How it Works: LOOP, my LOPA Optimisation Platform

Check out what’s under the hood on one of my favourite tools

Why use thirteen letters when four will do? One of aviation’s standard acronyms is LOPA, Layout of Passenger Accommodation. But I reckon that short and sweet Area is a sweeter and easier substitute for the A.

One of any airline’s toughest challenges is to decide how to configure their cabin. Figuring out how many seats they should put in, which models to choose, whether there should be premium cabins, what they galleys should look like and how much space should be used for the loos directly impacts capex, opex and, most importantly, revenue.

Like substituting Area for Accommodation in LOPA, making this decision sweeter and easier has been a way I have been helping airlines and their suppliers for the last fifteen years (see article). I do this using a tool I first built back in 2013 called LOOP – the LOPA Optimisation Platform.

Essentially a toy airline with fleet, network, product and fares, LOOP was one of the first experimental models I built when I started my business. Since then it has been used for several airlines, an IFE supplier, a seating supplier and in some high tech applications across other parts of the industry (see article).

LOOP is not one of those turn-key software solutions though (see article). It is a flexible menu of algorithms that I call upon to apply airline revenue economics to any question about aircraft interiors or the passenger journey. To some extent, it is the application of revenue management principles to help take great decisions in in-flight product development.

Today I thought I would take you through how LOOP works. Over the next few weeks I will be showing some entertaining applications of LOOP. Stay tuned for those.

Now let’s take a look at what’s under the hood at LOOP…

The eight principles of LOPA optimisation

Long-term readers of Airline Revenue Economics may remember my eight principles of LOPA optimisation from this article and this article:

1. Start with maximum density and only deviate when doing so has a strong revenue case

2. Remove low value seats in a lower cabin and replace them with high value seats in a higher cabin until the higher cabin’s demand at worthwhile fares is exhausted

3. If you can fit extra seats by placing galleys and cabins in unconventional positions, do so

4. If it costs nothing to enhance the product, do so

5. Be prepared to use higher cabins as “virtual capacity” and upgrade where necessary

6. People booking a lower cabin can be inspired by marketing to book a higher one - but only if you have a higher one

7. Consider flexible cabin solutions where these are available

8. Galleys are revenue generating spaces, not cost centres

There is also a ninth one:

9. Involve revenue management and ancillary specialists in the LOPA decision process

…but this is harder to make a reality because many revenue management and ancillary specialists are not familiar with cabin programme processes.

LOOP takes the core eight principles as it’s starting point.

What is an aircraft cabin?

It sounds like a trivial question, but exactly what an aircraft cabin is and how it is structured is an essential part of the LOPA optimisation process.

An empty aircraft is a tube with fixed doors and side-by-side rails laid along the length of the cabin from one end to the other. Anything installed on the cabin floor has to fit on these rails. Accordingly things can move forward or backwards but not side-to-side.

This makes sense when you think about it - architecture tailored for the right-hand-side is curved the wrong way to fit on the left.

“Plinths” fit on the rails and “monuments” from basic bulkheads to funky business bars are mounted on the plinths. Look under almost any economy class seat and you can clearly see from the supporting frame how it is fitted. More advanced pieces, even something that looks simple like an ottoman that goes up and down, can have hundreds or thousands of parts.

Generally speaking the doors have to be left clear and regulatory requirements regarding the number of loos and cabin attendant seats must be met. In principle planes need not have galleys, but I would be surprised if any country in the world did not mandate space for at least some water on anything more than a puddle jump.

Up on the ceiling there will be overhead bins and a passenger supply channel containing emergency Oxygen mask, call bell, light, seat belt sign etc… Somewhere there will be IFE boxes and a controlling server if the airline has a wired-in IFE product.

A complex network of wires and connectors links all of these, often with significant penalties for opex and capex.

The airline may decide to have equipment for in-flight wi-fi too. This could be something “true-broadband” satellite-based like that Viasat’s or a local box-based streamer like Airfi’s. They will need to fit somewhere.

The length and width of the plane is fixed and the usable length and width is slightly less due to the wall panels. Everything in the cabin needs to go in this limited space.

LOOP will auto-reject any combination that does not fit.

The tough questions

Here are some examples of tough questions that I can use LOOP to answer for airlines.

