Opening Vignette: Intercontinental Hotel Group Uses Decision Rules for Optimal Hotel Room Rates Introduction With 4,437 hotels and 647,161 rooms, InterContinental Hotel Group (IHG) is the worlds largest hotel group in terms of number of rooms. About 85 percent of its hotels are franchised, 14 percent are managed, and 1 percent are owned directly by the InterContinental Hotel group. Some of the hotel brands that belong to this group are Holiday Inn, Holiday Express, Staybridge Suites, and Crowne Plaza. Revenue generated from their rooms amounts to around $20 billion. Before the optimization model was implemented, pricing decisions were made based on a complex myriad of variables, some of which were day of the week, seasonality, occupancy level, competition, and customer feedback. These decisions were made without the use of analytics. Price decisions were made with the assumption that demand was independent of the price charged for a room. This fundamental flaw worked well in normal economic conditions. However, when the hospitality industry suffered a decline in revenue, with the challenge posed by the widespread use of the Internet, which introduced multiple distribution channels, IHG started considering and exploring alternative and effective revenue generation methods. The main aim was to increase the revenue per available room (RevPAR). Methodology/solution IHG rolled out their retail price optimization system to help increase their RevPAR. The large number of hotels was a big challenge to this task. Pricing decisions numbered over 273 million (or 76,000 per hotel) per day. The project resulted in a change of their fundamental business flow. The final model included a demand forecast model, market response model, competitor rates model, and an optimization price model. For each hotel, a price response is calculated by the market response model based on historical data. Price and competitor rates were used to estimate the demand for rooms. The objective function used in this computation turned out to be nonlinear. The input data for the competitor rates model were derived from third-party sources. Decision variables used to determine the best rates for each hotel were based on factors like estimated demand, hotel capacity, current bookings, and prices being charged by competitors. IHGs price optimization system is packaged in a Web application called PERFORMsm. Results/benefits There has been widespread adoption of the retail price optimization model by hotel managers globally. PERFORM is used by over 4,000 users worldwide. The retail price optimization model was tested in a couple of IHGs hotels and the results were compared with hotels where the model had not been implemented yet. It was recognized that there was a 2.7 percent increase in RevPAR for hotels where the optimization model had been implemented Questions for the Opening vignette 1. Describe the challenges faced by IHG during development of their retail price optimization system. 2. Besides the hotel business in the hospitality industry, explain at least three other areas where an optimization model could be used. 3. What other methods could be used to solve IHGs price optimization problem? What we can Learn from this vignette IHG has been doing business using manual price optimization methods for a long time and it seems to have worked for them. However, sometimes business environments change, which renders existing methods of running a business obsolete. IHG used data analytics and mathematical optimization methods to revolutionize revenue management. The price optimization model was a combination of different operations research methods. What is also important is that such decisions are eventually implemented using a decision system that is available to each client hotel. They do not have to know anything about the underlying decision methods to be able to use the recommendations made by the system