by 2000, virtually all major airlines, hotel firms, cruise lines and rental car firms had implemented revenue management systems to predict customer demand and optimize available price. these revenue management systems had limited "optimize" to imply managing the availability of pre-defined prices in pre-established price categories. the objective function was to select the best blends of predicted demand given existing prices. the sophisticated technology and optimization algorithms had been focused on selling the right amount of inventory at a given price, not on the price itself. realizing that controlling inventory was no longer sufficient, intercontinental hotels group (ihg) launched an initiative to better understand the price sensitivity of customer demand. ihg determined that calculating price elasticity at very granular levels to a high degree of accuracy still was not enough. rate transparency had elevated the importance of incorporating market positioning against substitutable alternatives. ihg recognized that when a competitor changes its rate, the consumer's perception of ihg's rate also changes. working with third party competitive data, the ihg team was able to analyze historical price, volume and share data to accurately measure price elasticity in every local market for multiple lengths of stay. these elements were incorporated into a system that also measured differences in customer elasticity based upon how far in advance the booking is being made relative to the arrival date. the incremental revenue from the system was significant as this new price optimization capability increased revenue per available room (revpar) by 2.7%. ihg and revenue analytics, a pricing and revenue management consulting firm, were selected as finalists for the franz edelman award for achievement in operations research and the management sciences for their joint effort in implementing price optimization at ihg.