1. Should I offer a premium economy cabin on long-haul, single-aisle or both?

2. Which business class seat option will generate the most revenue?

3. What is the revenue value of increasing galley space (in terms of Standard Unit or Atlas drawer equivalent) by 50%?

4. I know how many ovens I need, but what about chillers?

5. My passengers need IFE, but should it be wired-in or wireless?

I have used LOOP to help suppliers answer their equivalent questions too, like these:

1. Should I offer my airline customer a discount if they buy my premium economy seat for their single-aisle aircraft as well as their long-range fleet?

2. I need to price my RFP submission for my airline customer’s business class seat, so what is their willingness to pay?

3. Should I pitch flexible or non-flexible galley solutions to my airline customer?

4. Which airlines should my sales team target for moving my latest chiller?

5. Ditto for my latest wireless IFE box?

LOOP uses five modules to deliver the answers

Ideally the airline or supplier will have some handy customer research data to hand that will help the analysis. But using standard industry data that all airlines and suppliers have access to can deliver worthwhile results too. I will explain how.

The most fundamental product of any airline is it’s schedule. No matter how comfy the seat or chummy the crew nobody flies just for fun (ahem, Oliver… – ed). So the network is the first input into LOOP. There are two possible approaches.

Network option 1: The schedule-based approach

Download schedule data from OAG (the Official Airline Guide) and it will tell you about every flight that the airline operates in the next twelve months. You can either look at the entire network or an individual aircraft type.

For airlines, using a schedule-based approach is most helpful when the Planning Department can indicate what the schedule might look like over the life of the product. It would be a shame to spend lots of time evaluating great beds for an aircraft that will be put exclusively on four-hour day flights from next year.

For suppliers, the current schedule is normally the “best guess” of what the schedule will look like in the future. Airlines are usually impressed enough by your mastery of the current schedule to share future plans if this would be helpful for their procurement.

Network option 2: The aircraft-rotation-based approach

Download aircraft-rotation data from Flightradar24 or build a mini-model considering different scenarios about how specific air frames might move around.

This approach is most helpful when a product is being considered for a small sub-fleet or if the rollout is expected to take some time.

Typically the OAG schedule data will not be sufficient to understand the routes that these aircraft are used on as it just states origin-destination-time-plane. Reverse engineering a rotation pattern from OAG data can be done with a margin of error but is normally not worth the effort.

London-based British Airways for example has Boeing 777s with two versions of business class – newer Club Suite and older Club World. If I had been using LOOP to help a supplier respond to an RFP for Club Suite* I might have reasonably assumed that the planes that go to New York will be fitted first. I would then have used rotation data to see where else they go.

* I was not

The second part of a LOOP study is all about demand and revenue.

I love it when airlines give me revenue accounting data, the detailed breakdown of all tickets sold and everything you would want to know about them. This data is used by revenue management to generate forecasts and can be extremely rich for product development too.

When I was helping an airline with a galley space issue I could use a part of this data to see from the fare basis code how much demand there was from people buying fares including a free gourmet meal.

When working with suppliers, ATPCO* fares data and Routehappy content about the product plus an MIDT** source for demand are a good substitute for revenue accounting. A handy hint to consider when thinking about how many people book each fare is what I call “RBD*** normalisation” – I assume that the airline receives equal revenue from each fare class.

* ATPCO = Airline Tariff Publishing Company, who collect and distribute fares

** MIDT = Market Information Data Tape, used to hunt for competitive insights

*** RBD = Revenue Booking Designator, a fare class

When using LOOP in this way I always try to consider that some fares, especially expensive ones in premium cabins, could be mainly used by corporate buyers with a discount.

If the airline does not currently fly a route that I am looking at, competitor fares for the same or similar routes can be used as a good benchmark.

The demand and revenue data tells us how full the planes get and how much revenue each seat is worth.

Think of an aircraft cabin as a demand curve sloping downwards – some seats are sold for high prices and some for a bargain discount. The LOOP analysis attempts to answer two simple questions:

How much revenue is each row of seats worth? Is it worth more or less than a row of seats in another cabin?

If a group of rows in a lower cabin is worth less than a row of seats in a higher cabin, the lower cabin’s seats should be replaced. If a row in a higher cabin is worth less than a group of rows in a lower cabin, then rip out the bigger seats and replace them with smaller ones.

Passenger and crew behaviour are the third and fourth things that I need to look at.

