About
Starting Semester: Fall 2025Assigned: No
Location: New York City
Global Ops
Client Profile
GLOBAL OPS is a premier security services agency based in New York City, with a robust global presence. Specializing in personal protection, security consulting, risk analysis, and advanced safety measures, we utilize cutting-edge technology and industry-leading training to ensure unparalleled protection for our clients.As part of our ongoing commitment to innovation, we have developed GOPS ONE, our latest technological advancement—a comprehensive enterprise resource planning (ERP) platform. GOPS ONE is designed to elevate the client experience, streamline operations, and enhance agent accountability and communication. This platform reflects our mission to transform the security industry through technology, ensuring that every client receives the highest standard of service.
With a growing demand for security solutions both nationally and internationally, and a continued focus on technological investments, GLOBAL OPS has experienced rapid expansion in recent years. We are poised to redefine the future of security, combining the best of human expertise with cutting-edge technology to deliver world-class protection and peace of mind.
Project Description
Problem:The scheduling team currently dedicates significant time each week to managing shift assignments for over 60 clients. While the task is completed, the existing approach lacks optimization in terms of maximizing operational efficiency, profit margins, and agent satisfaction. This suboptimal system results in inefficiencies, contributing to higher agent turnover and increasing challenges in client service delivery. The current methodology does not adequately address key factors such as resource allocation, agent well-being, or the alignment of shift schedules with client needs, ultimately leading to a cycle of disengagement and operational friction.
Opportunities:
By leveraging historical data and real-time insights from GOPS ONE, we can develop and implement an optimization-based scheduling model to enhance workforce efficiency. Using constraint-based routing algorithms and integer programming, this model will optimize shift assignments by balancing key factors such as labor costs, agent availability, skill requirements, and client demand.
By integrating directly with the GOPS ONE scheduling system, the solution will minimize idle time, reduce scheduling inefficiencies, and streamline workforce allocation. Additionally, the model will incorporate agent preference modeling and fatigue management constraints to enhance job satisfaction and reduce turnover. This data-driven approach ensures a dynamic, adaptive scheduling framework that not only improves operational efficiency but also maximizes profitability and service quality.