Prescriptive Analytics for Product Lifecycle Collection
Retail
Project Type:
Data Science/Business Analytics
Project Sponsor:
Global Watch Company
Students helped this business with examining the lifecycle of their product collections, including determine when the collections should ramp up, peak, and ramp down, finding lifecycle trends and segment by product collections, determining when the company should launch their new collection, understanding performance by sales channels, determining if certain collections work in certain sales channels better than others, and predicting the optimum collection mix based on past performance.
Keywords: Product Lifecycle, Sales, Trends
Spring 2022
Faculty Leads
Christopher Policastro
Industry Assistant Professor
Tom Mazzone
Director of Industrial Engineering, Industry Professor