Data-Driven Scheduling

Combining Commercial And Operational Information

The capability to incorporate valuable passenger traffic, fare and market capacity data into AirVision Schedule Manager enables higher quality, balanced decisions further into the schedule-development process.

In the data-rich world of today’s business, numbers are the driving force behind everyday decision-making. Whether selling a home, investing in the stock market or changing the lineup of a fantasy football team, to be successful, individuals must accurately evaluate and interpret available data to gain a competitive edge.

Organizations, including airlines, are no different in their use of data to guide decision-making in an effort to create an advantage. While commercial and operational data are plentiful, converting large data sets, known as “big data,” into useful information and making it available at the time of decision-making is a challenge.

Current Data Sources
Disparate Data Points

When making important decisions, schedule analysts need to reference multiple sources of data that are often difficult to access quickly and are not aligned. As a result, analysts may simply rely on intuition instead.

There is no greater example of this challenge than in the area of schedule planning. Schedule analysts have the immense responsibility for making decisions that directly affect the profitability of an airline. To do so, they must locate and collate data from multiple sources to make the most informed and accurate choices. The data-driven scheduling concept involves bringing this data to the analyst making the decision.

Data-driven decision-making and modeling is most effectively used in the long-term schedule horizon to assist with decisions related to schedule structure. Data may be utilized manually or incorporated into a model, such as Sabre AirVision Profit Manager and Sabre AirVision Fleet Manager.

Profit Manager must be calibrated with a variety of data, including post-departure and market/fare information, before it can generate future schedule forecasts.

Fleet Manager uses fares and unconstrained demand data to consider every possible fleet/flight combination to ensure the most profitable use of an airline’s equipment.

While data is generally used by the long-term schedule-planning department for creating the schedule structure and making macro-level decisions, data is not readily available once the schedule is being developed inside the schedule editor (a system used to develop and edit the schedule such as Sabre AirVision Schedule Manager) and as operational constraints and exceptions are applied.

Often, an airline’s reservations system or an enterprise data warehouse may be used to query historical data, and even in today’s highly technical world, some carriers find a three-ring binder on the shelf is the best reference available for route profitability data. However, these options are cumbersome and cost the scheduler valuable time and productivity.

These disparate data points are difficult to access quickly and are not aligned to make optimal operational or scheduling decisions under the time constraints associated with schedule deadlines. For example, current bookings in the reservations system may tell a different story than historic bookings in the route profitability system. Therefore, many times, an analyst will make decisions based on intuition or feasibility without regard to commercial data. Most often, though, the driving factor tends to be operational constraints, which can result in lost revenue.

Why Data Is Not Being Used
Lost Profits

There are multiple reasons an analyst will not use data when making decisions during the schedule development process, leading to lost profit.

There is an inversely proportional relationship between the use of operational data and commercial data in schedule decision-making. As more operational constraints are applied, the incorporation of commercial data tends to decline. Therefore, most airlines use only the most basic commercial data when making schedule decisions and trade-offs. As was noted above, data is not readily available in the schedule editor and, as a result, it is rarely used when developing the schedule after it is passed on from long-term schedule planners. Improving the use of data in this phase of schedule development will increase both productivity and profitability.

Source, volume, correlation and visualization are among the many aspects to consider when improving the use of data. While all are important, visualization is often neglected during schedule development. With data-driven scheduling, market data is made available within the schedule editor, improving visualization, so decisions can be balanced between their commercial and operational impact.

To enable data-driven scheduling, an analyst needs applicable data elements readily available that create true actionable insights. While reliable market data can be difficult to obtain, it is a critical component for making decisions that lead to financial success.

Market Intelligence
Reliable Market Data

Market data, available directly in the schedule editor, can be difficult to obtain. However, it is critical in providing the user with actionable insights when making decisions that affect an airline’s profitability.

Sabre AirVision Market Intelligence connects airlines with a wealth of market data by providing information such as market sizes, traffic, flow, fares and competitive schedules. Using proprietary algorithms and historical traffic, monthly versions of the data are produced that include input from multiple sources, such as MIDT, Sabre fares, Innovata, government agencies, industry associations and web scraping.

Schedule Manager already has the tools to display up-to-date and accurate revenue management and fare data, enabling analysts to gauge the impact of potential schedule changes in the light of current and applicable information.

Additional airline origin-and-destination market data combined with competitor airline schedule information provide even greater capabilities. By making competitive activity visible, analysts can adjust schedules using factors such as equipment size, pattern of service, time of day and number of frequencies. With market data, optimal connections are maintained based on historic airline traffic and fares. This information will be quickly and easily accessible to analysts by right-clicking directly in the schedule editor.

Incorporating this data into the schedule editor enables the creation of real-time alerts, notifying analysts when optimal connections are missed or capacity drops below that of a competitor. By providing these actionable insights, Schedule Manager will allow analysts to consider crucial commercial data simultaneously with operational constraint data, thus protecting the profitability that the long-term planners have built into the schedule.

Combining data from Market Intelligence with a schedule developed in Schedule Manager provides a complete picture for an airline that includes both critical commercial and operational constraint data. By eliminating suboptimal decision-making resulting from time constraints or operational feasibility alone, data-driven scheduling can maximize an airline’s profitability and increase its competitive advantage.