FUTURES The future of revenue management and pricing science Phi Hoang Received (in revised form): 1st August, 2006
Walt Disney World E-mail: Phi.Hoang@disney.com
Phi Hoang is currently Director of Decision Science for Revenue Management at Walt Disney World where he is responsible for overseeing the strategic direction for applying operations research and statistical techniques to solve complex revenue management and pricing problems. He has been with Disney since 1995 and has played various leadership roles in Revenue Management and Information Technology. He holds a Master’s Degree in Business Administration from the University of Houston focusing on decision and information technology.
ABSTRACT KEYWORDS: consumer choice modelling, revenue management, price optimisation, measurement
There are ﬁve major areas where the future of revenue management and pricing science will be focusing on. This paper is not meant to recommend the right solution to any particular problem, but its main purpose is to highlight the areas where revenue management and pricing science are still in their infancy, but can be poised to explode and provide high value to organisations. Journal of Revenue and Pricing Management (2007) 6, 151–153. doi:10.1057/palgrave.rpm.5160069
PRODUCT TO CUSTOMER-FOCUSED MODEL Traditional revenue management models focus on predicting demand for products through historical observed demand for those products. These models typically assume the demand for these products are independent of each other; that is, they ignore what alternative products (and their associated prices) were available to the customers at the time of their purchase. Also, little attention has been given to estimate customers’ ﬂexibility in shifting products if their original requests were not met. In the hotel industry, this could mean not only offering an alternative room category, hotel, package, or dates, but also in which order. Ordering is important because some customers will only sit through a couple of offers before abandoning the sales call. Furthermore, companies are still not very good at segmenting customers and selling to these segments appropriately. A lot of companies still treat customers homogeneously. The limitations of these models are usually related to limitations of the data that are available to the company to forecast and optimise. The data captured usually are product-focused and lacks visibility into the behaviour of the customers at the individual level. With the decreasing costs of data storage and more sophisticated sales systems that can track
& 2007 Palgrave Macmillan Ltd, 1476-6930 $30.00 Vol. 6, 2 151–153 Journal of Revenue and Pricing Management 151
Future of revenue management and pricing science
customers’ behaviour during the sales process, there is, however, little excuse for companies to not start capturing demand data at the individual customer level. This type of data can help build these more sophisticated revenue management model that will forecast demand and behaviour at the customer level or at least some sort of customer segmentation. This way companies can be smarter about presenting the right offers to the right guest at the right time and price to maximise proﬁts. Even though this customer-centric revenue management concept is not a revolutionary new concept, it has not been successfully implemented in general. However, the stars are aligned to make customer-centric revenue management be the focus of many companies in the future. This is because companies are starting to understand the right type of data that they need to be capturing, the science to help model these types of problems are becoming more sophisticated such as consumer choice modelling, and proliferation of science software vendors who are willing to tackle such models. INDIVIDUAL TO HOLISTIC PRODUCT PORTFOLIO OPTIMISATION Many companies that sell multiple products still determine...