Inventory Management Software Development

Stock levels updated the moment goods are received, picked, transferred, or adjusted, not in a nightly batch, not manually. Every stock movement creates an auditable record: timestamp, quantity, location, reference document (PO number, sales order number, transfer ID), and the user or automated process that performed the action.

Movement types tracked: goods receipt (PO-based and unplanned receipt); sales order pick and despatch; stock transfer (warehouse-to-warehouse, bin-to-bin, location-to-quarantine); stock adjustment (write-off, write-on, quantity correction); return processing (customer return, supplier return); and production consumption and yield (for manufacturers tracking work-in-progress). Each movement type has its own permission controls, a warehouse operative can pick and receive, but cannot process a write-off above a configurable value without supervisor approval.

Database architecture for real-time accuracy: stock levels maintained as a materialised balance using double-entry transaction accounting, every stock movement is a debit to one location and a credit to another, with a balance view derived from the transaction log. This design means the current balance is always reconstructable from the audit trail, and point-in-time historical balances are queryable without storing snapshots. Optimistic locking prevents concurrent pick operations from over-allocating the same inventory units when two orders are picked simultaneously.

Multi-location view: a single dashboard showing current stock for every SKU across all locations, with configurable grouping (by warehouse, by zone, by bin level). Stock available for sale calculated as on-hand minus allocated minus quarantine, updated in real time. The "what does the system say vs. what's actually on the shelf" reconciliation problem is eliminated when every physical movement is captured at the point it happens, via barcode scan, RFID event, or system action, not entered later from a paper record.

Purchase order-based receiving that matches incoming goods against the expected PO line items and flags discrepancies before they enter the live stock balance. Short deliveries (received less than ordered), over-deliveries (received more than ordered, the system captures the overage and routes it for approval before accepting into available stock), and unexpected items (not on the PO, quarantined pending investigation) are all handled with distinct workflows rather than silently accepted.

Receipt workflow for barcode-scanned goods-in: warehouse operative scans the incoming item barcode or SSCC label; the system displays the matched PO line (expected quantity, unit cost, supplier), the operative enters or scans the received quantity, the system validates against PO tolerance rules (typically ±2% for quantity, ±5% for catch-weight items), and the line is closed. For lot-tracked products, lot number and expiry date are captured at receipt, scanned from the supplier label if GS1-128 or GS1-DataMatrix format is used, or entered manually if the supplier doesn't label in a machine-readable format.

RFID receiving: for operations using RFID-tagged goods (retail apparel, pharmaceutical case-packs), a fixed RFID portal at the receiving dock reads all tags in the incoming shipment simultaneously, matches against ASN (Advance Shipment Notice), and receives the entire shipment in seconds. Discrepancies between the ASN and the RFID read surface immediately for investigation before the goods are moved to the put-away queue.

Quality hold workflow: configurable QC steps for incoming goods (temperature-sensitive products, first-article inspection for new suppliers, goods-in inspection for returned stock). Items that fail QC are moved from quarantine to rejected status with the failure reason recorded; a supplier returns process creates a return shipment and updates the original PO with the rejected quantity. Supplier performance metrics: fill rate (lines received in full / lines ordered), on-time rate (receipt date vs promised delivery date), and lead time variance (actual vs standard lead time) tracked per supplier and surfaced on the purchasing dashboard for commercial review.

Reorder point triggers calculated from true available stock, on-hand minus allocated minus in quality hold, plus pending PO quantity, so the reorder fires based on stock the business can actually use, not the gross on-hand figure. A reorder point of 100 units means "order more when true available stock falls below 100", not "order more when the shelf count falls below 100 regardless of outstanding orders."

Reorder point calculation methodology: configurable per SKU with three approaches. Static: buyer-defined minimum stock level reviewed periodically. Dynamic (demand-based): calculated as average daily demand multiplied by supplier lead time in days, plus safety stock calculated as Z-score multiplied by lead time demand standard deviation (Z-score of 1.65 for 95% service level, 1.96 for 97.5%). This formula is auto-recalculated weekly using the trailing 13-week demand history, so reorder points stay calibrated to seasonal demand without manual updates.

Automated purchase requisition generation: when any SKU's true available stock falls below its reorder point, the system generates a draft purchase requisition for the configured supplier at the calculated reorder quantity (economic order quantity or a buyer-defined fixed quantity). The requisition is routed to the buyer's approval queue with the supporting data (current stock, daily demand rate, lead time, recommended order quantity, supplier lead time) so the buyer can approve or adjust rather than creating the order from scratch. Approved requisitions convert to POs and transmit to the supplier via the configured integration method (email, EDI 850, or supplier portal API).

Safety stock recalculation: lead time variance captured per supplier per SKU from historical PO receipt data (confirmed delivery date vs promised delivery date); demand variability calculated from week-over-week consumption variance. SKUs with high demand variability or unreliable suppliers receive higher safety stock buffers automatically, removing the reliance on a buyer to manually adjust safety stock levels after a stockout incident.

Lot and batch tracking with complete forward and backward traceability, from supplier batch to specific customer order on the forward trace, and from a customer complaint back to the supplier delivery lot on the backward trace. The full chain of custody is a compliance requirement in food, pharmaceutical, and medical device sectors, and a quality management tool in electronics and chemicals.

