Big Data Analytics in Supply Chain Ecosystems: Emerging Innovations and Strategic Pathways

Abstract

To improve predictability, hazard of risks, and conservation activities, this investigation aims to explore the function of Big Data Analytics (BDA) in contemporary logistics habitats. The goal of the investigation is to comprehend how BDA facilitates tactical flexibility and informed choices in more intricate international production networks. The study is based on the concept of Industry 4.0 principles and fueled by data control of oversight, chains, which include forecasting, IoT-enabled surveillance, and powered by AI analysis. The versatility of imagery processing, grouping, and machine learning approaches for optimizing supply chains is demonstrated by earlier research in cross-domain areas including medical and farming. This study adopts a mixed-method approach, combining literature synthesis of 52 peer-reviewed articles (2015–2024) with a quantitative analysis of the “Global Supply Chain Data 2023” Kaggle dataset. The dataset comprises supplier lead times, demand variability, and transportation costs for 500 suppliers and 200 customers. Data processing and visualization were conducted using Python (pandas, sklearn) and Tableau to assess predictive accuracy and cost reduction. According to the findings, implementing BDA may improve timely fulfillment from 85% to 93%, lower predicted errors (MAPE) from 18% to 11%, and save storage expenses by 12% and 15%, respectively. These results show how BDA may improve productivity and adaptability, which is consistent with cross-domain data from recognized patterns apps, powered by AI BI instruments, and IoT surveillance. The investigation offers firms useful advice on how BDA principles can increase taking decisions rapidity, savings, along with supply system robustness. The investigation supports prospective creative routes and deployment methods by emphasizing uptake barriers that include expenses lack of skills, along with information reliability. By illustrating the factual effects of BDA in manufacturing habitats and the applicability of cross-domain AI and Internet of Things approaches for enhancing supply network processes, this study adds to the body of study. The study offers a strategic outlook for building intelligent, adaptive, and future-ready supply chains, supporting both academic research and practical decision-making.