AI-Driven Data Analytics to Mitigating Supply Chain Disruption: Insights from the Aftermath of the COVID-19

Abstract

This study explores ways to address the risk of supply chain disruption by applying Artificial Intelligence data collection and analysis in the wake of COVID-19. The outbreak disrupted many organizations' supply chains, and supply chain disruption is an extremely serious issue for organizations. Traditional supply chain risk management is based on analyzing historical understanding of the extent of an event's impact. However, when faced with a rare and severe catastrophic event such as COVID-19, traditional approaches struggle to quantify the risk due to a lack of historical data, leading to serious losses for organizations. Describing the supply chain through mathematical modeling and data analytics allows predictions to be more realistic and forward-looking, helping to counter or respond to the risk of supply chain disruption during a pandemic. These strategies not only reduce the risk of supply chain disruptions faced by organizations but also drive digital transformation and improve the competitiveness of organizations. This paper highlights how AI-based data collection and analysis methods in the context of epidemics can help companies better respond to the risk of supply chain disruption and achieve sustainable development.