Optimizing Inventory of Perishable Goods by Forecasting Daily Sales

Project Details


Fall 2023


Hsuan-Jung Lin (Tiffany), Yuan-Jie Fong (Francis), Kai-Yi Chu (Kyle), Chieh-Jui Ho (Jerry)




Presentation recording

Business Problem
Retailers often grapple with the challenge of balancing inventory levels, especially for perishable goods. Overstocking leads to waste and financial loss, while understocking can result in missed sales opportunities. Our focus is on providing forecast suggestions for effective inventory management that is crucial for financial success, sustainability, and maintaining a positive brand image among eco-conscious consumers.
The project aims to optimize inventory management at a Maryland store of a multinational retail chain by forecasting daily sales of the three top-selling perishable goods sold in-store. The forecasts are to be generated on a weekly basis to guide inventory decisions.

We have utilized daily sales data from a leading multinational retail chain in the USA, provided by Nuqleouse, a retail technology solutions firm. The analysis concentrates on the three top-selling perishable items sold through the in-store channel at the Maryland location.

Forecasting Solution
Our approach involves advanced analytics to forecast daily sales on a weekly basis. This predictive model allows for more accurate inventory planning, minimizing the risk of overstocking and the associated costs and waste. The forecasting is sensitive to over-forecasting risks, which is crucial for perishable goods due to their limited shelf life and the financial implications of unsold stock.

To maximize the effectiveness of our advanced analytics forecasting model for perishable goods inventory management, it is crucial for the store to maintain a robust and consistent data collection process to prevent inaccuracies due to missing data. Equally important is the implementation of a digital inventory record system that is updated in real-time, ensuring seamless integration with our weekly forecasting updates. By adopting this forecasting solution, the store can expect to see a reduction in waste, improved financial performance, and a boost in its reputation among eco-conscious consumers.

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