Thesis/Capstone
Publication Date
Authored by
Amine Tmimi, Yaniliz Valentin
Advisor(s): Jim Rice
Topic(s) Covered:
  • Healthcare
Abstract

A leading medical device company has experienced a consistent decline in profit margins across its product categories. Factors such as high inventory costs, complex Supply Chain operations, and challenges in managing a highly complex product portfolio have contributed to the erosion of gross profit. This study aims to uncover and address the factors eroding gross profit by exploring three key research questions: How can the company effectively segment its Endosurgery products to identify profit-eroding factors? What are the primary factors affecting the profitability of these products? Can unsupervised machine learning techniques, inspired by the BCG and Category Role matrices, provide a more comprehensive understanding of the factors influencing the business unit's financial performance compared to traditional approaches? The findings of this study contribute to the development of actionable strategies for enhancing product portfolio management and improving financial performance in the medical device industry. Within the product portfolio, 62% of the total product base codes have dilutive gross profit, driving further exploration of the factors influencing that behavior using Machine Learning techniques.
 

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