القائمة
Track and manage e-commerce inventory levels. Set up low stock alerts, forecast demand, manage reorder points, and prevent stockouts across multiple platforms.
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استنادا إلى تصنيف SOC المهني
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| name | ecommerce_inventory_tracker |
| description | Track and manage e-commerce inventory levels. Set up low stock alerts, forecast demand, manage reorder points, and prevent stockouts across multiple platforms. |
Monitor and manage inventory across multiple sales channels.
Use this skill when the user wants to:
| Metric | Formula | Target |
|---|---|---|
| Stock Turnover | COGS / Average Inventory | 6-12x per year |
| Days of Inventory | 365 / Turnover | 30-60 days |
| Stockout Rate | Stockouts / Total Orders | <2% |
| Carrying Cost | Inventory Value × 20-30% | Minimize |
| Reorder Point | (Lead Time × Daily Sales) + Safety Stock | Calculate |
Safety Stock = Z × σ × √(Lead Time)
Where:
- Z = Service factor (1.65 for 95% service level)
- σ = Standard deviation of daily demand
- Lead Time = Days from order to receipt
Gather current stock levels:
## Inventory Snapshot
| SKU | Product | Current Stock | Location | Status |
|-----|---------|--------------|----------|--------|
| SKU-001 | Product Name | 150 | Warehouse A | OK |
| SKU-002 | Product Name | 5 | Warehouse A | ⚠️ LOW |
| SKU-003 | Product Name | 0 | Warehouse B | ❌ OUT |
For each product, define:
## Alert Thresholds
| Alert Level | Trigger | Action |
|-------------|---------|--------|
| 🔴 Critical | ≤5 units | Immediate reorder |
| 🟡 Warning | ≤20 units | Review and plan reorder |
| 🟢 Normal | >20 units | Monitor |
Weekly Forecast Formula:
Expected Weekly Sales = (Last 4 weeks sales) / 4 × Seasonality Factor
Seasonality Factors:
- Peak season: 1.3-1.5x
- Normal: 1.0x
- Off-peak: 0.7-0.8x
## 📦 Daily Inventory Report - [DATE]
### Critical Alerts
| SKU | Product | Stock | Days Left | Action |
|-----|---------|-------|-----------|--------|
| SKU-123 | Widget A | 3 | 0.5 days | REORDER NOW |
| SKU-456 | Widget B | 8 | 2 days | Review reorder |
### Healthy Stock
| SKU | Product | Stock | Days Left |
|-----|---------|-------|-----------|
| SKU-789 | Gadget X | 250 | 45 days |
| SKU-012 | Gadget Y | 180 | 30 days |
### Out of Stock
- SKU-999 - Super Gadget (2 pending orders)
## 📋 Weekly Reorder Plan - Week of [DATE]
### Orders to Place Today
| Supplier | SKU | Qty | Cost | Lead Time |
|----------|-----|-----|------|-----------|
| Supplier A | SKU-123 | 500 | $2,500 | 7 days |
| Supplier B | SKU-456 | 200 | $1,800 | 14 days |
### Orders to Monitor
| SKU | ETA | Status |
|-----|-----|--------|
| SKU-789 | Mar 30 | In Transit |
| SKU-012 | Apr 2 | Processing |
EOQ = √(2 × D × S / H)
Where:
- D = Annual demand
- S = Ordering cost per order
- H = Annual holding cost per unit
Days of Inventory = (Current Stock / Average Daily Sales)
Interpretation:
- <30 days: Potential stockout risk
- 30-60 days: Healthy range
- >60 days: Overstocking risk