UPS Shipping Optimization Tool

Overview

I built a UPS shipping optimization tool to compare shipping rates and transit times across multiple distribution centers. The system was designed to help evaluate which fulfillment location should be used for a given destination ZIP code based on speed, cost, and distribution center priority.

Problem

Shipping decisions can have a major impact on both customer experience and profitability. With multiple distribution centers, it was important to understand which location could serve each region most efficiently.

Manually checking rates and transit times across hundreds of destination ZIP codes and multiple origin locations would have been slow and difficult to maintain.

Solution

I created a Python workflow that connected to the UPS API and generated rate and transit-time comparisons across origin and destination ZIP combinations.

The system included:

• UPS API authentication
• Batch rate lookups
• Transit-time analysis
• Destination ZIP grouping
• Distribution center comparison logic
• Supabase/PostgreSQL storage
• Error logging for invalid destinations
• Data exports for further analysis
• Interactive charts for reviewing shipping performance

The tool compared multiple distribution centers and selected the best option based on transit time, cost, and business-defined priority rules.

Impact

This project made it easier to evaluate fulfillment strategy by geography. It created a repeatable way to analyze shipping performance and supported better operational decisions around routing, cost, and customer delivery expectations.

What I Learned

This project strengthened my experience with external APIs, operational analytics, and decision logic. It also showed how valuable automation can be when a business process requires hundreds or thousands of repeated calculations.