A Study on Evaluating the Accuracy of Qualitative vs. Quantitative Demand Forecasting Methods in Retail

This research paper examines the accuracy of qualitative and quantitative demand forecasting methods in the retail sector. The study focuses on two major Indian industries—FMCG (Fast-Moving Consumer Goods), represented by Hindustan Unilever Limited (HUL), and the apparel sector, represented by Myntra. Using real-time data and analytical models such as ARIMA, Random Forest, and LSTM networks, the paper evaluates the effectiveness of different forecasting approaches. The findings highlight the strengths and limitations of each method and provide recommendations for businesses to optimize demand forecasting accuracy.