Global Health Supply Chain Optimization
An analytics platform tracking $1.46B in global health commodity shipments — ARV antiretroviral drugs and HIV Rapid Diagnostic Tests (HRDT) — across USAID-funded international health programs. Identifies freight cost concentration, carrier performance gaps, and procurement optimization opportunities.
The Analytical Process
Data Engineering (Python)
Performed extensive wrangling with Pandas to handle missing capture dates, non-numeric costs, and multi-country delivery records from the USAID SCMS global health commodity dataset — covering ARV antiretroviral and HIV diagnostic shipments across Africa, Asia, and Latin America.
- Feature Engineered: Delivery Lead Time & On-Time Flags
- Standardized Weight & Freight Cost conversion
- Imputed NULLs for Line Item Insurance and Shipment Modes
KPI Development
Identified core metrics critical to logistics spend and operational reliability.
Interactive Visualization
Deployed Tableau dashboards with dynamic filters to allow ad-hoc exploration by country, mode, and product group.
Cost Concentration
ARV antiretroviral drugs and HRDT HIV Rapid Diagnostic Test commodity groups account for 99% of total logistics spend ($1.46B+) across global health supply chains — identifying the primary levers for procurement cost reduction in international health programs.
Mode Reliability
Ocean shipments (84% OTD) and standard Air (88% OTD) contribute most to delays compared to 100% OTD for Air Charter. Average lead times varied from 88 to 144 days.
Technical Toolkit
Strategic Recommendation
"Concentrate procurement negotiations on Air and Ocean freight contracts for high-volume ARV and HRDT routes. A 5% cost reduction on these two commodity groups recovers approximately $73M annually across the global health supply chain network."
Github RepositorySupporting Visuals
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