Redesigning Logistics Data with Artificial Intelligence
Table of Contents 1- Introduction: From Warehouse Shelves to Data Shelves — The hidden cost of data chaos in logistics. The “We have data but can’t use it” syndrome. 2- AI in Logistics: More Than a Trend — The real problem: Not the algorithm, but the data structure. Real-world applications beyond the AI hype wave. 3- Data Architecture: From a Messy Warehouse to a Smart Warehouse — Making data from different systems speak the same language. Master data management and data integrity challenges. 4- Forecasting and Optimization — Demand forecasting: Surplus stock or shortages? Route and fleet optimization: Balancing fuel savings with customer satisfaction. 5- Real-Time Decision Mechanisms — Processing sensor, IoT, and telemetry data instantly. The clash between AI saying “decide now” and operations culture saying “wait for approval.” 6- Data Quality and Security — The disaster of correct decisions based on incorrect data. Cybersecurity threats in logistic...