Product Economics for Logistics & Supply Chain
Logistics technology operates at the intersection of real-time systems, IoT scale, and AI forecasting. Each dimension creates distinct engineering economics.
Real-Time System Debt
Tracking millions of packages, vehicles, and warehouse operations in real-time creates latency requirements that compound infrastructure complexity exponentially.
IoT Scale
Thousands of sensors, GPS trackers, and RFID readers generate billions of data points daily. IoT infrastructure debt grows silently as sensor networks expand.
AI Forecasting Economics
Demand forecasting, route optimization, and inventory prediction are AI-intensive features where inference costs scale directly with the number of SKUs, routes, and warehouses.
Integration Complexity
ERP systems, WMS, TMS, carrier APIs, and customs platforms create layered integration debt. Each new partner adds API maintenance cost forever.
How I Help Logistics Companies
- → Model real-time system infrastructure costs as tracking volume scales
- → Calculate AI forecasting COGS per SKU/route to optimize model economics
- → Quantify integration debt from carrier/ERP/WMS API maintenance