Business Decisions through Models
As part of the Modeling Business Decisions course, I worked on two data-driven assignments applying advanced decision-making frameworks, including sensitivity analysis, decision trees, and Monte Carlo simulations. These projects involved evaluating complex business challenges under uncertainty and developing optimal strategies for implementation
TransAtlantic Airlines: Overbooking Optimization
This project analyzed overbooking policies for TransAtlantic Airlines, focusing on minimizing costs and managing passenger no-show variability. Using sensitivity analysis and Monte Carlo simulations, we compared three overbooking strategies to determine the most cost-effective approach. The optimized policy reduced risks and achieved the lowest average costs, aligning with real-world industry practices.
Recreational Properties: Strategic Land Investment
This assignment evaluated a strategic land investment in White Mountain under significant uncertainty. Using decision trees and sensitivity analyses, we calculated expected monetary values for different outcomes, such as lease approvals and development scenarios. The analysis guided an optimal decision-making strategy balancing risk and reward while addressing external legal and reputational challenges.
