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Purpose/Impact

As companies plan to diversify supply chains, this research will analyze factors that lead to growth and open the door to further possibilities in apparel manufacturing. With this data, Baxter and Chapman will create and test predictive analytics to identify countries that may be positioned for increasing growth in apparel production. In addition, as the international environment is dynamic and ever changing, the team is exploring the use of an artificial intelligence (AI) platform to factor in political, cultural, economic, and environmental events to determine their impact on growth—information which will provide fast and factual information to guide companies in their sourcing decisions.

Outcomes/Accomplishments

The research duo is identifying the quantitative and qualitative factors that impact sourcing success or failure, and developing a comprehensive process for collecting and analyzing this data. By defining the type of data/material that needs to be analyzed to incorporate dynamic changes in the market, they will give industry members a more thorough, detailed understanding of the apparel manufacturing market and the ramifications of growth within it. The result will be a predictive tool that incorporates dynamic changes in the market to assist apparel companies with sourcing decisions, with a focus on cotton and man-made fibers. While working through their timeline, the team will keep a watch for competitive product innovations that could influence the predictive tool’s efficacy, and they will test the prediction model against publicly available import data. Utilizing an AI platform will allow them to incorporate the assessment of non-data driven factors, leading to a more resilient and comprehensive product.

STATUS UPDATE

Throughout the course of this project, Baxter and Chapman’s understanding of the limitations of pure data-driven assessments will expand, as will their experience in using AI to inform business decisions—such as the rapid assessment of external events. Many of the components of this research and the predictive analytical tool can be integrated into course content, thereby exposing students to new instruments used to solve business problems.

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