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 Pradeep.bandla@rtscorp.com.
Pradeep Bandla
VP, Product Management and Marketing
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