AI-based predictive models can enable airport management to predict peak times, variations in queue lengths and potential bottlenecks, as well as anticipate heavy road traffic and its impact on lead times arrival of passengers.
I normally navigate Metro Manila by staying a short distance between services to avoid seasonal traffic congestion. However, recent travel needs – an international flight and a domestic flight – forced me to venture outside these limits.
As the holiday season brings with it the familiar increase in traffic, my recent travel experiences have become even more punishing. Traffic congestion and vibrant traffic, especially in our metropolises, make the “ber” period in the Philippines a crucial time to consider the effectiveness of our public systems.
Ripple effects of international travel delays
In preparation for my international trip, I left Makati at 2:30 pm for a 9 pm flight, only to find myself stuck in holiday traffic. What was usually a 20-minute drive to the Ninoy Aquino International Airport (NAIA) turned into an exhausting order of several hours.
Road congestion was just the beginning of a cascade of delays. Upon arrival at the airport, I was greeted with unexpectedly long lines for a simple bag drop-off at check-in, and the “priority lanes” at immigration turned out to be a misnomer, offering little relief from the long wait. Talk about a domino effect. (Un)surprisingly, we arrived at our boarding gate with less than an hour to spare before departure, only to face an unexpected turn: we were deplaned – but that’s a story for another time.
Systemic inefficiencies in domestic travel
My domestic travel experience reflected the same challenges and complexities. Anticipating potential delays, I left Makati well in advance for a flight scheduled to board at 3pm. However, despite my proactive measures, I soon fell into a web of inefficiency that seemed all too familiar.
At the airport, I headed straight to the check-in desk, expecting a quick bag drop-off. I had another long delay due to systemic inefficiencies.
The line at the check-in counter was not only because of the usual rush, but was made worse by the delays caused by the international flights. These delays spread throughout our domestic system, creating a significant bottleneck even for those of us who drop off our bags.
It took us at least an hour to navigate through this congested process – another stark reminder of how interconnected and vulnerable our systems are to disruptions, even those originating from different segments.
Integral approaches in public service
Ironically, my recent travels have served as a clear demonstration of what I have argued all along – the need for a Complexity Sciences perspective in strategic planning.
When considering complex systems, it is essential to recognize that the whole is not only more than the sum of its parts, but also fundamentally different. This is particularly applicable in systems such as city transport or airport operations, where the interaction between individual components can lead to emergent behaviors that are unexpected and often exceed what each part can achieve independently.
Understanding this perspective is critical to realizing that simple cause and effect solutions rarely work effectively in such complex systems. Instead, a multi-faceted approach is needed that considers the myriad of variables and their interactions.
This becomes especially critical in the public service, where systemic improvements are essential. Merely strengthening individual components of our public infrastructure, such as check-in lines at airports, toll roads, or airport runways alone, is insufficient to address the broader problems. Integrated solutions that take into account the complex interaction between different public services are needed.
For example, consider the problem of queuing in airports – a classic example of a complex system challenge. The mechanism-based model helps us to understand fundamental aspects of queuing dynamics, such as the rate of passenger arrival, service times at check-in counters, and the impact of these factors on the length of the line and the waiting times.
But while this knowledge is crucial to designing efficient queuing systems and effectively managing the flow of passengers at the airport, it forms only one part of the wider system. Addressing airport efficiency comprehensively requires broadening our focus beyond internal dynamics to include external systems, such as traffic congestion on adjacent roads.
For example, AI-based predictive models can analyze historical passenger traffic data, both inside and outside the airport, to forecast peak times, variations in queue lengths and potential bottlenecks. This broader perspective allows airport management to make more informed, data-driven decisions. For example, anticipating heavy road traffic and its impact on passenger arrival times could lead to adjusting check-in procedures or coordinating with city traffic management to mitigate delays
This integrated approach illustrates the need for a whole systems perspective in managing complex environments. Solving the internal challenges of the airport, while crucial, is not enough. A comprehensive strategy must also consider external factors, ensuring a perfect and efficient experience from the beginning of the journey to its end.
Integrating complexity science for future solutions
The lessons learned from my travel experiences underscore the need to embrace a Complexity Sciences approach to strategic planning and public service. This approach, which includes the use of tools in network science, artificial intelligence and agent-based modeling, among others, is crucial for the development of strategies that are not only reactive, but also proactive and comprehensive.
By understanding the interplay of various factors in complex systems, such as the cascading effects of air travel delays or the intricacies of urban traffic during the holiday season, we can only remove the symptoms to address the causes roots of these problems. Complexity science allows us to anticipate potential challenges and craft policies that are adaptable and resilient, improving the quality of life for individuals, especially during periods of high stress like the holidays.
This perspective is not just about addressing current issues; It is about preparing for future challenges and ensuring sustainable solutions. It involves looking beyond the immediate, understanding the deeper and interconnected nature of the challenges we face, and appreciating the wider impact of our decisions. – Rappler.com
Erika Fille T. Legara is a scientific educator and interested in the study of complex systems and artificial intelligence. He is an associate professor and holds an Aboitiz Chair in Data Science at the Asian Institute of Management.
