Revenue management and Route Planning
The percentage of occupancy defines the profitability of airlines. Most often than not, flights go empty if there are direct flights connecting places in different continents. One solution to increase the occupancy rate is to have connecting flights based on forecasting demand over a time period.
Understanding traveler demand for specific city pairs and pricing flights are among the main problems airlines solve to survive. To do that carriers must consider thousands of factors when analyzing data. While analysts still can use traditional statistical approaches.
Data science allows for more sophisticated ways to accomplish demand analysis. IATA suggests that airlines can use traveler behavioral data, abandon searches on the online travel agents, and metasearch sites or social media chatter can help define leisure demand.
Benefits for the company
Business Impact :
– Increased occupancy rate
– Increased profits
– Reduction in maintenance cost
– Effective crew utilization
– Increase in customer satisfaction
Type of expertise/ AI domain
Network analysis performed on flight & passenger traffic helps in identifying effective connecting routes thereby improving occupancy rates
Measures of centrality to identify the most cost efficient route by connecting flights with the airports that are most feasible
Perform data simulation with what-if analysis for effective crew management
Analysis on weather changes of various regions helps in effective routing, thereby reducing flight maintenance cost
Internal data required
Traffic, Demand data
External data possible
Weather data, Search Data