Many airlines have done a “passenger archetype” study to try and characterise the sort of people who fly on their planes. These are sometimes used to figure out what sort of schedules are needed in terms of frequency and departure time.

For example flights from Europe to South Africa are often scheduled overnight in both directions, even though this involves a lot of down-time for planes at Johannesburg where they are just sitting still rather than earning revenue.

The idea is that since the route is often full of busy business travellers, “everybody” flying wants to sleep and be ready for meeting on arrival rather than “wasting” a day in the air.

Archetypes are also useful for developing on-board service too. When I was at Qatar Airways the standard vegetarian option on the Doha to USA menus was always the same as the Hindu vegetarian special meal. This was because so many passengers connected from India that in case a passenger had not ordered a special meal the menu’s vegetarian option was most likely to be suitable.

When I do a LOOP project I sometimes use results from the airline’s own passenger research study. But if one is not available I normally use a list of nine, taken from general observation:

1. Long sleepers zonked out

2. Busy workers going clackety-clack on their laptops

3. Device lovers glued to their phones

4. Popcorn fiends who fill the flight with movies

5. Restless souls who cannot settle down and flit from one activity to another

6. Parents looking after their kids

7. Young children not asleep

8. Youths on tour

9. The groggy and the sick

We have all seen them. Let me know if you think I have missed anyone out!

It can be interesting to build some behaviour models around each of them, for example the probability that somebody in each group will be asleep or awake at a certain time. This tells me how important different aspects of the hard and soft product are likely to be on specific flight profiles.

Given a network for an airline, fleet or sub-fleet, LOOP then tells me on average how important different product attributes are for that airline.

I also consider the crew too, with another nine archetypes from my own observation.

1. Lookouts – making sure everybody has what they need

2. Nannies – taking special care of families with kids, Etihad once had crew trained as magicians

3. Gourmets – I helped Qatar Airways start a sommelier training programme to help passengers with food and wine pairing

4. Chefs – aside from Turkish Airlines’ fabulous flying chefs it is not uncommon for some crew to spend their time in the galley plating and preparing while others deliver the service

5. Artists – delivering creative service ideas like the not-on-the-menu Coke float with strawberry ice cream that BA gave me on a recent flight to Philadelphia

6. Sales pros – these savvy guys roll the duty free trolleys out and the sales commission rolls back in

7. Entertainers – keeping the passengers occupied with galley chat and joining you in the empty adjacent seat for a spot of convo

8. Off-days – airlines are full of great and highly motivated crew, but everyone sometimes has days where they are not quite as motivated as usual, so it is important to remember that on each flight there will be somebody not quite at 100%

9. Directors – ensuring everything is going to plan

Have I missed anyone? Let me know!

I love using LOOP to build quantitative models of crew behaviour to help optimise galley and service design. The thing to remember when it comes to modelling crew behaviour is that crew often fulfil several roles during a flight. Considering the proportion of total crew time spent in each role at each stage of the journey is better than imagining one crew member as a lookout, another as an entertainer etc…

The steaks are high (geddit!) (groan… – ed). When airlines get it right passengers have a great experience and come back for more, increasing demand and revenue. Get it wrong and you get disasters like the Club World service of 2018 that took half the flight to deliver. As a regular passenger myself I want to see things done well.

The fifth and final part of a LOOP study is a product decomposition

By this stage in a LOOP project I have already looked at the airline’s schedule, demand profiles, passengers and crew. This will have given me a good idea about what sorts of products and services are likely to generate the most revenue for the airline. The final question is simple:

Which specific products and services are most closely aligned with the airline’s revenue generation potential?

To answer this question I perform something called a product decomposition. This can be applied to a seat, catering product, service, in-flight entertainment & communications system or anything else.

It breaks down the product into every single attribute that can be of value and defines how that value is created across the passenger and crew archetypes.

The product whose value is most closely aligned with a network or fleet type will generate the highest revenue.

But that is not the finally final step. It is not just revenue that matters but cost too. Airlines have to choose the product submission that generates the highest profit, revenue net of cost.

For suppliers, LOOP tells us what an airline is willing to pay for the product. Deciding how much of that value to capture when pricing an RFP is another step. More on that another time…

Would you like to see LOOP in action? Are you ready to be in the LOOP? Let me know and we can sort out a chat.

oliver AT ransonpricing DOT com