From Manual Push-Sheets to Proactive Distribution
Traditional allocation is often a time-consuming, spreadsheet-driven process based on static store grades and historical sales. This leads to suboptimal inventory placement, lost sales from stock-outs, and costly end-of-season markdowns or transfers. The Cybex WMS Allocation application leverages the Cybex Retail AI Data Platform to automate and optimize distribution, ensuring every store gets the right inventory to meet local demand.
Our approach is to create a dynamic, self-learning system that understands demand drivers at a granular level—from store-specific size preferences to a style's position in its life cycle—to generate precise allocation quantities.
Core AI Use Cases in WMS Allocation
Our application uses machine learning to generate precise, parameter-based distribution quantities that adapt to store performance, seasonality, and product lifecycle.
1. Automated, Parameter-Based Distribution
The system generates allocation quantities based on a forward-looking demand forecast, ensuring inventory is placed to maximize future sales potential, not just repeat past performance.
- SKU-Location Granularity: Forecasts are generated for every SKU at every location, incorporating unique demand patterns for optimal inventory placement.
- Forward Weeks of Supply (WOS): Allocation quantities are calculated to meet forward WOS targets, ensuring each store has the right depth of inventory.
- Dynamic Parameterization: Incorporates weekly seasonality indexes, store clusters, and style life cycle stages (launch, growth, maturity, decline) to adjust allocation strategies in real-time.
2. Intelligent Size & Store Indexing
Getting the right styles to a store is only half the battle. Getting the right sizes is critical for sell-through. Our platform uses AI to perfect the size mix for every delivery.
- Store Index (SiteIX): The platform clusters stores based on sales volume, climate, and demographic attributes, allowing for tiered and targeted allocation strategies.
- Size Index (SizeIX): By analyzing sales data at the size level for each store or cluster, the system generates a dynamic size index. This ensures allocation reflects true local size demand, preventing broken size runs and maximizing full-price sales.
- AI-Generated Size Curves: The application generates optimal size curves for initial allocations of new products and continuously refines them based on real-time sales data.
3. Optimized Inventory Balancing
The platform provides the tools for intelligent in-season inventory management, suggesting transfers to resolve inventory imbalances between stores.
- Warehouse-to-Store Allocation: Generates optimized distribution plans for new receipts from the WMS to the store network.
- Store-to-Store Balancing: Identifies opportunities to move unproductive inventory from over-stocked locations to under-stocked locations where it has a higher chance of selling.
Key Benefits for Project Decision-Makers
Implementing the Cybex AI WMS Allocation application is a direct investment in improving sell-through, protecting margins, and increasing operational efficiency.
Optimized In-Stock & Sell-Through
By aligning inventory with true local demand and size preferences, you increase full-price sell-through, reduce stock-outs on best-sellers, and improve customer satisfaction.
Reduced Markdowns & Transfers
Intelligent initial allocations and precise size curves prevent sending the wrong product to the wrong store, dramatically reducing the need for costly end-of-season markdowns and inefficient store-to-store transfers.
Increased Planner Productivity
Automate the manual, repetitive tasks of creating allocation push-sheets. This frees your allocation team to focus on strategic decision-making, exception management, and refining high-level inventory strategy.
In-House Customization & Deployment Project
We partner with your team to deploy an Allocation solution tailored to your unique business processes and data landscape. A typical project follows a clear, phased approach:
Phase 1: Integration (2-3 Weeks)
Connect to your data sources (POS, eCom, ERP, WMS). Our adapters map your native schemas to the Cybex conformed data model, establishing a single source of truth for sales and inventory.
Phase 2: Customization (2-3 Weeks)
Configure allocation parameters (WOS, presentation minimums) and business rules. We train the initial set of forecasting, store clustering, and size index models on your historical data.
Phase 3: Deployment & Training (1-2 Weeks)
Go-live with the application. We provide dashboards, an allocation review workflow, and comprehensive training for your allocation and planning teams to manage the system.
Ready to perfect your inventory placement?
The Cybex WMS Allocation application is the key to maximizing sell-through and profitability.