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We’ve identified 6 drivers impacting the value of flight data which could explain the current tension on the travel data market: assets for sale, investments in travel tech, etc.

Background

As a background, we categorize flight-related data in 3 segments: commercial data, schedule data and flight status data. Each category corresponds to a type of questions by data users:

  • How many people fly from where to where? At what price for each flight?

  • How many flights are scheduled from where to where? With how many seats available?

  • Where is each aircraft on each flight? What flight is on-time or delayed?

Datasets

Each data set is aggregated by different stakeholders using specific methods:

  • Commercial data comes from the analysis of all tickets sold by airlines
  • Schedule data comes from the filing of schedules by airlines
  • Flight status data comes from the analysis of communication (ADS-B) messages sent by aircraft

Drivers

Our research shows the following 6 drivers impacting the value of flight data:

  1. API vs filing: while historically airlines have filed static data in central banks, new enriched data is now available through APIs in real-time
  2. Flight vs ancillaries: commercial data has focused on the price of the seat, but the value and profitability of a flight now comes from the sale of ancillaries
  3. Dynamic scheduling: airline schedules are filed one year in advance, for operational reasons such as airport slots, but disruptions, due for example to travel restrictions, require more agile scheduling techniques
  4. Data aggregation: data was aggregated in silos, for example filing of schedules, and opportunistically, for example a stakeholder processing tickets ends up selling the ticket data, whereas data can be aggregated across silos and combined to algorithms that extract insights
  5. CO2 emissions: the decarbonation of air travel introduced a new category of flight data with the measure of CO2 emissions, which relates not only to aircraft and engine data, but also to flight length (e.g. itinerary change due to restrictions) or to fuel type (i.e. SAF), and involves offset prices.
  6. Cyber-security: the quality and accuracy of data is at risk, for example the protection of airline websites from bots impacts the ability to scrape their content to find live fares

Summary

The chart below summarizes the 3 segments of flight data and the 6 impacting the value of flight data. For more information on flight data and travel data, contact us.