Inventory ABC Classification Analysis Builder
Analyze inventory with ABC classification, velocity, margin, stockout risk, carrying cost, and replenishment actions for retail or warehouse teams.
Prompt Template
You are an inventory analytics lead. Build an ABC classification analysis for: Business type: [retail, ecommerce, wholesale, manufacturing, spare parts, grocery, pharmacy] Dataset available: [SKU, units sold, revenue, margin, stock on hand, stockouts, lead time, carrying cost, supplier, category] Time window: [last 30 days, 90 days, 12 months, seasonal period] Classification goal: [service-level focus, cash reduction, replenishment priority, warehouse slotting, shrink review] Known constraints: [seasonality, new SKUs, discontinued SKUs, long lead times, substitutes, minimum order quantities] Segmentation needs: [category, supplier, location, channel, margin band, velocity band] Tools: [SQL, spreadsheet, Python, BI dashboard, ERP export] Decision audience: [operations, finance, merchandising, procurement, warehouse] Create: 1. Data cleaning and validation checklist 2. Metric definitions for consumption value, margin value, velocity, stockout rate, carrying cost, and days of supply 3. ABC classification method with cumulative percentage thresholds and optional margin/risk overlay 4. SQL or spreadsheet calculation outline 5. Segment readout by category, supplier, and location 6. Recommended actions for A, B, C, dead stock, and high-risk items 7. Dashboard specification with filters, charts, and exception tables 8. Caveats for seasonality, new products, substitutions, and low-data SKUs 9. Executive summary template with cash, service, and operational tradeoffs Separate classification logic from replenishment policy decisions.
Example Output
# ABC Inventory Analysis - Outdoor Gear Retailer
Method
Calculate annual consumption value as units sold x unit cost, sort SKUs descending, and assign A items to the first 80% of cumulative value, B to the next 15%, and C to the final 5%. Add a risk flag for stockout rate above 8% or lead time above 45 days.
Findings
| Class | SKUs | Value Share | Action |
|---|---:|---:|---|
| A | 420 | 80% | Tight cycle counts, higher service level, weekly replenishment review |
| B | 1,100 | 15% | Monthly planning, standard reorder rules |
| C | 4,800 | 5% | Reduce review frequency, rationalize duplicates, avoid overbuying |
| Dead stock | 360 | - | Markdown, bundle, return-to-vendor review |
Caveat
New winter SKUs are underclassified because the analysis window excludes peak season.
Tips for Best Results
- 💡Ask for margin and stockout fields; revenue alone can misclassify operationally important SKUs.
- 💡Call out new and seasonal items so they do not get punished by short history.
- 💡Use ABC classes to guide actions, not as a final purchasing policy by itself.
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