Every day, the modern airport sees tens of thousands of passengers through to their final destination. With passenger numbers expected only to increase, finding ways to continuously measure and improve operational performance is more important than ever. In this article, we’ll cover what it takes to measure and enhance performance from curb to gate at your airport.
Airport operators and airlines alike are facing new challenges driven by a continuous increase in passenger numbers. This puts undeniable pressure on airports to keep up with rising traffic while maximizing performance and providing a top-notch customer experience.
But you can't improve what you can't measure. To reach peak performance from curb to gate, start by collecting information on all your current processes. Ask these questions:
What data sources do you currently have, and do any of them feed into one another?
Where is all of that data stored?
Are you missing data from any key performance areas?
Once you have that overview, you can start to look towards automatically collecting and measuring all of that data in a single spot.
Automation not only streamlines data collection, it also provides valuable data insights that optimize airport processes: forecasting and planning, passenger processing, queuing at security and border crossings, baggage handling, staff and capacity optimization—the list goes on.
Once automation is implemented in and between airport systems, how do operators regularly measure their success and assess what needs to be adjusted?
No matter their size or passenger capacity, airports around the world are measured on a variety of factors. Key performance indicators (KPIs) and Service Level Agreements (SLAs) for airports cover a wide range of areas: financial performance and revenue growth, safety and security, service quality, environmental factors, and of course, operations and productivity.
As an airport manager, one thing is to know what you're measuring—another is to know why. To make a difference, you need to know how.
The biggest advice we can give is take the insights you collected about your current processes. Turn those into targets that you can measure and monitor continuously.
We have compiled some of the top reasons airports should measure and optimize their own operational performance, along with a few ideas for key performance indicators.
Success starts with a great plan. By basing passenger and baggage flow forecasts on automation, airports can predict when and where bottlenecks will develop. Systems like Better Forecast enable them to plan and prioritize staff, infrastructure, and resource allocation more efficiently, helping to prevent unnecessary delays.
Forecasting KPIs
Presentation profile accuracy: Airports often focus on how many people show up, but when they show up can make or break a day's forecast. This KPI compares your predicted arrival curve against the actual sensor data from your WiFi, Lidar sensors, or baggage scans. If your curve shifts 15 minutes early, your staffing will be 15 minutes behind. This metric constantly helps airport and security managers to challenge assumptions when it comes to passenger behavior.
Staffing requirement vs. actual demand: This measures the gap between the number of desks or lanes that the forecast said you needed and when you needed them, compared to the number of desks or lanes that should have been opened based on actual traffic. It reveals whether the long queue was due to the forecast being wrong, because the desks weren't manned, or a third factor altogether.
👉 See how we helped Luton Airport cut forecasting time from 3 hours to 20 minutes a week.
Automation can help airports optimize their staff allocation and capacity utilization. With systems like Better Shift or Better Deployment, airport operators can better prepare for passenger flow—particularly during peak travel times. This ensures that airports handle increasing passenger volumes without compromising efficiency, safety, or security.
Staff and capacity KPIs
Wait time consistency: Most airports track average wait times, but the real test is standard deviation of wait times. If your average is 10 minutes, but some passengers wait 2 minutes and others wait 25, your capacity allocation is reactive, not proactive. Lowering the variance shows that your automation tools are successfully smoothing out the peaks and valleys of passenger arrival.
Staff utilization rate: This measures the percentage of time staff members are actively processing passengers versus time spent idle or time being overwhelmed by an overflowing queue. Aim for this rate to be high enough to be efficient, but low enough to avoid burnout and maintain service levels. If it is too high, your capacity is brittle; if it's too low, you're overstaffed.
Throughput per open position (lane/desk productivity): This KPI tracks how many passengers are processed per open security lane or check-in desk per hour. If throughput drops during peak times, it often indicates secondary congestion. For instance, the bins at security are full, or the baggage belt is jammed. Tracking this allows you to optimize the environment around the staff, not just the staff themselves.
Tactical plan compliance: This measures the delta between the planned staffing schedule and the actual staffing on the day. Use this to improve short- and long-term planning. Did you deviate because the forecast was wrong, or because of a call-in or operational delay?
👉 Manchester Airport used Better Shift and Better Deployment to reduce their security queues and cut over 60 rosters down to 10.
Automation is also becoming increasingly prevalent at check-in. Passenger processing systems like Better Check-in optimize passenger processing, handling, and flow through automated counter allocation.
Automated passenger processing systems also support common use self-service (CUSS) kiosks and automated baggage drop points in airports. They use advanced technologies to scan passports, print boarding passes, and tag luggage. This significantly streamlines the check-in process, helping to optimize efficiency and boost airport performance at the beginning of the passenger journey.
Increased use of CUSS kiosks also enables airports to reduce unnecessary queuing and crowding in transit areas. This helps ensure a faster, easier flow and improves flexibility, planning, and efficiency.
Passenger processing KPIs
Seconds per PAX at check-in or bag drop: This KPI tracks how long a passenger (PAX) is stationary at a desk or kiosk. A high number of seconds per PAX leads to terminal crowding before the passenger even reaches security.
Self-service completion rate (SSCR): This KPI tracks the percentage of passengers who start a self-service process (like bag drop or biometric boarding) and finish it without needing human intervention. A low completion rate likely means your "automation" is actually causing more frustration than it is helping.
