AI-Led Supply Chain Optimization for a Global Retail Giant
Client Overview
Industry: Retail & Consumer Goods (Fortune 100)
Size: $90+ Billion Annual Revenue | 2,000+ Stores in 40 Countries
Regions Served: North America, EU, LATAM
Engagement Model: AI/ML Integration + Inventory Optimization + Real-Time Analytics
IBU’s Role: Predictive Analytics, Machine Learning Implementation, Digital Twin for Logistics
The Challenge: Stockouts & Overstocking Across a Fragmented Supply Chain
Despite global expansion, this retail powerhouse faced operational inefficiencies in demand forecasting. Legacy ERP systems failed to handle SKU-level predictions across geographies, leading to revenue leakage and excess warehousing costs.
Pain Points:
- 22% inventory mismatch across stores
- Forecasting based on static, outdated data
- Low visibility across distribution hubs
- Rising last-mile delivery costs
“We needed precision forecasting at a hyper-local level — not just a dashboard that looked good.”
— SVP, Global Supply Chain
Why IBU? End-to-End AI + Domain Expertise
IBU offered a unique combination of:
- Advanced ML models tailored for retail seasonality
- Geo-specific demand prediction with external data fusion (weather, holidays, events)
- Digital twin simulation of logistics networks
The Solution: Smart Inventory, Real-Time Insights
Phase 1: Data & Forecasting Engine Overhaul
- Cleaned and merged 6 TB+ of historical, POS, and logistics data
- Created predictive demand models for 17,000+ SKUs
- Integrated with existing SAP/Oracle systems
Phase 2: Real-Time Analytics Platform
- Built a unified control tower for live inventory tracking
- Used AI to recommend auto-replenishment thresholds
- Integrated external data like weather, social buzz, and economic data
Phase 3: Simulation & Optimization
- Created digital twins of 12 key distribution hubs
- Ran scenario modeling to reduce dead stock and optimize lead times
The Metrics: What We Delivered
Metric | Before IBU | After 6 Months |
Inventory Accuracy | 74% | 95% |
Dead Stock Volume | $230M | $92M |
Forecast Accuracy | 68% | 91% |
Delivery SLA Compliance | 82% | 97% |
“This wasn’t just analytics. It changed how we make supply decisions globally.”
