Dead Stock Analysis: Using Data to Clear Out Slow‑Moving Inventory
- Identify dead stock using key turnover metrics and age‑based clustering.
- Map inventory bottlenecks to logistics issues (COD delays, RTO rates).
- Deploy Edgistify’s EdgeOS & Dark Store Mesh to dynamically route goods and trigger liquidation campaigns.
Introduction
In India’s rapidly expanding e‑commerce arena, a single SKU stuck in a Tier‑2 warehouse can cost an entire business thousands of rupees per month. Cash tied up in slow‑moving inventory hampers cash flow, inflates storage costs, and, more importantly, erodes the customer experience when COD‑heavy shoppers face long waits or RTO (Return‑to‑Origin) complications. The challenge is not just inventory, but data: without a clear, metrics‑driven view, merchants risk overstocking or under‑stocking critical items. This post shows how a systematic Dead Stock Analysis, powered by Edgistify’s EdgeOS and Dark Store Mesh, can turn dormant stock into cash flow.
Why Dead Stock Matters in Indian E‑Commerce
Cost of Holding Slow‑Moving Inventory
| Holding Cost | Annual Impact (₹) | Example (₹10k SKU) |
|---|---|---|
| Storage (₹10/sku/month) | ₹120 | ₹1,200 |
| Opportunity Cost (5% ROI) | ₹500 | ₹5,000 |
| Total | ₹620 | ₹6,200 |
Impact on Cash Flow
- Cash tied up : ₹6,200 per SKU per year.
- Delayed order fulfillment : 15–20% of COD orders delayed due to RTO from storage bottlenecks.
Customer Experience
- COD delays : 30% of Tier‑3 cities report COD wait > 48 hrs.
- RTO rates : Average RTO in Bangalore is 12% for items > ₹500, half of which are slow‑moving.
Key Metrics for Dead Stock Analysis
| Metric | Formula | Interpretation |
|---|---|---|
| Inventory Turnover Ratio | Cost of Goods Sold ÷ Average Inventory | < 3 = high dead stock |
| Days Sales of Inventory (DSI) | 365 ÷ Turnover | > 120 days = stagnant |
| Stock Aging | Count of days since last sale | > 180 days = candidate for liquidation |
Using Pareto (80/20) and Cluster Analysis
- Pareto : 20% of SKUs account for 80% of sales; the remaining 80% often are dead stock.
- Cluster : Group SKUs by age, demand pattern, and RTO frequency to target specific clearance strategies.
Data‑Driven Approach to Identify Dead Stock
Data Sources
| Source | Data Points | Frequency |
|---|---|---|
| POS & ERP | SKU sales, returns, stock levels | Daily |
| Delivery Records | COD collection status, RTO rates | Real‑time |
| Dark Store Analytics | Pick‑rate, order volume | Hourly |
Analytics Techniques
- 1. Time‑Series Forecasting to detect demand dips.
- 2. Anomaly Detection for sudden sales drops.
- 3. Heat‑Map Visualization of inventory age across warehouses.
Problem‑Solution Matrix for Indian Logistics
| Problem | Root Cause | Edgistify Solution | Expected Benefit |
|---|---|---|---|
| Excess dead stock in Tier‑2 warehouses | Poor demand visibility | EdgeOS real‑time inventory dashboard | +25% inventory turnover |
| High RTO from COD orders | Slow pick‑and‑pack | Dark Store Mesh routing to nearest fulfillment node | -15% RTO rate |
| Inflexible inventory movement | Manual stock transfer | NDR Management API for automated transfers | -20% handling cost |
Leveraging Edgistify’s EdgeOS & Dark Store Mesh
EdgeOS: Real‑Time Visibility
- Dashboards show SKU age, turnover, and RTO trends at a single click.
- Predictive alerts flag SKUs exceeding 180 days, triggering automated liquidation workflows.
Dark Store Mesh: Dynamic Routing
- Multi‑hub architecture lets the system re‑route orders to the nearest dark store, reducing COD wait times.
- Geo‑targeted promotions push slow‑moving SKUs to high‑traffic dark stores, boosting sales velocity.
Implementing NDR Management to Reduce Returns
- 1. Set Return Thresholds : Automatically flag SKUs with >10% RTO in the last 30 days.
- 2. Auto‑Dispatch : Use NDR API to send replacement items to the nearest store, cutting return shipping cost.
- 3. Feedback Loop : Feed return data back into EdgeOS to refine demand forecasts.
Conclusion
Dead stock isn’t a silent drain; it’s an active cash‑flow leak that can cripple an e‑commerce operation, especially in India’s COD‑heavy market. By combining robust data analytics, real‑time visibility through EdgeOS, and agile fulfillment via Dark Store Mesh, merchants can turn stagnant inventory into a revenue engine. The key is a data‑driven, integrated logistics strategy—not just inventory cuts, but smarter movement of goods.