Overcoming The ‘Planning Fallacy’ and Improving Flight Turnaround Times

We’ve all been there. Rushing to find our passports in a long-lost drawer, getting stuck in a traffic jam, or waiting impatiently in a check-in queue that stretches into infinity. Far too often we find ourselves in a sprint towards our gate, desperately trying to make our flight on time. Only to find our flight is delayed! And the truly frustrating part? It happens time and time again, enough to give us a strong sense of a déjà vu.

Just like individuals, airlines and airports continue to find themselves in the same dilemma – faced with the all-too-familiar flight delay. A recent 2023 report highlighted that major US airlines consistently fail to meet anticipated turnaround times. Discrepancies reach as high as 19%. One of the reasons for this could be that airlines consistently miscalculate turnaround times, underestimating them by a significant margin of 9.5% to 18.8% [1].

Whether it's people or airlines, there seems to be a common trend: underestimating time. One possible contributor is the Planning Fallacy.

The Planning Fallacy

This cognitive bias was identified by Kahneman and Tversky in 1979, and is defined as an optimistic underestimation of the time needed to complete future tasks. Factors like optimism bias and overconfidence contribute to this phenomenon. And just like passengers often think they'll make it to their gate faster than they do, airport and airline staff might also underestimate how long it takes to get planes ready, leading to delays.

Overcoming The Planning Fallacy With AI

To begin with, it’s important to understand the complexities of an aircraft turnaround, as well as the importance of visibility. A successful aircraft turnaround involves a multitude of tasks and sub-tasks, with many interdependencies. The status of passengers and luggage for example, has a direct impact on the readiness of an aircraft. When faced with scenarios like a late passenger - stakeholders are often faced with decisions they must make in the dark - wait for the passenger or remove their luggage – what will take longer? But without knowing the location of the passenger or the luggage in the terminal, the risk of sub-optimal decisions is likely. ?

To overcome the Planning Fallacy and enhance turnaround times, it's crucial to move away from manual means of monitoring and coordination. Quite simply, the time taken to report the completion of all these processes manually is cumbersome; but once you add in the potential for human error and miscommunication, the situation becomes time-intensive and a huge drain on resources. Embracing AI-powered solutions is the key. These tools offer real-time monitoring and precise predictions, empowering stakeholders to make informed decisions and optimize turnarounds.

By leveraging historical data and real-time analytics, AI algorithms can anticipate potential delays and disruptions well in advance. For example, AI solutions can analyze past patterns of passenger behavior to predict the likelihood of delays. With this foresight, airlines can make data-driven decisions, allocate resources efficiently, and minimize the impact of unforeseen events.

Indra’s Complete Flight Turnaround Management Platform

Indra's AI-powered Complete Flight Turnaround Management Platform, in collaboration with IntellAct, seamlessly aligns with the Airport Collaborative Decision-Making (A-CDM) and Airport Operations Plan (Plan) concepts. Our joint solution empowers airports, airlines, and ground-handling teams by providing real-time visibility into the aircraft turnaround process. It optimizes turnaround times by closely monitoring both the aircraft turnaround process and the movements of passengers, crew and baggage. By doing so, it recognizes their significant impact on overall turnaround efficiency.

Its key features include:

• Integration with Baggage Handling and Reconciliation Systems (BHS/BRS) for seamless and end-to-end luggage tracking.
• Systems (BHS) for seamless luggage tracking.
• Passenger flow monitoring at touchpoints from check-in to boarding.
• Leveraging of CCTV cameras on the ramp and jet bridge to monitor aircraft turnaround processes (up to 200 events Above and Below the Wing).
• Advanced predictive models refining Target Off-Block Time (TOBT) and raising alerts if it lies outside the TSAT window.
• Integration with Airport Operational Database (AODB) / Airport Collaborative Decision Making (A-CDM).

At Palma De Mallorca Airport (PMI), part of SESAR 3 Joint Undertaking, Indra and IntellAct accurately predicted TOBT 45 minutes ahead of departure, well before the airline’s own predictions were forecasted.

In the world of aviation, where every second costs, harnessing the power of AI is vital for airlines and airports to conquer the Planning Fallacy and enhance visibility, both key to optimizing operations. By leveraging AI, we can ensure smoother and more predictable processes. The combination of AI's planning capabilities with real-time monitoring and historical analysis empowers stakeholders to proactively address and mitigate departure delays. With AI as our ally, the industry can embrace efficiency, anticipate disruptions, and confidently deliver timely turnarounds.

[1] Innovative Airline Operations: The Turnaround | Travel Tech | OAG