Corporate Blog

Using deep learning models to reduce crew standby costs in airline operations

Using deep learning models to reduce crew standby costs in airline operations
Airlines factor standby crew in their planning as a buffer in case unexpected events cause deviations to operational plans, such as disruptions or last-minute crew roster changes. In these situations, standby buffering is a critical part of crew planning to safeguard the passenger experience and brand reputation. Additionally, the cost of reassigning crews to flights is significantly higher without standby buffers. Balancing crew standbys with actual utilization on the day of operations is challenging. Our analysis indicates that, on average, only 30%-40% of crew standbys are used, representin...
Read More

How a new approach to airline crew tracking helps optimize costs

How a new approach to airline crew tracking helps optimize costs
With the advent of Low-Cost Carriers, new business models emerged that fundamentally changed the way airlines operate. Increased pressure on cost reduction and optimized spending is now firmly on the agenda. Yet, a fine line exists between controlling costs and delivering quality service that drives customer satisfaction. Crew management sits between both. In our recent "Applying scenario-based planning in airline operations for crew pairing optimization"white paper, we looked at how "what-if" models help build cost-effective pairing. So let´s dig a little deeper into optimized spending during...
Read More