Business Intelligence for Airlines

Aircrafts, customers, ground operations are just the start for business intelligence

According to SITA, the world’s leading specialist in air transport communications and information technology, more than half of passengers would use their mobiles for flight status, baggage status and airport directions, and majority of airlines and airports will offer these services using business intelligence analytics. Information updates like Bag status is offered by 61 percent of airlines, and 79 percent of airports provide status notifications like queue times through security and walking times to gates. All airlines and 90 percent of airports are investing in business intelligence systems to better serve the needs of their passengers, although more progress is needed to make these investments count.

Predictive airport analytics, customer satisfaction

Predictive and Descriptive Analytics

A combination of Business Intelligence, Predictive and Descriptive Analytics will help make the real difference, along with optimizing the use of infrastructure and space at airports.

Airlines and airports should measure themselves in 4 important categories of business intelligence:

Data Access & Management

Infrastructure

Data Presentation

Governance

“All airlines and 90 percent of airports are planning to make business intelligence investments in the coming three years.”

– says leading industry analysts

 

Using BI, airlines and airports will be more proactive in managing ‘irregular events’ by analyzing past events and combining live data feeds from multiple sources to predict future events, and take preventative action before they occur. Not only can the BI tools provide descriptive analytics (i.e., analytics comparing the past to the present) but also predictive analytics (i.e. analytics predicting the future).

According to global standards, the average cost per passenger for LCCs (low cost carrier) should be $35 lower than that of FSCs (full service carrier). But this is contingent on better utilization of aircraft through faster turnarounds.

What can predictive analytics bring?

  • Project the future utilization based on seasonality factors, nature of customer segments served currently, past trends and patterns, etc.
  • Predict in advance the viability of building airports specially for LCCs which would give scope for reduction of airport charges and in turn a reduction in prices of tickets

Tackling airline challenges with analytics

Airline challenges with data intelligence

Operations Efficiency

Operations engineers at major airlines, responsible for a fleet of aircraft, must constantly weigh the cost and disruption of ad hoc maintenance against the risk and even higher cost of technical failures.

Fleet Status

Fleet technical health predictions and reports on remaining life for critical engine components, based on multiple machine learning models, aircrafts’ Quick Access Recorder & other data sources.

Optimization

Visually rich representations to provide an overview of the flight plans and locations to help decide where an aircraft should be serviced and which other aircraft is best positioned to replace it.

Visualization

Custom Sankey charts and striking 3D heat map rationalize fleets’ different KPI weightings based on types of air frames. These visuals provide insights, intuitive to those working in the airline industry.