Optimizing Cash on Delivery (COD) for Retail Success

Optimizing Cash-on-Delivery (COD) for Retail Success


Technology Used:

  • Angular 7 (front-end development with TypeScript)
  • Node.js (back-end development)
  • Python (data analysis and machine learning)
  • Google OR Tools (optimization algorithms)
  • R Programming Language (statistical analysis)
  • Oracle 12c Database


A leading New York City-based retailer with a strong market presence and 30 years of experience. Recognizing the need for improved profitability and customer satisfaction, they sought to optimize their COD process.


  • Network Complexity:Optimizing a network with diverse transportation modes, inventory levels, and delivery timelines proved difficult.
  • Limited Visibility:Gaining real-time insights into inventory, transportation status, and demand patterns remained a hurdle.
  • Resource Allocation:Balancing cost-efficiency with service levels and ensuring optimal resource allocation across locations presented an ongoing challenge.

Solution Delivered:

  • Advanced Supply Chain Visibility Platform:We developed a platform integrating data from various systems, offering real-time insights into inventory levels, transportation status, and demand patterns.
  • Predictive Analytics & Optimization:By leveraging advanced analytics and demand forecasting tools, we predicted demand patterns, optimized inventory levels, and minimized stockouts or excess inventory.
  • Collaborative Communication Tools:We implemented communication tools to facilitate seamless communication and coordination among supply chain stakeholders.


The client was able to get the following results –

  • Enhanced Visibility:The client gained real-time visibility into their entire supply chain, enabling better monitoring of inventory, transportation, and demand.
  • Optimized Logistics Planning:Scenario generation capabilities and optimization tools facilitated more efficient and cost-effective operations.
  • Increased Agility:The client gained the ability to respond rapidly to supply chain changes such as demand shifts, transportation disruptions, or market trends.
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