Dynamic pricing – The next revolution in RM?

Abstract

Thomas Fiig is director, chief scientist at Amadeus, where he is responsible for revenue management strategy and scientific methodologies. He holds a PhD in Theoretical Physics and Mathematics and a BA in Finance from the University of Copenhagen, Denmark. He has published several articles, recently focused on methodologies for origin-and-destination forecasting and optimization of simplified fare structures. He serves on the editorial board of the Journal of Revenue and Pricing Management.Oriana Goyons is a product definition analyst in the revenue management area at Amadeus. Currently, she is constructing the dynamic pricing product. She earned her master's degree in Operations Research from INPG Institut National Polytechnique and her engineering degree from ENSIMAG in Grenoble, France.Robin Adelving is a software development engineer at Amadeus, and a main contributor to the development of the Altéa Benchmarking Engine (ABE) simulation tool. Currently, he works in revenue management and operations research. He holds an engineering degree in Mathematics and Computer Science from ENSIMAG in Grenoble, France.Barry Smith is a freelance engineer specializing in pricing, revenue management and air transportation scheduling. While at American Airlines and Sabre, he developed many of the revenue management techniques used throughout the airline industry and pioneered the application of revenue management techniques in other industries. He holds patents in reservation system design, scheduling, pricing, operations and online retailing. He is an AGIFORS past president and Fellow. He led a team that received the Edelman Award and INFORMS Revenue Management Section Prize for their work on revenue management at American Airlines.ABSTRACT Existing revenue management systems (RMS) base their recommendations on historic observations and do not explicitly consider competition. This means that RMS recommendations often are not appropriate for real-time competitive situations. Dynamic pricing (DP) is an extension of RMS that dynamically calculates the optimal price, taking into account the airline's strategy, customer-specific information and realtime alternative offerings. By optimizing the contribution within the shopping session, DP has a more current and detailed view of demand and can improve RMS performance. We investigated the performance of DP using two simulators, Altéa Benchmarking Engine and Passenger Origin Destination Simulator and demonstrate that DP can deliver substantial revenue benefits with no modification to existing revenue management (RM) processes. However, the deployment of DP into the airline distribution process will be a challenge, because it affects all shopping and downstream processes, such as ticketing, servicing, revenue accounting, RM and interline settlement, that rely on information from existing fare aggregators. Nevertheless, the potential benefits of DP are so compelling that we believe the effort to bring this technology into practice is warranted.

Dynamic pricing mechanisms for the airline industry: a definitional framework

“…For other authors, dynamic pricing represents an evolutionary leap from the pricing and RM practices used by airlines today. Fiig et al (2016) describe dynamic pricing as a "dynamic calculation of the optimal price, taking into account the airline's strategy, customer-specific information, and real-time alternative offerings," while Kumar et al (2018) view dynamic pricing as "varying pricing over a continuous interval instead of opening and closing fare classes." Under this latter definition, dynamic pricing would not be possible using traditional airline distribution technologies, which transmit and display the availability of a small number of pre-priced fare products.…”

Continuous pricing algorithms for airline RM: revenue gains and competitive impacts

“…To quantify the revenue potential of new RM developments enabled by NDC, some authors studied the competitive impacts of dynamic price adjustment heuristics. Fiig et al (2016) and Wittman (2018)…”

From product-oriented flight providers to customer-centric retailers: a dynamic offering framework and implementation guidelines for airlines

“…Using currently emerging new data-driven pricing solutions, optimizing the pricing of an offer will bring significant margin improvements. Regardless of whether airlines focus on value-based or competition-based pricing strategies, real-time observable information can enhance pricing based on more accurate estimations of customers’ WTP or improved competitive position, such as faster competitor price matching (Fiig et al 2016 ). Considering the aim of enabling continuous (instead of discrete) price curves, the pricing step is referred to as continuous pricing .…”

“…Considering the fundamental change from fare-filing-based product orientation to customer-centric airline retailing, aligning organizational processes, culture, and employee capabilities to airlines’ targeted retailing approaches is inevitable. It has already been emphasized that current airline processes need to be adjusted in order to support more dynamic price updates (Fiig et al 2016 ). The creation of customer-centric offers spans internal product, pricing, and distribution departments, external partners and marketing, sales, distribution, and service delivery processes.…”