Alaska Airlines, the 7th largest passenger airline in the US, employs around 1400 pilots and first officers. It requires extensive planning and forecasting to plan for flight trips by accommodating varying schedules of the pilots. Over- or under-estimation of pilot’s flying time impacts the overall costs, and it needs to be utilized efficiently as hiring pilots is expensive.

After extensive research we came up with a solution in the form of a predictive analytics algorithm. It considers the pilot’s historical data comprising of variables such as vacation and training hours, and helps in predicting the open flying time for the pilots. This solution will automate the process of calculating open flying time and will assist the team at Alaska to prepare pilot’s monthly schedule in advance. The nearly accurate estimation will lead to elimination of superfluous costs resulting from over/under estimation of open flying time and will ultimately lead to heightened pilot productivity.