The importance of the right data in the airline industry

In any industry, internal data allows us to analyze key information for business, such as logistical aspects, revenue, or performance. Competitor data adds another perspective: market signals, how it evolves, and what changes we can anticipate. My view is that this information should be part of the standard process for planning, definition, and strategic decision-making in the airline industry.

In my work with data in the airline industry, I have been involved in ingesting competitor schedule and capacity data from specialized providers in the aviation industry, and I have worked with Strategy teams to facilitate its analysis. That experience has allowed me to identify a specific need: when planning an airline’s activity, understanding its own results must go hand in hand with an understanding of the market in which it operates.

The experience has also shown me the importance of working closely with those who use the information to make decisions. The Strategy team provides the questions and criteria for the analysis; the data team turns them into consistent and accessible information. Agreeing on what we want to understand about the market and how we are going to measure it makes it possible to align the technical work with the business’s planning needs.

A need that already existed in the hotel industry

The need to understand the competitive environment predates today’s analytics tools. In the hotel industry, where I began my career and held different positions for several years, hotels already shared occupancy and average nightly rate data, among other information. The exchange included information from both competing hotels and the hotel itself. It was done in a rudimentary and manual way, with limited scope and speed, but it made it possible to place each hotel’s results within the context of its market.

Looking at occupancy and average price together helped to understand how prices were evolving and how they related to demand. This benchmark allowed each hotel to assess its own adjustments and seek an equilibrium price: a level that would improve revenue without compromising the desired occupancy, or allow occupancy to be managed more effectively depending on the circumstances and the establishment’s objectives. The comparison provided context for deciding how much room there was to raise prices or when it was appropriate to review them.

In aviation, we find a similar need. What has changed is the scale at which we can collect and analyze information. Today, it is possible to compare the capacity offered by multiple airlines, routes, and airports, track its evolution, and combine it with your company's data. Specialized companies such as Cirium and OAG, and platforms such as ch-aviation, provide data and tools for analyzing other airlines’ schedules and capacity. Some of these providers also offer information on punctuality. With different scopes and methodologies, these sources provide context for planning and operational analysis.

Capacity as a market signal

Airline schedule data includes information on routes, dates, times, airlines, and aircraft types. Seat data makes it possible to analyze scheduled capacity, understood as the number of seats planned for a given period. Based on these data, we can study frequencies, presence at airports, and the distribution of capacity across markets. For the business, this provides a basis for assessing where to open a route, increase capacity, or review our presence, taking into account how the competition is evolving.

It is important to distinguish between frequency and capacity. In an illustrative example, two airlines may schedule the same number of weekly flights on a route while offering different numbers of seats because they use aircraft with different configurations. Aircraft type can also serve as a starting point for estimating differences in fuel consumption and cost per seat, using comparable models and operational assumptions. These estimates help assess our own planning scenarios.

Similarly, comparable weekly capacity may be distributed across different days and times, with implications for the passenger’s travel options.

It is also important to be precise about what we can conclude. An increase in capacity indicates a change in scheduled supply; it does not prove that demand has grown, nor does it reveal a competitor’s load factor or profitability. Historical data makes it possible to identify seasonal patterns and changes in supply. Combined with traffic, booking, or occupancy data, when available, it helps assess whether those changes are related to variations in demand or passenger behavior.

Decisions competitors data helps inform

For Strategy, this information makes it possible to assess a route within its competitive environment. Before considering opening a route or increasing frequencies, the team can review which airlines are present, how many seats they schedule, and how they distribute their capacity throughout the season. A reduction in capacity by another operator may justify analyzing an opportunity, which must then be assessed against demand, costs, and resource availability.

For Commercial, external data helps interpret sales trends. If a route begins to perform differently, reviewing changes in competitors’ capacity makes it possible to formulate additional hypotheses. A new frequency or a schedule change may alter the alternatives available to passengers. Analyzing these changes alongside our bookings, occupancy, and revenue helps investigate that behavior, without automatically attributing every variation to the competition.

For Operations, comparing our punctuality with that of other airlines at the same airport makes it possible to identify differences and guide process reviews. By combining this comparison with our data on causes of delays and turnaround times, we can investigate where to take action to reduce delays and limit their propagation to the other flights in the rotation.

These uses show how the same source can answer different questions. Its contribution depends on the decision being prepared and the internal information with which it is combined.

Keeping changes to understand planning

Airline schedules change, and a single query only provides a snapshot of a particular moment. Keeping successive snapshots makes it possible to study how planned capacity for the same season evolves.

Suppose that in January an airline announces a certain capacity for July and then reduces it in April. If we only retain the latest version, we will see the capacity as of April. By keeping both snapshots, it is possible to identify the revision and place it in time. This makes it possible to ask when the planning changed and on which routes the adjustment was concentrated. This evolution, and the changes in capacity and/or frequency, is often key to competitor analysis and may even allow us to anticipate an event that we may not otherwise have identified correctly.

To compare correctly, it is necessary to distinguish the flight date from the date on which the data was obtained. It is also useful to compare seasons at an equivalent point in advance. Comparing the schedule for one summer six months before it begins with that of another summer only a few weeks beforehand may confuse planning differences with changes in capacity.

Historical data therefore adds another dimension: it allows to analyze both planned capacity and the process through which that forecast changes.

From data ingestion to business use

Ingesting external information is the beginning of the work. For the analysis to be reliable, it is necessary to agree on how a route is defined, which flights are included, and how periods are aggregated. Codeshare flights must also be reviewed to avoid counting the same flight multiple times when measuring operated capacity.

External and internal data then need comparable criteria. A seat figure for a route can only be compared with our own capacity if both use the same period, direction, and scope. The update date must remain visible so that the user knows which version of the schedule they are viewing.

Collaboration between data and business teams translates into decisions such as which airlines to compare, how to group airports within a market, or how far in advance to analyze a season. Agreeing on these criteria ensures that the results answer planning questions and that everyone interprets the figures in the same way.

Planning with a view of the market

Competitor data helps prepare decisions with a more complete view of the market environment. It makes it possible to contextualize an internal result, detect a change in capacity, and review the assumptions behind a plan.

The lesson I have drawn from working with this information is that its value depends on how it is used. Integrating it, retaining its changes over time, and agreeing on criteria with those making the decisions allows us to move from simply consulting figures to answering specific business questions.

Before planning a route or reviewing its capacity, the team in charge should be able to explain what has changed in that market and how it affects our assumptions. Competitor data provides a basis for doing so with better-informed judgment.