Date of Award
Spring 2020
Degree Type
Thesis
Department
Moore School of Business
Director of Thesis
David Precht
First Reader
Pearse Gaffney
Second Reader
Pearse Gaffney
Abstract
This paper attempts to analyze how local alcohol vendors maintain their inventory throughout the year in Columbia, attempting to manage factors such as the season, sporting events, and other public gatherings and events. The research question resulted in contacting over 30 local alcohol vendors in Columbia, to ask them questions regarding their strategy in alcohol inventory management. The responses to these questions were then used to organize the vendors into groups by whether or not they utilize a reorder point to purchase/brew alcohol, or if they utilize periodic ordering. The vendors were also asked to rank the seasons from most to least alcohol sold. The analysis determined that vendors should utilize mathematical models such as the Newsvendor model in order to make accurate predictions to how much alcohol they should order, as opposed to relying on anecdotal evidence to estimate the amount that they should order. The report concludes with three recommendations, including that the vendors should track the amount of alcohol that they order on a periodic basis, implement a model in order to aid with inventory management and demand planning, and conduct an accurate pre and post analysis of performance of the entire process of maintaining records and using models to predict inventory and demand planning. These recommendations all serve to help the vendors become more profitable and more efficient.
First Page
1
Last Page
26
Recommended Citation
Amore, Angelo J., "Analyzing Local Alcohol Vendor Inventory Management Strategy" (2020). Senior Theses. 320.
https://scholarcommons.sc.edu/senior_theses/320
Rights
© 2020, Angelo J Amore
Included in
Business Administration, Management, and Operations Commons, Business Analytics Commons, Entrepreneurial and Small Business Operations Commons, Food and Beverage Management Commons, Management Sciences and Quantitative Methods Commons, Operations and Supply Chain Management Commons, Strategic Management Policy Commons