Role of BDA in Improving Supply Chain Resilience

In the modern world of interconnected and globalized businesses, adapting and overcoming unexpected disruptions has become a crucial factor in maintaining competitiveness. As a result, supply chain resilience has become a vital aspect of supply chain success. The correlation between resilience and value is well-documented. The ability to rebound from challenges and disruptions has consistently allowed top-performing companies to outperform their competitors in terms of Total Shareholder Return (TSR) during times of crisis, regardless of their industry. This research paper explores the potential of utilizing Big Data analytics—which refers to examining large and varied datasets to uncover hidden patterns, correlations, and insights—and predictive modeling, a statistical technique that uses historical data to forecast future outcomes, to strengthen supply chain resilience. This research paper explores the potential of utilizing Big Data analytics and predictive modeling to strengthen supply chain resilience. By implementing advanced data technologies, this study seeks to equip organizations with the ability to proactively identify, evaluate, and mitigate risks, thereby enhancing the overall resilience of their supply chains. Integrating Big Data analytics and predictive modeling can revolutionize traditional supply chain management methods, empowering businesses to survive and thrive in the face of uncertainties and disruptions.