location data; enforcing FEFO/FIFO at pick-time both requires and reinforces accuracy by blocking wrong-lot picks.

Q4. Our biggest issue is wrong UoM. What’s the fix?
Standardize UoM per SKU, convert at the edge (handheld), capture tare for variable-weight items, and disallow free-text UoM at receiving and backflush.

Q5. Are manual adjustments bad?
They’re necessary but must be scarce, reason-coded, and investigated. Patterns should trigger CAPA and potential process or layout changes.

Q6. What about multi-site networks?
Use standardized label data (GTIN, lot/expiry), common EPCIS event models for shipments/receipts, and harmonized bin and status taxonomies to avoid translation errors.

Related Reading
• Warehousing & Movement: Goods Receipt | Bin / Location Management | Dock-to-Stock | Directed Picking | Dynamic Lot Allocation
• Traceability & Labels: GS1 / GTIN | EPCIS | Barcode Validation | Batch-to-Bin Traceability
• Controls & Compliance: FEFO | FIFO | Expiration / Shelf-Life Control | Hold & Release | Audit Trail (GxP)
• Quality & Records: eBMR | Deviation / NC | CAPA | Change Control | Document Control