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The article explores the effectiveness of Big Data and Artificial Intelligence (AI) in logistics forecasting. It emphasizes the advantages of these technologies in improving operational efficiency, predictive accuracy, and decision-making. The study includes a comparative analysis of traditional forecasting methods versus Big Data and AI-driven techniques. It highlights the experience of companies such as PepsiCo and XPO Logistics, demonstrating successful applications of predictive maintenance and route optimization. Additionally, an experiment was conducted comparing the use of AI and Big Data in reducing fuel consumption, improving demand forecasting, and minimizing downtime. The results underline the transformative potential of these technologies in logistics management, providing a framework for enhanced performance.

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Forecasting in Logistics Using Big Data and AI: Analyzing Effectiveness

  • 会议论文

  • 发表日期：

    2025年

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  • Dmytro Verner

摘要

The article explores the effectiveness of Big Data and Artificial Intelligence (AI) in logistics forecasting. It emphasizes the advantages of these technologies in improving operational efficiency, predictive accuracy, and decision-making. The study includes a comparative analysis of traditional forecasting methods versus Big Data and AI-driven techniques. It highlights the experience of companies such as PepsiCo and XPO Logistics, demonstrating successful applications of predictive maintenance and route optimization. Additionally, an experiment was conducted comparing the use of AI and Big Data in reducing fuel consumption, improving demand forecasting, and minimizing downtime. The results underline the transformative potential of these technologies in logistics management, providing a framework for enhanced performance.