Optimizing food and FMCG supply chains: A dual approach leveraging behavioral finance insights and big data analytics for strategic decision-making

Optimizing food and Fast-Moving Consumer Goods (FMCG) supply chains is crucial for enhancing efficiency and responsiveness in today’s dynamic market. This paper presents a dual approach integrating behavioral finance insights with big data analytics to refine strategic decision-making processes. Behavioral finance provides valuable understanding of how psychological factors and biases influence decision-making among supply chain stakeholders. By analyzing patterns such as overreaction to market trends or herd behavior, companies can anticipate and mitigate irrational decision-making that may lead to inefficiencies and supply chain disruptions. Big data analytics, on the other hand, enables organizations to process and analyze vast amounts of data from various sources, including sales figures, inventory levels, and consumer behavior. Advanced analytics techniques, such as predictive modeling and machine learning, offer actionable insights into demand forecasting, inventory management, and logistics optimization. Integrating these insights with behavioral finance principles allows for a more comprehensive approach to managing supply chain risks and opportunities. This dual approach supports strategic decision-making by addressing both the human and data-driven aspects of supply chain management. For instance, understanding cognitive biases can help in designing better forecasting models and inventory policies, while big data analytics can provide real-time insights to correct course deviations and align supply with actual demand patterns. The synergy between these methodologies enhances overall supply chain resilience, reduces costs, and improves service levels. The paper discusses practical applications of this integrated approach, including case studies where companies have successfully employed behavioral finance principles alongside big data analytics to optimize their supply chains. It also highlights the challenges and considerations in implementing this dual strategy, offering recommendations for best practices and future research directions.