Demand Forecasting System
ML-powered demand prediction with external factor integration and inventory optimization.
Duration
7 months
Team Size
4 developers
Industry
Retail
Category
AI/ML
Demand Forecasting System
An ML-powered forecasting platform that predicts product demand by combining sales history with external factors like weather, events, and economic indicators.
The Challenge
A retail chain struggled with inventory management:
- Inaccurate forecasts - Simple moving averages failing
- Stockouts - Losing sales on popular items
- Overstock - Markdowns eating margins
- Manual planning - Buyers using spreadsheets and intuition
They needed intelligent, automated forecasting.
Our Approach
We built an ML platform that considers hundreds of demand signals.
Forecasting Strategy
- Ensemble Models - Multiple algorithms for robustness
- External Factors - Weather, holidays, events, trends
- Hierarchical - Store, region, and company level
- Automated Pipeline - Daily forecasts without manual work
The Solution
Data Integration
- POS sales history
- Weather forecasts
- Event calendars
- Economic indicators
Forecasting Models
- Time series decomposition
- ML ensemble (XGBoost, Prophet)
- Promotional lift modeling
- New product forecasting
Inventory Optimization
- Safety stock calculation
- Reorder point recommendations
- Allocation optimization
- Markdown timing
Planning Interface
- Forecast visualization
- Override capabilities
- What-if scenarios
- Accuracy tracking
Technology Stack
| Layer | Technologies |
|---|---|
| ML Models | Prophet, XGBoost, LightGBM |
| Orchestration | Apache Airflow |
| Backend | Python, FastAPI |
| Database | PostgreSQL, Redis |
| Frontend | React, Recharts |
| Cloud | AWS (SageMaker, Redshift) |
Results & Impact
The system transformed inventory management:
- 35% more accurate forecasts
- 25% fewer stockouts on key items
- 20% less overstock and markdowns
- $5M+ saved annually
ML Features
External Signals
- Weather correlation
- Holiday and event impact
- Competitive pricing
- Social media trends
Accuracy Monitoring
- Forecast vs actual tracking
- Model performance dashboards
- Automatic model selection
- Drift detection
Client Testimonial
"Our buyers went from spreadsheet guesswork to data-driven decisions. The accuracy improvement paid for the system many times over in reduced stockouts alone."
— VP of Merchandising, Retail Chain
Optimizing inventory? Contact us to discuss demand forecasting solutions.
Key Results
35% improvement in forecast accuracy
25% reduction in stockouts
20% decrease in excess inventory
$5M+ annual savings
Technology Stack
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