Case Study: RetailPro — 40% Reduction in Stockouts With AI Demand Forecasting
Overview
RetailPro, a multinational retailer operating in 22 countries, suffered from frequent stockouts, inaccurate demand planning, and supply chain delays. Their legacy forecasting system couldn’t adapt to regional seasonality and real-time demand fluctuations.
Logicwerk implemented a real-time AI demand forecasting platform backed by robust data pipelines and predictive models.
Challenges
- Frequent stockouts and overstock situations
- Manual forecasting based on outdated spreadsheets
- Lack of real-time inventory visibility
- Multi-region, multi-SKU complexity
- Large costs tied to storage and lost sales
Traditional BI tools couldn’t handle the scale or speed.
Solution: AI Demand Forecasting Engine
1. Unified Data Pipeline
Aggregated data across:
- POS
- ERP
- Warehouse logs
- Promotions
- Seasonality
- Weather trends
2. Predictive AI Models
Logicwerk developed forecasting models using:
- LSTM time-series models
- Transformer-based forecasting
- Scenario simulations
3. Stockout Prevention Engine
Triggered:
- Auto-replenishment
- Supplier notifications
- Safety-stock recalculation
4. Real-Time Dashboard
Provided demand predictions at:
- Region level
- Store level
- SKU level
Results
📉 40% reduction in stockouts
Better demand predictions improved replenishment cycles.
💰 $12.8M annual savings
Reduced storage + lost-sales recovery.
⚡ 3× improvement in forecast accuracy
ML models replaced manual spreadsheets.
📦 Faster replenishment cycles
AI-driven triggers reduced delays.
Final Outcome
RetailPro became a predictive retail operation, using AI to make real-time supply chain decisions with measurable financial impact.
Work With Logicwerk
Logicwerk builds enterprise-grade AI solutions for:
- Predictive analytics
- Retail optimization
- Supply chain automation