Abstract
This study addresses demand forecasting challenges at MIXUE, a beverage chain, focusing on issues like high subjectivity and significant prediction errors that lead to market volatility and operational inefficiencies. Despite the critical role of the food and beverage industry in economic growth, MIXUE faces intense competition, emphasizing the need for accurate demand forecasting. This research aims to analyze historical sales data using time series analysis to identify patterns, optimize demand forecasting methods, and reduce data volatility. The study develops a demand forecasting model to align supply and demand, improve revenue management, and mitigate risks associated with uncertainty. Results highlight the importance of precise demand forecasting in enhancing operational efficiency, reducing costs, and maximizing profits. This research provides actionable insights for MIXUE to better anticipate market trends and strengthen its competitive position.
Published Version
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