This project will give students the opportunity to work directly on the operational side of logistics by analyzing JIT Logistics’ delivery workflows and recommending improvements in route planning, driver allocation, and cost management.

The goal is to design a data-driven optimization framework that reduces delivery times, lowers fuel costs, and improves customer satisfaction. Students will use real or simulated data to propose solutions around routing, scheduling, and efficiency, building a practical operations playbook that JIT can use as it scales.

What tasks will students need to complete to achieve the project goal?

Route Data Analysis:

• Collect and analyze data from past or sample delivery routes (travel time, fuel usage, delivery windows).
• Identify inefficiencies such as overlapping routes, underutilized vehicles, and delays.

Optimization Framework Development:

• Research tools and methods for logistics optimization (Google Maps API, route optimization software, Excel Solver, AI-based dispatching).
• Create a model or workflow that reduces travel time and fuel cost while meeting delivery deadlines.

Scheduling & Driver Allocation:

• Develop a scheduling system that balances workload across drivers.
• Recommend shift structures and delivery batching to improve efficiency.

Cost Reduction Strategies:

• Break down variable costs (fuel, maintenance, overtime wages) and propose ways to minimize them.
• Model potential savings if optimization recommendations are implemented.

Technology & Tools Assessment:

• Evaluate affordable route optimization and fleet management tools (e.g., Routific, Onfleet, Tookan).
• Provide a recommendation matrix comparing cost, features, and scalability for JIT Logistics.

Customer Experience Impact:

• Assess how improved routing and scheduling affects delivery reliability and client satisfaction.
• Recommend customer communication improvements (ETA notifications, tracking links).

Describe the expected project outcomes and deliverables

By the end of the project, students will deliver:

• A route analysis report highlighting inefficiencies and bottlenecks.
• An optimization model or workflow (Excel-based, or software prototype) showing improved delivery routes and schedules.
• A driver allocation and scheduling framework for better resource use.
• A cost savings report quantifying projected reductions in expenses.
• A technology recommendation matrix comparing 3–4 route optimization tools with pros/cons.
• A customer experience improvement plan tied to logistics reliability.
• A final Operations Efficiency Playbook and 10–15 minute presentation summarizing findings and recommendations.