A STUDY ON THE IMPACT OF SEASONAL TRENDS ON RETAIL PRODUCT DEMAND FORECASTING AT D-MART, NAGPUR REGION

Abstract

Retail demand forecasting is a critical component of inventory management and operational efficiency in the retail sector. This study explores the influence of seasonal trends on demand forecasting for retail products at D-Mart, located in the Nagpur region. The research identifies how various factors such as holidays, weather patterns, and cultural events contribute to fluctuations in demand for different product categories throughout the year. By analysing historical sales data, the study investigates the accuracy of existing demand forecasting methods and how they incorporate seasonal variables. Through a combination of quantitative and qualitative research methodologies, including statistical analysis and expert interviews, the study provides valuable insights into the optimization of forecasting models to account for seasonal demand changes. Findings suggest that understanding seasonal patterns allows retailers like D-Mart to better align their inventory management strategies with consumer demand, thereby minimizing overstocking and stockouts. Furthermore, this study highlights the importance of adapting forecasting models to local market conditions, considering unique regional events and cultural trends in Nagpur. The results offer practical recommendations for improving demand forecasting accuracy, optimizing product availability, and enhancing customer satisfaction in the retail industry. This research not only contributes to the existing body of knowledge in retail management but also provides actionable strategies for retail chains to improve operational efficiency through more accurate demand predictions.