Are You Ready for High Volume NDC? Addressing NDC Scalability Issues in the Leisure Market

Since the introduction of the New Distribution Capability (NDC) standard, concerns have been raised about the industry’s readiness to cope with the high volumes of transaction queries that characterize the leisure travel market.

Jean Philippe Mesure, an independent consultant from ITS4T, has explored this topic in a new whitepaper titled “Addressing NDC scalability challenges in the leisure market,” which was recently published by IATA (March 2019). Drawing on interviews with more than 25 leading industry players, Mesure concluded that NDC at scale comes with widely acknowledged technical and commercial challenges that the industry believes can be addressed – including the elephant in the room, i.e., look-to-book ratios.

Ouch! Look-to-Book Ratios Off the Charts

“Far from the 100- to 300-to-1 observed with airlines’ own websites, the look-to-book ratios for OTAs or MSEs are in the best case 1,000-to-1 but more commonly above 10,000-to-1”^[1]

The quoted figures used in the whitepaper and referenced above align with our own industry look-to-book experience. Search volume is on a startling upward trajectory as a result of such disruptive trends as the hyperconnected customer, affinity/attribute shopping, large date-range calendar shopping, the rise of metasearch (MSEs), and more. Indeed, any airline planning to compete in a retailing/NDC world needs to be ready!

On an NDC playing field, the airline is responsible for responding to shopping requests, and this comes with an overhead. According to the whitepaper, the pain points associated with high-volume NDC shopping are:

• Cost
• Scalability
• Response Times

Interestingly, those interviewed for the whitepaper maintain a substantial degree of confidence in existing solutions’ ability to handle high-volume NDC transactions, due primarily to cloud-based implementation. However, Mesure is quick to note that as few solution providers have proven experience with high NDC volumes, this level of scalability may yet be put to the test.

In our experience, it is common for airline IT departments to address scalability issues by deploying more (expensive) computing power, which compounds the cost of doing business. Another approach is to employ a cache solution which can increase booking failure rates and neglects to provide the real-time accuracy required for NDC shopping and dynamic pricing.

At Accelya, we believe that in an NDC-enabled marketplace, the airline needs to take ownership of the offer, and this means owning high-performance offer engines which leverage elastic cloud resources. In this way, the airline can cost-effectively meet the responsibilities of performance and accuracy associated with NDC and reap the rewards of better customer engagement.

Rising to the Challenge

In our view, the employment of airline-controlled offer engines is the stand-out solution for mitigating the challenges and costs highlighted in the IATA whitepaper.

1.Effortlessly meet the demands of swelling volumes. New-generation offer engines have been designed from the ground up to respond to high-volume, NDC-shopping requests in milliseconds. Integration of airline-controlled shopping and pricing engines with schedule and availability data from sources outside the traditional ecosystem can simultaneously deliver performant response times, as well as lower the costs (e.g. look-to-book). As an example, our Shopping and Pricing solution delivers this result.

2.Make the right offer at the right time. New-generation offer engines orchestrate a delicate dance between offer and customer. They gracefully craft the offer according to who is searching, where they are in the buying journey, and the attributes available at the time of the request. All this is designed to reduce choice paralysis and time to convert. Airlines can customize offers with simple, known data (for example, preferences of a logged-in user) acting on a dynamic rules engine or by leveraging machine learning (ML) or artificial intelligence (AI) initiatives.

3.Provide consistent offers. Offer engines enable airlines to make consistent offers across channels. Without their use, it is not unusual for airline customers to experience price discrepancies above $10.00 across touchpoints and storefronts, for no logical or commercial reason. Those interviewed in the whitepaper maintain that search results will fall if consumers have confidence that the offer received is the same regardless of touchpoints or storefront. In addition, if distribution partners such as Online Travel Agencies (OTAs) or MSEs have confidence that an offer is consistent across all points of sale (POS), they will be less motivated to make multiple shopping requests.

4.Don’t rely on a cache. The right offer engines do not need to employ cache. As Mesure maintains, cache solutions: “…contradict the premise that NDC will provide personalized offers…indeed, caches tend to generate unproductive shopping transactions just to get refreshed” ^[2]. New-generation shopping and pricing engines, such as those provided by us, don’t rely on a cache to respond to high-volume shopping requests in milliseconds. They simply don’t need to.

Understanding the Relationship Between Offer Strategy and Technical Performance:  Moving Beyond Look-to-Book to Offers-Per-Second

Escalating search volumes are only part of the challenge of ensuring fast, real-time, dynamic offers. The engagement between offer and consumers is critical in determining the quantity and “payload” size of offers sent in response to every search request, and this can have a more significant impact on response times. For example, does the airline’s offer strategy return multiple dynamic fare brands in response to a single offer? Or, is continuous pricing logic adding to the processing time? Moreover, is rich media content included in the response? If an airline’s strategy does not efficiently and appropriately respond to the nature of the offer, it will compound the pressure of escalating NDC volumes.

Understanding an airline’s offer strategy is key to defining the technical performance relationship between airline and consumer. Identifying this early on will enable the airline and its technology partners to properly size the technical infrastructure for optimal performance and customer satisfaction.

We believe being able to anticipate and cost-effectively manage the airline’s required “offers per second” is the next wave of achieving NDC@Scale.