Revenue managers know it best: one thing is to get insightful data when they are monitoring competitive movements. However, understanding trends and figures for key variables such as pricing in any place and time, in order to make timely responsive decisions, is something very different.
Airnguru was a “refreshing novelty” of the two-day Aviation Festival Americas in Miami, thanks to a user-friendly competitive analysis tool, during a conference where Big Data analytics was a recurrent discussion.
Artificial intelligence and data science isn’t new in the airline industry. However, its development has only recently begun to make a leap forward for two reasons:
Internet, the enabler; Low Cost Carriers, the flagships
We (the elder) remember those obscure times when legacy carriers were trapped by the oligopoly of the Global Distribution Systems (GDS's) outspread through their exclusive brick & mortar travel agency partners, and had no control of their ever growing distribution costs ("the distribution cost trap"). I remember those times when total distribution costs (including travel agent commissions, booking costs, sales office costs, etc) represented around 20%-25% of legacy airlines' revenues.
The current airfare management model has become outdated regarding data analysis. While other industries have taken advantage of big data analytics, airline pricing is still behind regarding market insight, reducing its flexibility and capacity to respond to market trends, competitive moves and customer demands.
Unexpected time zone changes are common around the world. Authorities, when deciding on changing a time zone, don't seem to understand the holistic and negative impacts they cause. They disrupt our agendas at work, generating confusion and lost productivity for weeks and sometimes for months. Computer operating systems, smartphones, productivity software, etc, loose synchronization. Time zone changes also represent a challenge in the management of risk. In the airline indusrty, time zone changes have logistical, financial and commercial consequences, affecting airport operations, flight itineraries, distribution and, of course, passenger service and airlines' costs.
In a previous post we spoke about fuel, exchange rates and other variables influencing pricing strategies. Today we will focus on a single, external variable, that affects the potential benefit of pricing strategies.
One of the most relevant tasks for an airline is making sure that the investment they made in fleet and itinerary gets the maximum possible return. This task is in the hands of several "post itinerary" functions within the airline, involving at least pricing, revenue management, sales and marketing teams, which, empowered by sophisticated analytics, make their best efforts to maximize the expected net revenues.
However, there are external barriers that constrain the growth potential of the airline and limit the power of the airline's pricing strategies. Some of these constraints may produce a relevant social detriment, because they limit the service quality and growth potential of the airline business as a whole and thus, they damage the economy. It may be the case, for example, of airport taxes and fees.
A few months ago, an innovative and revolutionary start-up airline was launched at the APEX Expo 2015. It wasn’t Richard Branson with a new version of Virgin, or Mark Zuckerberg investing in the airline industry. It was Poppi, an airline whose approach to air travel is similar to Starbucks’ love for coffee: consumers don’t pay for the service, but the experience.
Pricing and revenue management teams aim at maximizing the expected net revenues produced from a given itinerary. Their fundamental levers are the price structures (demand segmentation rules and price levels) and the inventory allocation (demand forecasts and inventory optimization and allocation). Robust airline pricing and revenue management strategies involve the analysis and visualization of some critical variables and their long term behavior. These variables affect the optimum prices and inventory allocation directly or indirectly, in sometimes complex ways and substantial amounts.