SKU Proliferation: How to Clean Up Your Messy Product Catalog
- Data‑driven pruning : Use analytics to identify low‑velocity SKUs and redundant variants.
- EdgeOS + Dark Store Mesh : Automate inventory sync across tier‑2/3 hubs and reduce RTO incidents.
- Strategic partnership : Align with couriers like Delhivery & Shadowfax to optimize COD fulfillment during festive peaks.
Introduction
Every Indian e‑commerce business that has scaled beyond a single SKU is fighting the same invisible war: SKU proliferation. In cities like Mumbai, Bangalore, and even tier‑2 hotspots like Guwahati, the sheer number of product variants inflates storage costs, distorts demand forecasts, and strains logistics partners. Cash‑on‑delivery (COD) remains the default payment mode for 70% of Indian consumers, while Return‑to‑Origin (RTO) incidents spike during festive rushes. If your catalog is a tangled mess, these pain points multiply. Let’s dissect the problem, quantify the impact, and map a clear, data‑backed path to a leaner, faster‑moving catalog.
1. The Anatomy of SKU Proliferation
1.1 Why SKUs Multiply
| Driver | Typical Impact | Example |
|---|---|---|
| A/B Testing | 3x more variants in a month | 2 color options → 6 variations (size + color) |
| Seasonal Collections | 5–10% of catalog added yearly | Festive “Diwali” bundle added to all categories |
| Third‑Party Sellers | Uncontrolled SKU entry | Marketplace sellers list 100+ variants per product |
1.2 Quantifying the Cost
- Inventory Carrying Cost : ₹15 per SKU per month (storage + depreciation).
- Order Fulfillment Complexity : 0.5 minutes per SKU for picking/packaging.
- RTO Rate Increase : +2% RTO for every 100 SKUs added.
2. Problem‑Solution Matrix
| Problem | Root Cause | Solution | KPI Impact |
|---|---|---|---|
| Redundant variants | Manual SKU creation | EdgeOS SKU audit engine | ↓ SKU count by 30% |
| Inconsistent inventory data | Multiple silos | Dark Store Mesh real‑time sync | ↓ Stockouts by 20% |
| High RTO during festivals | Unbalanced courier load | NDR Management + EdgeOS routing | ↓ RTO by 15% |
| Poor demand forecast | Skewed historical data | Data‑driven SKU pruning | ↑ Forecast accuracy by 18% |
3. Data‑Driven SKU Pruning
- Sales Velocity : SKUs with < 5 units/month for 6 consecutive months.
- Margin Impact : SKUs with gross margin < 5% and low turnover.
- Customer Feedback : SKUs with > 30% return rate.
| Criterion | Weight | Score | Decision |
|---|---|---|---|
| Monthly Sales | 0.4 | 0–20 | Keep / Reduce |
| Gross Margin | 0.3 | 0–10 | Keep / Reduce |
| Return Rate | 0.3 | 0–5 | Keep / Reduce |
- 1. Batch Removal : Delete or archive SKUs in 1,000‑SKU batches.
- 2. Variant Consolidation : Merge color/size combos that share SKU attributes.
- 3. Metadata Cleanup : Standardize titles, images, and attributes across remaining SKUs.
4. EdgeOS: Your Catalog‑to‑Logistics Bridge
EdgeOS is a lightweight, AI‑enabled micro‑service that sits between your ERP and warehouse management.
- Real‑time SKU Validation : Flags duplicates before they hit the catalog.
- Inventory Sync : Pushes accurate stock levels to Dark Store Mesh hubs in 2 seconds.
- Demand Forecasting : Uses machine learning to predict SKU demand spikes, especially during Indian festivals (Diwali, Holi).
5. Dark Store Mesh: Localized Fulfillment for Tier‑2/3 Cities
Dark Store Mesh creates a network of decentralized fulfillment centers (e.g., in Guwahati or Mysuru) that:
- Reduces Delivery Time : 30–40% faster than city‑wide warehouses.
- Optimizes COD Handling : Local couriers (Delhivery, Shadowfax) can pick up COD orders in real time, lowering the risk of cash loss.
- Supports RTO Management : Return packages can be processed locally, cutting RTO cost by 20%.
6. Aligning with Indian Couriers
- Delhivery : Integrate their API with EdgeOS to auto‑assign delivery slots based on SKU weight and volume.
- Shadowfax : Use their dark‑store‑first approach to handle COD orders during peak times.
Best Practice: Set a minimum SKU threshold per courier route; SKUs with low volume should be routed through a shared dark store node to avoid under‑utilization.
Conclusion
Sku proliferation is not just a catalog issue; it’s a systemic inefficiency that inflates costs, delays deliveries, and erodes customer trust—especially in a COD‑heavy, festival‑driven market like India. By adopting a data‑driven pruning strategy, leveraging EdgeOS for real‑time visibility, and deploying Dark Store Mesh to localize fulfillment, you can trim your catalog to a lean, high‑velocity set of SKUs that aligns with your logistics network. The result? Lower inventory costs, fewer RTO incidents, and a smoother omnichannel experience for your customers in Mumbai, Bangalore, Guwahati, and beyond.