Supply Chain Analytics: Inventory, Demand Forecasting, Logistics Optimization
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# Supply Chain Analytics: Inventory, Demand Forecasting, Logistics Optimization ## 🎯 Learning Objectives - Apply analytics to optimize inventory levels - Build demand forecasting models for supply chain planning - Optimize logistics and distribution networks - Measure supply chain KPIs and identify bottlenecks ## �...
Supply Chain Analytics: Inventory, Demand Forecasting, Logistics Optimization
🎯 Learning Objectives
- Apply analytics to optimize inventory levels
- Build demand forecasting models for supply chain planning
- Optimize logistics and distribution networks
- Measure supply chain KPIs and identify bottlenecks
📖 Core Content
1.1 Supply Chain KPIs
| KPI | Formula | Target |
|---|---|---|
| Inventory Turnover | COGS / Avg Inventory | Industry-dependent (5-10× for retail) |
| Fill Rate | Orders Fulfilled / Total Orders | > 95% |
| Lead Time | Order to Delivery time | < industry avg |
| Stockout Rate | Days out of stock / Total days | < 2% |
| OTIF | On Time In Full deliveries / Total | > 90% |
1.2 Demand Forecasting
python# runnable # Time series methods for demand forecasting # Simple Exponential Smoothing: weights recent observations more # Holt-Winters: trend + seasonality # Prophet (Facebook): handles holidays, changepoints # LSTM: for complex patterns with enough data # Simple demand forecast formula: # F_{t+1} = α × D_t + (1-α) × F_t # where α is smoothing factor (0.1-0.3 typical for stable demand)
1.3 Inventory Optimization
The Economic Order Quantity (EOQ) model:
where D = annual demand, S = order cost, H = holding cost per unit.
Safety Stock:
where z = service level Z-score (1.65 for 95%), = demand std dev, L = lead time.
1.4 Why This Matters
Supply chain analytics directly impacts profitability. A 1% improvement in forecast accuracy can reduce inventory costs by 2-5% and stockouts by 10-20%.
2. 📝 Practice Questions
Q1: A retailer has annual demand of 10,000 units, ordering cost of 5/unit/year. What's the optimal order quantity?EOQ = √(2 × 10,000 × 100 / 5) = √(400,000) = 632 unitsOrdering 632 units at a time minimizes total inventory costs (ordering + holding). They should place approximately 10,000/632 ≈ 16 orders per year. Join Discord PreviousMarketing AnalyticsNextPricing Analytics