Automated Inventory Management Infrastructure

A UK-based retail chain with 45 locations was experiencing significant revenue loss due to stockouts and overstocking. Their manual inventory management system relied on spreadsheets and weekly reports, creating blind spots in their supply chain.

The Challenge

The client's existing inventory system had three critical failures:

• No real-time visibility into stock levels across locations
• Demand forecasting based on historical averages, not predictive analytics
• Manual reordering processes taking 3-4 days per cycle

These gaps resulted in 18% stockout rate during peak periods and £1.2M in excess inventory annually.

The Infrastructure Solution

Entrelix architected a three-layer inventory intelligence system:

Real-Time Inventory Layer

Connected all POS systems and warehouses into a unified data stream. Every transaction updates inventory state instantly across the network, eliminating blind spots.

Predictive Demand Engine

AI-powered forecasting analyzes historical sales, seasonal patterns, local events, and weather data to predict demand at the SKU level for each location. Accuracy improved from 67% to 94%.

Automated Reordering System

Intelligent automation triggers purchase orders based on predicted demand and lead times. The system optimizes order quantities and timing to minimize both stockouts and carrying costs.

Measurable Outcomes

Within 6 months of deployment:

• 73% reduction in stockouts during peak shopping periods
• £940,000 reduction in excess inventory carrying costs
• 94% forecast accuracy vs. 67% with manual methods
• Automated 89% of reordering decisions
• 3-hour response time for supply chain adjustments vs. 3-4 days previously

Long-Term Impact

The infrastructure continues to improve through machine learning. After 18 months, the system handles seasonal demand spikes autonomously, and the client has expanded to 12 additional locations without adding inventory management staff.