Fifteen-second speed read:
Airport aeronautical revenue could be increased through service improvements
Bots may be best-suited for this challenge
AI initiatives face three main limitations
- Becoming data-driven will have side effects
The term “airport” first appeared in a newspaper in 1919, referring to Bader Field
in New Jersey, a pioneering parking spot for both sea and land-based craft. Since inception, this infrastructure point has been associated with dynamism and development both in popular culture
and in business studies
. Now it may continue its leadership by providing a perfect base for developing artificial intelligence systems close to resembling magic
and earning more money from it.
Understanding this claim requires a bit of background. A well-run airport extracts as much as possible from its two revenue sources: aeronautical and non-flight operations fees. Charges in the latter have been argumented by among other reasons improvements in service quality (eliminated flow bottlenecks
, easier shopping
, needing finance for better connectivity to the port
, and others). Pricing for the former has been growing for some time
in search for market equilibrium and since there is a lack of substitutes for places to land or refuel an airplane unlike, e.g. leaving a passenger’s car at home instead of at a long-term parking closer to a runway or city centre versus duty-free shopping.
The two direct users of an airport’s services, airlines and passengers
would of course like to get value for being charged more. Service improvements constitute one reason to raise fees. But while focus on serving the consumer qualitatively may justify markup and serve marketing goals
well, the business-to-business segment does not usually make the news. Could it be because not much changes in it?
Probably, since elements of service demand from one business to the other have not changed much since Bader’s Field opened. Here’s a proposed list of Service Level Agreement items required from airports by airlines:
0. Infrastructure at quality (no potholes, clear NOTAMs, reasonably reliable weather predictions)
1. Efficiency – speed of ATC handling, quick provision of ground power, higher electrical supply on demand,
2. Punctuality – a delay minimisation approach,
3. Space to grow passenger volume (including baggage belts, check in desks, security checkpoints),
4. Security of its assets while on premises.
Demand details may vary, depending on the full suite of services on tender. Charging for their quality of provision has been studied
already but without detailed consideration of IT multiplier effects. Here is a short attempt: Information Technology cannot increase the amount of space offered (some are trying to circumvent the need for extending it altogether by outsourcing services to people’s homes
). It can certainly assist in analysing what to focus on and how to effectively manage infrastructure quality (0), punctuality (2) and asset security (4).
Another potential means of raising charges could be efficiency increase in aircraft handling (1) to improve customer satisfaction. This would include optimal parking and ground handling vehicle organisation with statistical proof that the airline operation gains revenue from the process.
To illustrate, let’s take the example of an aircraft arriving late with a large number of connecting passenger: the planes customers have to run and connect to could be automatically clustered at adjacent gates for shorter sprints. Meanwhile, ground handling units approaching from behind and right of the parked plane could be automatically queued, so the PRM service goes first, reaching the front right airplane door where the special passenger is before others; the catering one could be last as it has to reach the rear left door; and all their movements could be tracked via image recognition on existing apron-side cameras and in-vehicle GPS. QED with enough digital data sources combined with an analysis engine.
All this has already been possible but at the profit margin diminishing expense of hiring additional staff to supervise operations. Now, the Big Data challenge could be automated with the coming of age of self-learning bots
, so more one-time technology purchases and not a continued highest cost element
(direct personnel) increase.
A disclaimer must be considered when evaluating this idea since this feat does not appear to serve every operation equally well. Scale, Skills, and Data are essential:
A concluding consideration and the key takeaway may not be the artificial intelligence application itself but its effect of driving digitisation – once process inputs become binary (i.e. the airport is data-drivennew use cases
will spring up. And if a bot is faced with a well-defined problem to apply data to, answers about better customer service from both airlines and airports as well as means of increasing revenue from them might just emerge.
Flight Operations Challenge…
Like most people, I think the ubiquitous robot future is exaggerated. While headlines about machines going to take over our lives are everywhere, the associated artificial intelligence challenges abound and history suggests the economic party always continues with the machines going hand-in-hand with labourers anyway.
