Leveraging Data Analytics for Decision Making: A Review of Global Practices and Emerging Trends in The Food Processing Industry

Following the Fourth Industrial Revolution, data analytics has become a transformative influence across global industries, including the food processing industry. This study conducts a systematic review of international practices and emerging trends in utilizing data analytics for decision-making in the food processing industry, concentrating on literature from the last 15 years. The study consolidates insights from 42 peer-reviewed articles to analyse the extent, applications, advantages, and obstacles of big data tools in domains including quality control, predictive maintenance, supply chain optimization, product innovation, and sustainability. The review shows an increasing dependence on real-time analytics, machine learning, and IoT technologies to enhance operational efficiency and strategic agility. It also highlights obstacles, such as integration intricacies, data governance issues, and infrastructural constraints, especially in developing nations. Based on the analysed evidence, the study proposes a policy framework to direct stakeholders—industry leaders, policymakers, and technology providers—toward more effective and ethical utilization of data analytics in decision-making. This framework seeks to promote digital inclusion, innovation, and resilience within the global food processing industry. Keywords: Data analytics, decision-making, food processing industry, big data, policy framework.