Case Study: a global logistics carrier improves crew cost control with Sparq's AI-driven reserve planning model

Network Planning Efficiencies Bring $200 Million in Annual Savings to Large Logistics Client

The customer is a global logistics carrier that relied on manual planning to allocate costly reserve flight crews without a measurable accuracy baseline. Sparq was engaged to address this challenge and improve cost control and operational precision.

Sparq built an AI-driven probability model utilizing Google Cloud Platform and BigQuery to forecast reserve needs and benchmark performance against real outcomes. This solution created a data-driven path to optimize standby staffing, providing the customer with a method to control their long-term crew costs effectively.