Optimizing Supplier Selection Process Using Data Analytics in Purchasing and Supply Chain Management.

Thesis Abstract

Abstract
This thesis focuses on the optimization of the supplier selection process in purchasing and supply chain management through the application of data analytics. The importance of selecting the right suppliers cannot be overstated, as it directly impacts the efficiency and effectiveness of the entire supply chain. By leveraging data analytics tools and techniques, organizations can make informed decisions that lead to cost savings, improved quality, and enhanced supply chain performance. Chapter 1 provides an introduction to the research topic, discussing the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. The chapter sets the stage for the research by highlighting the critical role of supplier selection in supply chain management and the potential benefits of utilizing data analytics in this process. Chapter 2 presents a comprehensive literature review on supplier selection, data analytics, and their intersection in purchasing and supply chain management. The chapter explores existing theories, models, and studies related to supplier selection criteria, decision-making processes, data analytics applications, and the impact of technology on supply chain management. Chapter 3 outlines the research methodology employed in this study, including the research design, data collection methods, data analysis techniques, and sampling procedures. The chapter details how data analytics tools will be utilized to optimize the supplier selection process and improve supply chain performance. Chapter 4 presents the findings of the research, showcasing the outcomes of applying data analytics to supplier selection in real-world scenarios. The chapter discusses the key insights gained, challenges faced, and opportunities identified through the implementation of data-driven supplier selection strategies. Chapter 5 concludes the thesis by summarizing the key findings, discussing the implications of the research, and providing recommendations for future research and practice. The chapter emphasizes the significance of data analytics in enhancing supplier selection processes and improving overall supply chain performance. Overall, this thesis contributes to the existing body of knowledge in purchasing and supply chain management by demonstrating the value of data analytics in optimizing the supplier selection process. The research findings provide valuable insights for organizations seeking to improve their supply chain operations and achieve competitive advantage through data-driven decision-making.