The Disruption of Legacy Technologies via Software: Airlines

By: Marcus Stroud  |  11.01.2020  |  TXV's Thoughts

Kambr is a company founded by airline operators and executives to solve the most pressing problems of any industry: the inability of legacy actors to fully leverage emerging technologies. In TXV’s B2B focus, this is perhaps the singular problem that we focus on: backing companies bringing new technologies to market that will enable customers to succeed in a technological environment that is constantly changing.

As with all highly regulated industries, the air travel industry has razor-thin margins. The airlines that we all know – American, United, Delta, and Southwest- have an average ticket price of $150, and, of that, only $20 is profit. The industry upon which we rely to take us safely from coast to coast and, indeed, across oceans, is making remarkably little on the conveyance of a passenger safely, from gate to gate. The advent of newer systems, such as online travel advisors (OTAs) like Expedia, has made the problem even more pressing, as most of us can compare, in real-time, the various prices offered by different airlines. As airlines have begun to sub-segment themselves into ultra-low-cost carriers, low-cost carriers, and legacy carriers, with their attendant fee structures, purchasing decisions have become even more dynamic and nuanced for the consumer.  

Kambr steps in to solve that problem with its software of revenue management. Revenue management is the ability of service providers to intelligently price their offerings in such a way that maximizes the ability of the carriers to make a profit. 

In their view and ours, incumbent revenue management systems utilized by airlines have two dual problems. The first is that airlines have a limited data set to price their flights from the get-go. Aside from the most advanced airlines, of which Delta is the most technologically advanced, the data that is used is historical. RM departments at airlines would take the average price of a ticket from Austin to San Francisco, say, and that would be the starting offer. Airline prices, in this light, are better understood as a bidding system than an offer system. Airlines are not able to 1) leverage different streams of data to create more dynamic models of customer demand, and 2) use machine learning to sub-segment customers in a way that identifies the price-sensitivity of each customer and their price-elasticity, allowing the airline to both charge them more on the ticket of a flight as well as identify their proclivity to purchase ancillaries (checked baggage, meals and drinks on flights, etc.). The second problem is the software itself that is currently being used at airlines. These software systems have not been updated to reflect even the basic updates in the field of user interface and user experience, and analysts often find themselves switching into Excel when there are problems that are particularly hard to solve. 

We took a deep look at the industry, and we realized that the fundamental thesis of the lack of adaptation to technological progress was correct. In our conversations with airlines, we were told that they were desperate for new solutions, and their needs have become even more acute since the advent of the COVID age. When an airline accustomed to datasets of 60 years, as in the case of American Airlines, can hardly rely upon data sets of two weeks, it means that their toolbox is exhausted. Furthermore, and perhaps more importantly, Kambr has the most technologically dynamic offering on the market, bar none. We spoke to the companies that Kambr competes with, the companies that Kambr’s technology works alongside, and we spoke to McKinsey, with whom Kambr has just signed an exclusive partnership to implement their software as part of McKinsey’s regular engagements with airlines. The message was consistent and clear- this industry requires new solutions, and we have backed the only one.