But, for the sake of a hype’s devil’s advocate, if you were leading a flight operations department in a reasonably-sized airline (not your uncle Tom’s Air Taxi with a PC-12 but an enterprise where 20+ aircraft can form an actual line in the air), where would you start to replace humans? After all, your basic job is maintained adherence to safety standards and optimisation of processes (and a potential 30% return on investment within a year): the soulless, salary-free, 24 hour-a-day working product of robotic process automation, once set on “repeat”, never stops for a bathroom break. Assuming a constant rate of scientific and engineering evolutions, you’d focus on standardised, high-volume, low time-consumption task and in 10 years we’ll have:
- Flight-related tasks at 40-80% without human intervention, depending on willingness to invest.
- Pre-flight preparation: manual tasks on the way out (or almost completely replaced through management by exception).
- In-flight monitoring: minimum intervention and management by exception through constant connectivity and adapted aircraft (i.e. with intermediary adaptation layer installed even on older equipment because of the benefit of process efficiency and resulting competitive advantage).
- Flight and cabin crew: difficult to replace in the foreseeable future for varied reasons (required human interaction by other humans, currently manufactured equipment standards, security issues, insurance requirements).
- Post-flight processing: completely automated with no paper involved. Humans would only be needed for final decisions and to talk to other humans.
- Regulatory compliance/manuals updates/documentation follow-up: automated, partly through higher levels of external auditing.
- In cooperation with the head of ground operations: 90-100% process automation within 10 years (a USD 100 billion market without robots).
- Baggage vehicle drivers, loaders, unloaders: replaced by self-driving vehicles and robotised assistants.
- Fuelling service: same.
- Toilet service, cabin cleaners: what’s not to automate and reduce costs by?
- Together with the head of maintenance – 60% human-free by 2030:
- Routine checks: droned already.
- Fault analysis: much less engineering staff required through automated sensor processing and automated situational analysis. Final intervention by humans by exception.
- Repair: depends on the devil in the details but can certainly be automated.
- Emergency situation response teams: used in specific situations such as explosive device dismantling but generally a high degree of interaction with people required, so still largely human. 20% of decision support (and possibly a degree of manual coordination) could be removed in 10-20 years.
Source: Robotics Tomorrow
On a side note, that means that, save for maintenance downtime, airspace congestion, and airport regulations, operational expansion would become considerably cheaper (I’d estimate 27% in labour cost reduction of the average 34% airline expense with a corresponding direct operational cost (fuel, depreciation) increase).
So, what’s an honest flight operations worker to do in 10 years? The robot may not have a plan but you do:
Step 1: list your job’s functions in great detail, from the mundane (“create weekly punctuality chart”) to the highly complex “negotiate new ground-handling KPIs based on repeated delays due to their statistically-substantiated understaffing policy”.
Step 2: Look for high-volume highly standardised low time-consuming actions to figure out what can be automated initially. I’m not referring to reading e-mail but e.g. approving reimbursement claims, driving a GPU to an airplane – same process day in and day out and therefore soon to be performed by a being that does not tire or require pay. Cross these out.
Step 3: The entries without a line through them show your upper hand.
(Step 4: Assess if your manager and his/her manager is a risk taker since this outsourcing will take some entrepreneurial initiative to start).
I can start: can a robot write this blog? Probably not. It can seek examples of safety improvements in other industries and suggest other new information while I sleep (compiling information lists) but to apply concepts such as RPA to flight operations requires me. The recipient (could it be an automated posts crawler?) should not see the difference but hopefully they will have enough time to create something of their own based on my conjectures (that’s why I look forward to your comments below!).
All this panic seems to me misses another point: the future may not be AI-based but IA-focused. History suggests the machines will augment your intelligence in order to free your time and liberate cash to e.g. implement customer service in-flight initiatives (that is what emotionally deprived sentinels can’t do). So, if the robots could allow you to create your own job of the future what would your Kraftwerk be? Start drafting it now and get background preparations ready (i.e. study for it) because they’re already here.
Flight Operations challenge…accepted.