Enhancing Supply Chain Resilience And Performance: Leveraging Predictive Analytics And Erps In Vendor Selection

Abstract

Within the manufacturing sector, the supply chain is susceptible to a variety of external and internal risks. In this context, the susceptibility of the affiliated vendor can also lead to disruptions in the supply chain. Hence, the present study places emphasis on the utilisation of predictive analytics and enterprise resource planning (ERP) systems in the process of vendor selection, with the aim of enhancing both supply chain resilience (SCR) and performance within the manufacturing sector of Saudi Arabia. To fulfil this objective, qualitative data was gathered from employees who hold the responsibility of vendor selection within the manufacturing sector. A series of semi-structured interviews were undertaken with a sample of 10 employees who were purposefully selected. Following the interviews, a thematic analysis was conducted. This study identified six key themes: (a) the relationship between supply chain resilience (SCR) and performance challenges; (b) the impact of vendor selection on SCR and performance; (c) the vendor selection process; (d) the role of predictive analytics and enterprise resource planning (ERP) in vendor selection; (e) the integration of technologies; and (f) suggestions for enhancing SCR and performance. The findings indicate that the integration of enterprise resource planning systems (ERPs) and predictive analytics has a positive impact on inventory automation and the identification of vendors with greater resilience. This enables the procurement of necessary materials even in the face of disruptions in the supply chain. These techniques have also been identified as effective measures for mitigating potential supply chain risks in the future. This study also presents various practical and theoretical implications regarding supplier-customer relationships (SCR) and the process of selecting vendors.