Thesis Abstract

Abstract
The retail industry operates in a highly competitive environment where effective supply chain management is crucial for success. This study investigates the utilization of data analytics to enhance supply chain management in the retail industry. The objective is to explore how data analytics can improve the efficiency, responsiveness, and overall performance of supply chains in retail organizations. The research begins with a comprehensive review of the existing literature on supply chain management, data analytics, and their intersection in the retail sector. The literature review highlights the importance of leveraging data analytics tools and techniques to optimize supply chain operations and decision-making processes. Subsequently, the research methodology section outlines the approach taken to gather and analyze data for this study. The methodology includes a detailed description of the research design, data collection methods, data analysis techniques, and the sampling strategy employed to ensure the validity and reliability of the findings. The findings of this study reveal that data analytics can provide valuable insights into various aspects of supply chain management, including demand forecasting, inventory management, logistics optimization, and supplier relationship management. By harnessing the power of data analytics, retail organizations can make more informed decisions, streamline their operations, reduce costs, and enhance customer satisfaction. The discussion section delves into the implications of the study findings and their practical significance for retail managers and decision-makers. It also explores the potential challenges and limitations of implementing data analytics in supply chain management and offers recommendations for overcoming these obstacles. In conclusion, this thesis underscores the transformative potential of data analytics in enhancing supply chain management practices within the retail industry. By leveraging data-driven insights, retail organizations can gain a competitive edge, improve operational efficiency, and adapt to changing market dynamics more effectively. This research contributes to the growing body of knowledge on the strategic use of data analytics in supply chain management and offers valuable insights for academics, practitioners, and policymakers in the retail sector.

Thesis Overview

The research project titled "Utilizing Data Analytics to Enhance Supply Chain Management in Retail Industry" aims to investigate the application of data analytics in improving supply chain management practices within the retail sector. This study recognizes the growing significance of data analytics in modern business operations and seeks to explore how retail companies can leverage data-driven insights to optimize their supply chain processes. The retail industry is characterized by complex and dynamic supply chains that involve various stakeholders, including suppliers, manufacturers, distributors, and retailers. Effective supply chain management is crucial for ensuring timely delivery of products, minimizing costs, and enhancing overall operational efficiency. By incorporating data analytics tools and techniques, retailers can gain valuable insights into their supply chain operations, identify potential bottlenecks, and make informed decisions to streamline processes and improve performance. The research will begin with a comprehensive literature review to explore existing studies and frameworks related to data analytics, supply chain management, and their intersection in the retail industry. This review will provide a theoretical foundation for the study and identify key concepts, trends, and challenges in the field. The research methodology will involve a mixed-method approach, combining quantitative analysis of supply chain data with qualitative interviews or surveys with industry experts and retail practitioners. By collecting and analyzing both quantitative and qualitative data, the study aims to gain a holistic understanding of how data analytics can be effectively utilized to enhance supply chain management practices in the retail sector. The findings of the research will be presented and discussed in detail in the subsequent chapters, highlighting the key insights, trends, and implications for retail practitioners. The discussion chapter will critically evaluate the results, compare them with existing literature, and propose practical recommendations for retail companies looking to implement data analytics in their supply chain operations. In conclusion, this research project seeks to contribute to the existing body of knowledge on the application of data analytics in supply chain management within the retail industry. By highlighting the potential benefits and challenges of adopting data analytics tools, the study aims to provide valuable insights and recommendations for retail companies seeking to enhance their supply chain performance and competitiveness in the digital age.