Lot record structure: lot_number, supplier_id, receipt_date, expiry_date, quantity_received, current_quantity_per_location, certificate_of_analysis (linked document), and temperature log reference (for cold chain products). Lot records created automatically at goods receipt when a lot number is scanned or entered; subsequent movements (pick, transfer, adjustment) record the lot number used so the chain of custody is continuous.

FEFO picking enforcement: for products with expiry dates, the pick list generation algorithm selects the lot with the earliest expiry date first (First Expiry First Out). The warehouse operative's scan confirms they're picking from the correct lot; if they scan a different lot, the system alerts and requires override approval. FEFO is enforced at the software layer, not relied upon as a manual process, the picking guidance shows the operator which bin to go to and which lot to pick from, in the order that clears expiry risk first.

Serial number traceability: serial numbers assigned at receipt (for serialised goods purchased from suppliers) or at production (for serialised finished goods). Each serial number records its complete movement history and its current location. For maintenance and repair operations, serial numbers link to the service history record for the unit. Device-level recall: a specific serial number complaint traces back to the supplier delivery and forward to the current location or the customer who received it, in seconds, not days of spreadsheet investigation.

Lot recall simulation: a recall test (or actual recall) queries all locations and all customer orders containing units from a specific lot within seconds. The recall report shows current inventory quantity across all locations (for immediate quarantine), all sales orders shipped from the lot (for customer notification), and the total affected quantity. Required for BRC, FSSC 22000, ISO 13485, and FDA 21 CFR Part 11 compliance programmes.

iOS and Android warehouse app built in React Native for a single codebase that runs on both platforms, supporting the full range of warehouse operations from a mobile device with the built-in camera as the primary barcode scanner. For operations with high scan volumes (>500 picks/hour), the app pairs via Bluetooth with Zebra RS5100 Ring Scanners or Honeywell Voyager 1450g wireless scanners, which provide faster scan rates and reduce operative fatigue.

Barcode and QR support: 1D barcodes (Code 128, Code 39, EAN-13, UPC-A) for standard retail and warehouse SKU labels; 2D barcodes (QR Code, Data Matrix, PDF417) for GS1-128 labels with lot and expiry encoding; and RFID reading via Zebra FX9600 fixed reader integration (for dock and bay-level RFID counting, not per-item handheld scanning). Camera-based scanning using the device's rear camera with ML Kit Barcode Scanning API or ZXing, configured for the label formats in your warehouse.

Guided pick workflow: pick list generated in bin-sequence order (walking the warehouse in one direction to minimise travel distance); operative sees the bin location, the item description, the lot number to pick from (FEFO-sorted), and the quantity required; scan confirms the correct item and lot; system confirms the pick and advances to the next line. Substitution logic: if the expected lot is empty, the system surfaces the next available lot with override approval. Pick completion triggers sales order despatch update and reduces the inventory balance in real time.

Cycle count management: configurable count cycle (A-B-C classification: A items counted weekly, B monthly, C quarterly). Count task shows the bin location and item description but not the system quantity (blind count). After scanning and entering the physical count, the variance is calculated and displayed. Variances above a configurable threshold (e.g., >5% or >£500 at cost) require supervisor approval before posting to the stock balance. Count history stored per bin and per SKU for shrinkage analysis.

Offline mode: SQLite local database on the device stores pending transactions when network connectivity drops. Transactions queue locally with UUID identifiers for deduplication; when connectivity is restored, the sync pushes queued transactions to the server in chronological order. Conflict resolution handles the case where a stock movement on the server (from another user) and a queued offline transaction both affect the same lot quantity.

Stock valuation reports using FIFO or weighted average cost method (configurable per product category), reconcilable to the balance sheet stock account for period-end close. Valuation by location, category, supplier, and date range for finance team reporting; variance analysis comparing opening balance + receipts - despatches - adjustments to closing balance to reconcile movements to financial postings.

Inventory performance metrics: inventory turnover ratio (cost of goods sold / average inventory value, calculated monthly and trended over 12 months); days inventory outstanding (average inventory / daily COGS); stock-to-sales ratio. These metrics identify slow-moving and fast-moving SKUs before they become carrying cost problems or stockout incidents. The slowest-moving 20% of SKUs by inventory value and the fastest-moving 20% by turnover are surfaced on the purchasing dashboard as weekly action items.

Demand forecasting at weekly granularity: trailing 13-week weighted moving average consumption per SKU (with configurable seasonal adjustment factors for businesses with predictable seasonal patterns). Forecast accuracy measured as MAPE (mean absolute percentage error) per SKU weekly. SKUs where forecast error consistently exceeds 25% are flagged for manual review of demand patterns (promotional activity, product lifecycle changes).

ABC classification: automated weekly reclassification of SKUs by annual consumption value (A items = top 80% of value, B items = next 15%, C items = bottom 5%). ABC class drives cycle count frequency, safety stock levels, and reorder review priority. Reclassification changes logged so buyers can see when a product has moved from C to A (demand growth) and adjust safety stock accordingly.

Aged inventory report: stock on hand grouped by time since receipt (0-30 days, 31-60 days, 61-90 days, 90+ days) at cost value, filterable by location and category. For products with expiry dates, an impending expiry report shows units expiring within a configurable window (e.g., 30 days) across all locations with the current stock quantity and estimated disposal cost, the data needed to trigger price markdowns before stock expires rather than after.