Codesharing innovations

New big-data technology helps maintain fare and availability coordination among airline codeshare partners

By Hunkar Toyoglu

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eveloped by Sabre’s Operations Research and Data Science Consulting team, Codeshare Alerts is first-of-its-kind technology that systematically detects in-market fare deviation and availability misalignments. It also delivers alerts to inventory and pricing analysts, guiding and supporting them in pricing and inventory correction decisions.

Exponential growth in the airline industry has yielded several challenges, two of which pave the way for important changes in the airline business. First, not all city pairs are able to generate sufficient demand to sustain non-stop services for many airlines. Second, not one airline has enough aircraft to carry all demand and serve every market.

To address these issues, airlines began forming commercial partnerships that enable them to meet the demands of their passengers by having access to larger fleets and providing greater network coverage. Today, cooperation among airlines has become a dominant feature in the airline industry.

Codeshare partnerships, although relatively straightforward, present several practical difficulties. For example, marketing carriers do not have full inventory visibility due to operating-carrier-centric inventory systems. Operating carriers distribute their O&D-controlled availability to marketing carriers through AVS messages, which can handle only leg-level availability with latency. Then, the disjointed revenue-management systems of the codeshare partners separately control the unsynchronized shared inventory, which may result in inconsistent availability.


All these cascading factors make it difficult to maintain fare and availability coordination. Amid this complexity, an airline must protect its benefits from the codeshare agreement by ensuring its code-share partners are not inadvertently or intentionally using incorrect pricing and availability. This can easily be accomplished through new codeshare-alerts technology.

Codeshare Alerts helps codeshare partners avoid unintentional misalignment. It also helps prevent revenue leakage and makes certain the appropriate revenue-management controls are used in codeshare flights.



Codeshare alerts

One of the main reasons an airline enters into codeshare agreements is to increase its long-term profitability. However, each airline in the partnership has the same purpose which, in turn, makes each one of them a competitor, as well as a partner. Hence, each partner must make sure its codesharing partnerships are indeed helping increase profitability fairly and according to legal agreements.

Such mutual and conflicting benefits call for a systematic mechanism to prevent each partner from unintentional misalignment. To address this need, the Sabre Operations Research and Data Science Consulting team developed Codeshare Alerts, technology that assists airlines in this difficult endeavor to prevent revenue leakage and ensure the correct revenue-management controls are used in codeshare flights.

In late 2014, the conceptual design was introduced in an Ascend magazine article titled “Codeshare Alerts." Since then, the Codeshare Alerts project has evolved into a fully automated operational tool that several airlines rely on to reduce revenue spills to codeshare partners in daily codeshare-route operations.

The fundamental goal of Codeshare Alerts is to identify misalignments in fares and inventory management between operating airlines and their codeshare partners to prevent leakage due to inconsistent inventory controls and pricing. Every day, Codeshare Alerts issues thousands of alerts that can be addressed to prevent revenue leakage.


Big data and shopping robots

When a consumer shops for airfare using an online travel agent subscribing to Sabre’s global distribution system (GDS), the online travel agent will invoke the Sabre Low Fare Search engine via Sabre GDS Web Service. This is referred to as the low-fare search response to a consumer request as “shopping data.”


When collecting data for Codeshare Alerts, consumer actions are mimicked by connecting with the Low Fare Search engine using a customizable shopping robot. The robot takes customer-specified shopping input, including route and partner, advance-purchase date range, cabin type, trip type and length of stay, to set up market scanning. Then, it generates requests to the Sabre GDS and parses needed information from each pair of request and response files.

Current Codeshare Alerts robotic shopping generates around 200,000 daily requests for Sabre airline customers and returns approximately 15 million itineraries for further processing. The result is tens of thousands of alerts that, if corrected, would produce millions of dollars in extra revenue for the host airline in reduced fare dilution if one ticket were booked for each alert.

Data processing and rules engine

The extract, transform and load (ETL) process is responsible for generating alerts from the raw shopping big data. By comparing the point-of-sale, trip type, cabin type, departure and return date/time, and operating flight numbers, Codeshare Alerts finds identical itineraries that are priced differently by host and partner airlines.

The ETL inputs are:

  • Raw shopping big data: This is the daily output of robotic shopping. It contains itinerary information for the markets the host is marketing.
  • RBD mappings: The mapping between the host and all its codeshare partners for both host operating and partner operating cases. These mappings are used for generating inventory alerts. Currently, codeshare alerts support mappings up to segment-level resolution.
  • Business rules: These are the configurable rules that are used for filtering irrelevant and/or insignificant data from raw-shopping data. They are structured based on the host airline’s needs and may include dimensions such as itinerary leg count, connection time, mixed-cabin exclusions and fare-difference threshold.

Creating synergy via synchronization

In addition to Codeshare Alerts, Sabre also developed the SabreSonic Inventory and Shopping family of solutions, which includes SabreSonic Partner Specific Availability, SabreSonic Seamless Codeshare and SabreSonic Bid Price Exchange. Read "Advancements in codeshare technology" in Ascend for additional information about these innovations.

The Sabre Operations Research and Data Science Consulting team has collaborated with the company’s product teams to synchronize Codeshare Alerts with SabreSonic Partner Specific Availability. Now, both tools work seamlessly together to automatically detect and solve airlines’ inaccurate codeshare-availability problems.

Big data-guided codeshare technology

The primary objective of Codeshare Alerts is to identify misalignments in fares and inventory management between operating carriers and their codeshare partners to prevent leakage as the result of inconsistent inventory controls and pricing.


Codeshare Alerts uses a robot to systematically shop for relevant itineraries. The itineraries are analyzed using a set of business rules, an alert is issued if there are discrepancies in the handling of

codeshare inventory, and it is automatically corrected by Partner Specific Availability. On a daily basis, Codeshare Alerts issues tens of thousands of alerts that can then be addressed to prevent revenue leakage. Through dashboards and trend reports, the host airline can manage and track performance by partner airline and measure improvements in the management of codeshare inventory. /A

Hunkar Toyoglu

To learn more about Codeshare Alerts, contact Hunkar Toyoglu at hunkar.toyoglu@sabre.com.


Hunkar Toyoglu is leading Sabre Airline Solutions Operations Research and Data Science Consulting. His main responsibility is to solve airline problems where there is no readily available solution across a diverse range of domains including pricing and revenue management. He is building proof of concepts and developing innovative customized software solutions to explore novel ideas by utilizing analytical techniques such as operations research and machine learning. He has worked with many airlines globally and delivered software solutions in pricing and revenue management. Hunkar has been leading analytics teams for 20 years to translate scientific knowledge into real life applications. Hunkar is the co-chair of AGIFORS Revenue Management and Distribution Study Group. He has a PhD in industrial engineering.