The Smarter Airport – How Can Intelligent Decision-Making Transform Performance and Customer Experience?
Smarter airports – it’s a description we hear a lot, but it means different things to different people. So what does it mean from a Veovo perspective?
When it comes to improving airport efficiency and the passenger experience, airport operators traditionally focus on one area at a time. For example, measuring wait times at security checkpoints to adjust resourcing and smooth throughput, assigning gates and parking stands to improve on-time departures, minimise towing costs and ultimately reduce fuel burn.
Every improvement helps. But making decisions focused on one area alone does not optimise the entire airport.
Passengers and airlines view airports not as a series of discrete events but as a journey or a “flow”. A good decision that solves one pinch point, but doesn’t optimise the entire flow, will only have a limited impact on improving the passenger experience. Plans optimised for a “blue-sky” day often come up short when faced with irregular or unexpected events; but building in “buffers” to make them resilient simply wastes capacity and resources.
Smarter airports look beyond single processes and static plans with buffers. How well they have embraced that approach defines where an airport is on the transition to “Smart”.
Top-performing airports view the end-to-end process they need to optimise and look for the most impactful changes, which deliver the most improved outcomes across the entire airport, much like major manufacturers did in the second half of the last century.
But it needs to be more than that. Airports are operating in a very dynamic environment with constantly changing priorities. So smarter airports are not just reactive. They have to be predictive. They anticipate changes before they happen and get ahead of disruption; an unexpected influx of passenger numbers at immigration, apron congestion due to a late departure, or a traffic snarl-up causing late arrivals and check-ins.
Another difference is the way smarter airports continuously improve. They don’t make the same decisions because that’s what they’ve always done – they learn from past outcomes with a continuous improvement feedback loop. Smarter airports build their capabilities in much shorter cycles, allowing them to keep adjusting course and maximise “bang for buck” as priorities and challenges evolve.
So, how does an airport become smarter? Ultimately, it comes down to bringing together three things – data, prediction and decisions. Let’s break it down:
1. Data – The fuel of smart decision making
Smarter airports think in terms of flows rather than discrete events – the movement of passengers and aircraft and how they intersect. Understanding these flows requires capturing data and making sense of end-to-end journeys, not just a single event.
This means bringing together flight, passenger flow and turn-around data to create a holistic picture:
- Flight data that includes flight schedules, live status updates from airlines and third-party aggregators and air traffic management data sets;
- Passenger flow data includes how and when passengers show up and move through the airport, by flight, day and time.
- Turn-around data that capture on and off block times, taxi times and all critical events in between.
Aircraft turn-around is where most benefits emerge from joining aircraft, passenger and baggage flow data together – critically influencing turn-around efficiency and the ability of the aircraft to depart on time.
2. Prediction – Getting ahead of change
Building a rich data pool across flows gives smarter airports better situational awareness to react quickly. But more importantly, it provides critical insight to accurately predict the future.
When airports can predict passenger flow, border control and security can dynamically adjust staffing to meet service level agreements with fewer overheads. Baggage handling and reclaim belt allocations can be done more efficiently to match passenger arrivals. The passenger experience can be improved, for example, with FIDS call-to-gate times dynamically changed, based on actual flight behaviours, to encourage more dwell time in retail while ensuring on-time performance.
When airports can predict more accurate “Off Block Times” due to aircraft turn around, air traffic network effects, or the impact of passengers, they can better use their airside assets, get more capacity out of the same resources, and ultimately deliver a better service to airlines and passengers.
AI and machine learning can significantly impact this space by performing high-volume historical data and trend analysis while using live data to predict changes in the minutes, hours, and days ahead.
3. Decisions – Understanding contextual and holistic impacts
Every airport today uses decision support frameworks – whether it be resource management systems for gate, belt and check-in allocations or staff rostering systems. These tend to rely on a single set of rules with decision outcomes measured against static Key Performance Indicators (KPIs).
And yet, static rules and KPIs don’t account for the dynamic nature of airport environments. Different passengers, different flights, different weather – one day is never quite the same as the next. Without access to real data and accurate, dependable forecasting, operators must bridge the gap with guesswork.
Our decision tools must be more dynamic, learning from real-world per flight data, utilising ever-improving predictions to support decisions and planning that account for this variability. This will lead to more robust planning without the artificial buffers while also enabling far better tactical choices when things don’t go to plan.
This is also what inspires the team at Veovo to develop the Total Airport Score. It’s a scoring framework designed for contextual decision making to help operators understand the real impact on the entire airport, not just one corner.
It lets operators evaluate different plans, run complex scenario simulations and generate role-specific recommendations that reflect broader airport priorities and the current operating context. Armed with this information, operators can see which decisions will have the best outcomes, enabling them to act with confidence and in the best interests of the airport as a whole.
Moreover, when the outcome of that decision on performance is measured, it can then be fed back into future planning decisions – in a continuous cycle of plan, predict and perfect.
Siloed airport operations should be a thing of the past
There is no longer room for silos in airport operational planning and decision making today. One of the most significant changes to airport planning since COVID-19 is that plans must be ready to flex at any moment, and airports must be lean and efficient. Basing decisions on live data flows, advanced forecasting, and joined-up thinking is not just overdue; it has become a necessity for survival.
With new smart technology capabilities coming to market, operators that act smart will be in the best position to meet the challenges of recovery, resilience and evolving customer expectations, all at a reduced cost to serve. More importantly, becoming a smarter airport creates far more seamless and enjoyable experiences from terminal door to take off – no matter what the world might throw at us.
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