Leveraging Business Analytics for Strategic Merchandising Decisions in Fashion Retail - Begum, Nazma; Ali, Md. Mokshud (International Journal of Business and Economics, 2024)
The application of business analytics to strategic merchandising decisions in the retail fashion industry is investigated in this study. Using data-driven insights has become essential for improving product assortments, pricing strategies, and inventory management as the business faces increasing complexity due to rapidly changing consumer preferences, seasonal demand changes, and more competition. The main goal of this study is to examine how fashion retailers may use business analytics to strengthen their merchandising plans, increase operational effectiveness, and increase profitability. The application of real-time inventory management systems, dynamic pricing models, and predictive analytics in the retail fashion industry is highlighted. This study attempts to provide actionable insights that enable retailers to make better-educated, data-centric decisions by addressing the opportunities and difficulties related to these sophisticated analytical tools. Despite its potential to improve retail operations, a major problem identified in this study is the underutilization of business analytics in merchandising decisions. To solve this issue, a qualitative research methodology was used to evaluate the current state of analytics integration in fashion retail using secondary data from industry reports, case studies, literature reviews, and other pertinent sources. The results show that using analytics has many benefits, including better demand forecasting, more accurate pricing, and more effective inventory management. However, the study also identifies barriers such as difficulties integrating data, the need for qualified staff, and moral dilemmas about the privacy of customer data. By shedding light on the efficient use of business analytics in the retail fashion industry, this study enhances theoretical knowledge and real-world implementation. It makes recommendations for removing adoption hurdles while highlighting the necessity of combining analytics with human knowledge and creativity. A better understanding of how data-driven decision-making affects merchandising procedures in fashion retail is one of the theoretical ramifications. Practically, the study suggests tactics for retailers to maximize their use of analytics to stay competitive in a market that is changing quickly. This study admits some limitations despite its insightful findings, most notably its reliance on secondary data that might not accurately represent the most recent advancements in technology or industry trends. Future studies should investigate how analytics affect consumer behavior and retail performance over the long run, as well as how small and medium-sized businesses may use these technologies efficiently.