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Analyze inventory health using turnover ratios, ABC classification, safety stock calculations, and stockout vs overstock diagnostics. Use this skill when the user needs to optimize inventory levels, reduce carrying costs, prevent stockouts, or classify products by inventory priority — even if they say 'we have too much stock', 'we keep running out of bestsellers', 'how much safety stock do we need', or 'which products should we focus on'.
npx skill4agent add asgard-ai-platform/skills ecom-inventory-healthIRON LAW: Not All SKUs Deserve Equal Attention
ABC classification shows that ~20% of SKUs drive ~80% of revenue.
Treat A-items (top 20% revenue) with tight control and frequent review.
C-items (bottom 50% revenue) get simple rules and less attention.
Equal treatment of all SKUs wastes resources on low-impact items.| Metric | Formula | Healthy Range |
|---|---|---|
| Inventory Turnover | COGS / Avg Inventory | 4-12x/year (industry-dependent) |
| Days of Inventory (DOI) | 365 / Inventory Turnover | 30-90 days |
| Stockout Rate | Stockout incidents / Total demand occasions | < 2-5% |
| Fill Rate | Orders filled completely / Total orders | > 95% |
| Carrying Cost | Avg Inventory × Carrying Cost % (typically 20-30%/year) | Minimize |
| Dead Stock % | Items with zero sales in 6+ months / Total SKUs | < 10% |
| Class | Revenue % | SKU % | Strategy |
|---|---|---|---|
| A | ~80% | ~20% | Tight control, frequent review, safety stock optimized |
| B | ~15% | ~30% | Moderate control, periodic review |
| C | ~5% | ~50% | Simple rules, min/max levels, consider dropping |
Safety Stock = Z × σ_d × √(Lead Time)
Where:
- Z = service level factor (1.65 for 95%, 2.33 for 99%)
- σ_d = standard deviation of daily demand
- Lead Time = supplier lead time in daysReorder Point = (Average Daily Demand × Lead Time) + Safety Stock# Inventory Health Report: {Business}
## Summary
| Metric | Current | Target | Status |
|--------|---------|--------|--------|
| Turnover | {X}x | {X}x | 🟢/🟡/🔴 |
| DOI | {X} days | {X} days | 🟢/🟡/🔴 |
| Fill Rate | {X%} | >95% | 🟢/🟡/🔴 |
| Dead Stock | {X%} | <10% | 🟢/🟡/🔴 |
## ABC Distribution
| Class | SKUs | Revenue % | Avg DOI | Issue |
|-------|------|----------|---------|-------|
| A | {N} | {%} | {days} | {stockout risk?} |
| B | {N} | {%} | {days} | ... |
| C | {N} | {%} | {days} | {overstock?} |
## Top Issues
1. {issue with specific SKUs and data}
## Recommendations
1. {action with expected impact}references/eoq-model.mdreferences/seasonal-forecasting.md