We have just published our largest data visualization to date. From 2017 through February 2019, our model processes over 8.5 million flights among US airlines. The model has three pages listing on-time performance by aircraft type, OEM, and airline.
The following table is part of this model. We use color to identify how well an airline is doing in terms of its on-time performance. The 2019 data reported is through February, and will be updated as DoT publishes its own updates.
The model allows a reader to select an airline and see which tail numbers are among the Top 20 most delayed for 2017, 2018 and 2019 YTD February. We use the fleet tracking information from FlightRadar24 to keep track of tail numbers in service. The data shows that regional jets are the most frequently delayed.
We also show heat maps of the US, where once a reader selects an airline, you can see where each network has been experiencing delays. This is useful information as a typical US airline operational minute is worth about $90. Every delayed minute (we use arrival delays in our model) is an operational cost that is very difficult to recover. Airline profitability is driven by execution of schedule – deviations from the schedule are common because of weather and other exogenous issues. Our model helps to show how well, if at all, airlines are able to recover.
For our subscribers, please use this link to access the model.
Co-Founder AirInsight. My previous like includes stints at Shell South Africa, CIC Research, and PA Consulting. Got bitten by the aviation bug and ended up an Avgeek. Then the data bug got me, making me a curious Avgeek seeking data-driven logic. Also, I appreciate conversations with smart people from whom I learn so much. Summary: I am very fortunate to work with and converse with great people.