Price Elasticity and Demand Change Indicators
By Paul Wood Vice President of Revenue Management, Greenwood Hospitality | October 06, 2013
Many first generation revenue managers have been taught demand is a correlative function based on market place or external compression. At the same time, we've been taught rational pricing is the consumer's desire and willingness to pay for goods and/or services. What makes the Hospitality industry different from most other industries is variable pricing based upon demand factors. As example, if Apple understands their new product has an extremely high demand, Apple is not able to instantly elevate their pricing model until the next sales cycle or upon the delivery of a new model. This is but one case wherein the hospitality industry varies from retail and many other sectors. Our inventory cycle is every 24 hours and therefore demand fluctuates more fluidly than other retail sectors.
When talking about demand and pricing, revenue managers must clearly delineate the basic fundamental that correlation of demand does not equate to causation of demand. As we break down correlation and causation, a clear line of causation must be established when understanding how, why, when and where demand has come from. Additionally, once an understanding of the causation per occurrence has been established, our understanding deepens as to what amount of price elasticity the various reservations sources are willing to pay. As a result of factoring gathered data, the revenue manager is able to properly adjust the pricing factor.
Correlation of demand focuses primarily on external demand factors which would stem specifically from the market place and various competitors. As an example, factoring the occurrence of an annual in a downtown market and determining its overall effect. The market place in anticipation of downtown demand increases their best available rate. In doing so, the demand curve slopes to a negative when price increases. As a result, demand declines due to the amount of pricing being greater than the consumer is either willing or able to pay for their stay. In situations where rates increase the amount of additional demand versus rate growth needs to be at par with or slightly greater than the total demand potential for the hotel. Otherwise not all rooms are sold. Based on the conditions of internal demand and external demand, rates will decline or increase due to the amount of the total potential.
Since revenue is simply price multiplied by quantity purchased, the hotel must understand what effect changing the price will have on total revenue. Revenue managers usually judge the effectiveness of a rate based on regrets and denials, rather than on potential demand. If there are too many regrets and denials the conclusion would be the rate is too high and an adjustment would be deemed necessary. In revenue management we need to move away from pricing based on regrets and denials. We now have better intelligence sources through revenue management systems or via third party vendors which allow us to use predictive demand thresholds tools to make better decisions on pricing based on demand potential.
(% change in quantity demand) / (% change in price)
The equation represents a relative responsiveness to demand based on price. For example you have a 100-room hotel and 20% of the inventory has been sold at $100. The remaining 80 rooms would be able to be sold at a higher rate threshold because of the lower inventory and thereby lessening of the quantity available to be sold.
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