👉 Learn how Sydney Airport replaced manual, static methods with dynamic allocation of check-in desks based on business rules, preferences, and expected passenger load on each flight.
In baggage handling, automation enables airports to make data-driven decisions in the short- and long-term. By analyzing baggage load and passenger arrival curves, solutions such as Better Baggage make it possible for airports to optimize the flow of baggage handling and streamline the reclaim experience.
A baggage handling system with automation features ensures that all employees are working with the same updated plan at all times. The plan automatically updates based on the latest arrival times, bag load, and passenger data. When a belt does get congested, the system automatically alerts operators so that the issue can be resolved quickly. This helps to reduce wait times, free up capacity, and improve passenger satisfaction.
Baggage handling KPIs
Mishandled baggage rate (MBR) per 1,000 checked bags: By measuring against actual checked bags, you get a true reflection of your system's reliability, regardless of how many carry-on-only travelers are onboard. Reducing the "left behind" and "misrouted" percentages should be obtainable with widespread RFID and IoT tracking.
First and last bag delivery time: This measures the time from an aircraft's arrival to when the first and last bags hit the reclaim carousel. Look at the gap between the first and last bag to ensure a consistent flow. For example, if the first bag is out in 12 minutes but the last bag takes 45, your staffing or equipment could be bottlenecking the process.
Transfer baggage success rate: This measures the percentage of bags that successfully make it from an arriving flight to a connecting flight within the minimum connection time (MCT). A passenger might make a 45-minute connection by running through the terminal, but can their bag? Tracking this KPI allows you to optimize your early baggage storage and high-speed sorting systems to meet passenger expectations.
👉 After struggling with imbalanced belts and conflicting flight allocations, Denver International reached 95% automation in their belt assignment process using Better Baggage.
Virtual queuing creates a virtual line or waiting space for passengers needing to pass through check-in, security, or passport control. This significantly reduces physical queuing and helps airports stay on top of demand. The virtual queue is usually available through:
- An app
- Phone
- Email
- The airline’s website
- SMS
Technology such as Better Virtual Queuing allows passengers to pre-book a slot—typically offered in 15-minute intervals—in the virtual queue. This allows airports to better manage passenger flow and improve passenger satisfaction, which ultimately boosts the airport's operational performance.
By providing data that can be used to optimize staffing and reduce bottlenecks, virtual queuing also enables airports to better manage their resources and improve operational efficiency.
Queuing KPIs
Queue re-balancing efficiency: This KPI tracks the time elapsed from a "congestion alert" (detected by sensors) to the actual opening of a new lane or desk. It measures the agility of your operation. Automation in your systems should trigger these moves before the human eye even notices the queue growing.
SLA compliance: Most airports have service-level agreements (SLAs) for queue management. For instance, a maximum 10-minute wait for 90% of passengers. Targets like this allow airports to plan for rushes and not a perfectly flat day. It allows them to staff peak times properly without overstaffing the entire day.
👉 We helped Seattle-Tacoma International Airport become the first airport in the United States to introduce virtual queuing, shaving 25% off their peak-hour demand in security. What’s more, 63% of passengers spend more time shopping, eating, and drinking at the airport as a direct result of the time they save in security processing.
Automation offers faster and more convenient processes, reducing the time that passengers spend at various checkpoints throughout the airport. This leads to a more positive overall travel experience, as passengers experience less stress and frustration on their journey. Not only does this increase passenger satisfaction, it improves an airport's operational efficiency and performance.
Passenger experience KPIs
Effective dwell time (EDT): This measures the time a passenger spends in departure areas such as retail and food halls versus time spent in "process" (queues/walking). A passenger who isn't standing in a security line is a passenger who is relaxed enough to enjoy a coffee or do some shopping.
The "seamlessness" index: This measures the ratio of Moving Time vs. Waiting Time. If a passenger spends 5 minutes walking and 15 minutes standing still, the experience feels broken. A "walking" airport feels faster and more modern than a "waiting" airport, even if the total time is the same.
Real-time information "trust" score: If your app or digital signage says the wait time is 5 minutes, but the passenger sees a sea of people, you risk losing trust. This KPI measures the accuracy of the wait-time information displayed to passengers compared to their actual experience. When passengers have accurate data, they feel more in control of their journey.
Transfer stress resilience: For connecting passengers, this KPI tracks the buffer time remaining after they clear their transfer checkpoint. By using automation to speed up this process, you increase the "success rate" of tight connections. This directly reduces the number of missed flights—the single biggest "pain point" in any passenger's journey.
Depending on your airport’s size and ambitions, there is an endless combination of KPIs to track across your systems. But because of this, performance tracking can also become fragmented and siloed. So how do you efficiently measure performance across systems?
For the modern airport to reach maximum performance, its operations must be connected. When operations, analysis, and planning are connected through automated processes, airport teams can make smarter decisions faster. This is why we have developed Better Airport®: a cloud-based airport management SaaS platform that gives all airports a simpler way to run core operations.
With this software, you can automatically generate the most optimal plans based on data you've collected and KPIs you've selected, ensuring higher efficiency, lower wait times, and better passenger experiences.
Better Airport utilizes all the data points your airport has access to, feeding them into processes for better collaboration and decision-making. From forecasting and planning to day-of-operation and real-time adjustments, all teams stay in control of their operations and more accurately track performance measures.
Featuring nine core modules for airport optimization, Better Airport allows you to mix and match modules to create a solution perfectly suited to the specific needs of your airport.