Every consumer wants to be reassured that their purchase is performing to the best of it’s ability and they are doing everything possible to maximize the utility of their investment. Revenue Management departments at transportation companies globally are no exception to this. Though it is widely accepted in the airline and cruise ferry world that a Revenue Management System (RMS) can boost the top line, the challenge frequently encountered is in determining how significant these revenue benefits are. So while the why and how Revenue Management can positively affect a company are taken for granted, by how much is a question that every Revenue Management manager spends many a sleepless night contemplating.
Obviously, during the procurement process, an airline or cruise ferry will have to make the purchase based on empirical evidence and results reported by earlier adherent of RMS in order to justify their investment. However each company has it’s own distinct operational and strategic objectives that impact revenue and so empirical results at other companies are understandably received with a bit of skepticism. However, once an RMS has been deployed, companies have the opportunity to measure the value the system is providing. Savvy algorithms that strive to provide an indication of how much revenue opportunity has been realized through automation and optimization sciences are present in a number of sophisticated RM systems. These models typically tend to simulate two scenarios – one with no or completely inoptimal revenue management – this reflects the worst case scenario. The second scenario is diametrically opposite to the first and is best case scenario that assumes that optimal revenue management principles have been employed. These models are typically run after the departure on historical data so the revenue minimization and maximization algorithms can be applied with the benefit of hindsight. The third component used in these models is the easiest to compute as it is based on the actual observed results. Using these statistics, supervisors get invaluable insight into the available revenue opportunity, the amount realized, and that unrealized due to various reasons including spoilage, dilution and overbooking. Identifying and analyzing poorly performing departures along with associated causes can greatly help guide informed decisions on future departures as there exists the opportunity to learn from missteps of the past.
However a word of caution is very much in order regarding these approaches to determine revenue performance. As with any system, and especially in the case of a data intensive discipline like Revenue Management, the quality of the results is heavily dependent on the robustness and reliability of the input data. As the saying goes, Garbage in, Garbage out. So a great deal of care should be taken to ensure that the inputs are accurate and outliers are detected and ignored. Supervisors should also be cognizant of some of the assumptions that these models make which may not totally reflect reality and also be wary that system recommendations may not be taking into account external factors that are invisible to the system. However it is still possible to glean valuable inferences through intelligent analysis of the figures. It is also extremely important that the RM departments realize that the value of these exercises lies in learning from historical performance and any attempt to engage in a blame game where analysts are being targeted as reasons for less than satisfactory revenue performance in the past is not only unfair but obviously can be counter- productive.
How does your company quantify revenue benefits? Please share your experiences and thoughts with us. If you require more insight into this process, please don’t hesitate to reach out to me at