Cloud-Based Inventory & Warehouse Management System

GroceryHub Distribution 2022
84%Reduction in stockouts
62%Decrease in waste and shrinkage
99.7%Order fulfillment accuracy
55%Improvement in picking efficiency

How we got there

01

The Challenge

GroceryHub operated 6 regional warehouses distributing fresh and packaged goods to 120 retail locations, processing 85,000 SKUs daily. Their legacy inventory system couldn't handle perishable goods with complex expiration tracking, leading to 18% stockout rate on popular items and $2.8M annual losses from expired inventory and waste. Manual processes for receiving, putaway, and order picking created bottlenecks, with order fulfillment taking 18-24 hours.

The company needed a modern warehouse management system with FIFO/FEFO rotation for perishables, barcode scanning for receiving and picking, real-time inventory visibility across all locations, automated reordering based on demand forecasting, mobile apps for warehouse workers, and integration with their existing accounting system (QuickBooks Enterprise) and transportation management system. The solution needed to handle 150,000+ daily transactions during peak periods.

02

Our Approach

We spent 4 weeks on-site at all 6 warehouses, shadowing workers through receiving, putaway, picking, and shipping workflows. We documented 47 unique process variations and identified critical pain points: unclear bin locations causing 22-minute average pick times, manual expiration date tracking leading to waste, and lack of mobile access forcing workers to walk to stationary terminals. Time-motion studies revealed 68% of picker time was spent walking rather than picking.

We implemented a cloud-based ERP system built on Microsoft Dynamics 365 for Supply Chain Management, customized for food distribution. The system included advanced batch and serial number tracking, quality management workflows for receiving inspections, directed putaway using ABC analysis to optimize product placement, wave picking with optimized pick paths, and automated cycle counting schedules. We integrated Honeywell mobile computers for barcode scanning throughout all warehouse workflows.

A custom demand forecasting module used machine learning to analyze 3 years of sales history, seasonal patterns, promotional calendars, and weather data to predict demand and trigger automated purchase orders. The system integrated with QuickBooks for financial data sync and provided real-time inventory reporting across all locations via Power BI dashboards.

03

The Results

The inventory management system transformed operational efficiency across 6 warehouses and 120 retail locations. Real-time stock visibility eliminated $2.8M in annual shrinkage and waste. Automated reorder algorithms reduced stockouts from 18% to 3%, while order picking efficiency improved by 55% through optimized warehouse layouts and mobile picking apps. The system processed 85,000 SKUs daily with 99.7% accuracy.

Warehouse Optimization & Mobile Picking

We re-slotted all 6 warehouses using ABC analysis, placing high-velocity items in golden zones closest to packing stations. The mobile picking app displayed optimized pick paths reducing travel by 42%. Batch picking allowed workers to pick multiple orders simultaneously, improving efficiency by 55%. Voice-directed picking for high-volume areas achieved 99.8% accuracy. Real-time dashboards showed picking productivity by worker, enabling performance coaching and incentive programs.

Perishable Goods & Expiration Management

The system tracked expiration dates for 35,000+ perishable SKUs, automatically enforcing FEFO (First Expired, First Out) picking rules. Mobile scanners flagged products within 7 days of expiration for immediate promotion or disposal. Automated alerts notified buyers when slow-moving items approached expiration, enabling proactive markdowns. Temperature monitoring integration sent real-time alerts for refrigeration failures, preventing $180K in spoilage during the first year alone.

Demand Forecasting & Automated Replenishment

Machine learning models analyzed historical sales data, incorporating factors like day of week, holidays, local events, and weather forecasts. The system achieved 87% forecast accuracy, automatically generating purchase orders when stock reached reorder points. Min/max levels were dynamically adjusted based on lead times and demand variability. Integration with supplier EDI systems enabled automated order transmission and receipt confirmation.

Implementation & Training

We executed a phased rollout, starting with a single warehouse pilot running parallel with the legacy system for 3 weeks. After validation, we rolled out to remaining warehouses over 12 weeks. We trained 280 warehouse staff through hands-on sessions using realistic scenarios. Super users received advanced training to become on-site champions. The comprehensive training program achieved 92% user adoption within 4 weeks of each warehouse going live.

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