Omni Channel Inventory Optimization

1. Problem Statement – Detailed Understanding

Business Context:

• Operations:
  
  1. Australia: 1 main warehouse + 3 offline retail stores (which also act as mini-warehouses).
     
  2. USA: 1 warehouse for fulfilling only US orders.
     
• Sales Channels: Primarily in Australia, some in the USA, through Shopify website and Retail stores.
  
• Target Days of Cover: 90 days (ensure stock lasts at least 60 days post-procurement).
• Current State: Inventory planning done in Google Sheets.

‍

Challenges Identified:

1. Inefficient Inventory Allocation at Stores
   
   • Slow-moving stock remains stuck in certain locations, while the same SKUs sell out elsewhere.
   • Causes missed sales in some areas and overstocking costs in others.
     
2. No early warning system for
   
   • Low stock on top sellers at the Store
   • Stock with decreasing ROS (Sales velocity)
   • Slow moving stock at a Store
     
3. Data Inaccuracies & Delays
   
   • Manual spreadsheet dependency → high risk of human error.
     
   • Slow data updates → missed opportunities to adjust procurement or replenishment in time.
     
     
     

2. Solution – Detailed Breakdown of Implementation

‍

A. Demand & PO Planning:

• Centralized Demand Aggregation and Reorder Estimations
  
  • Combine sales data from Australia WH + 3 retail stores.
    
  • Use this combined demand to auto-generate accurate POs for the Chinese vendor.
    
  • Removes manual spreadsheet guesswork.
    
• Separate PO Planning for US WH
  
  • US warehouse has its own sales trends & stock needs.
    
  • Plan POs specifically for US orders, without interfering with AU stock.

‍

B. Inventory Rebalancing:

• Excess Stock Recommendations
  
  • Identify slow-moving items in stores.
    
  • Recommend sending them back to the Australia WH.
    
  • Redistribute from Australia WH to other stores where demand is high.
    
• Automated Store-Level Replenishment
  
  • Live sales velocity from each store → triggers replenishment from AU WH.
    
  • Avoids manual allocation delays.

‍

C. Forecasting Accuracy:

• Out-of-Stock Adjusted DRR (Demand Run Rate)
  
  • Adjust demand calculations to ignore periods when an SKU was out of stock.
    
  • Prevents underestimation of demand for fast-sellers.
    ‍
    

E. Alerts & Reporting:

• Daily Email Reports
  
  • Sales trends by SKU, style, and category.
    
  • Highlight top-performing products to capitalize quickly.
    
• Alert System
  
  • Delayed POs → email & dashboard notification.
    
  • Low coverage items → triggers replenishment.
    
  • Slow movers → flagged for clearance or reallocation.

‍