by Rob van der Mei, Kevin Pak, Maarten Soomer and Ger Koole

Revenue Management (RM) techniques provide a powerful means of increasing revenue, creating new business opportunities for companies in a wide variety of business areas. Recently, the authors have successfully applied RM techniques for one the world’s largest parking companies, creating millions in additional yearly revenue.

Suppose you are sitting in a plane and you ask the person next to you what price he paid for his ticket. It is likely that it will be different from the price you paid for the same ticket. This price differentiation is a result of Revenue Management (RM). While the use of RM techniques is now common practice in the airline industry, these techniques have recently started to create new business opportunities in the parking industry. In a joint effort between CWI, the Dutch company ORTEC and VU University in the Netherlands, the authors have successfully applied RM for one of the world's largest parking companies. This has boosted the company's annual revenue and given it a new competitive edge.

RM is a method for increasing revenue whereby available capacity (for example an airplane seat or a parking spot) is sold in a smart manner by offering different prices to different customers. In order to determine how much capacity can be offered at what moment and at what price, statistical methods and optimization models are to be used.

RM emerged in the 1980s in the airline industry. Today, for many airlines RM makes the difference between profit and loss. For each flight, airlines determine in detail how many seats will be offered at a given moment and price. The commercial success of RM has triggered the interest of other business areas, such as hotels, tour operators and car rental companies.

RM can be used to stimulate demand by offering services at lower prices in a controlled manner during periods when the demand is relatively low. It can be applied to products or services where the amount of capacity is fixed and has only a limited lifetime: the number of seats in an aircraft is fixed and cannot be extended if demand happens to exceed capacity. On the other hand, an empty seat cannot be sold once the aircraft has departed.

In order to be profitable, the available capacity should be offered at different prices. For each flight, the airline determines what fraction of the (remaining) seats are to be offered at what price. Of course, price differentiation is only useful when different groups of customers exist who are willing to pay different prices. These customer groups must also be distinguishable by the selling channel they choose, the time of reservation, or their choice of additional features (such as possibilities for cancellation).

To illustrate the use of RM for airport parking, let us assume for simplicity that a parking company offers a regular price of $10 per hour, but also wants to offer a discount rate at $6 per hour. The company must then identify how many parking spots are likely to be sold at the discount rate. To this end, it is crucial to have good forecasting models that can accurately predict the demand for any given day for the different customer classes based on both historical and current data.

The next step is to use these demand forecasts to optimize the expected revenue. To this end, one needs to determine the maximum number of seats to be sold at the discount rate of $6. This is done by the so-called Expected Marginal Seat Revenue Model (EMSR), which is based on comparing the revenue of one additional parking spot at the regular rate multiplied by the probability of filling that spot against the discount rate. As long as the first exceeds the second, the parking company should reserve this parking spot for customers willing to pay the regular rate; otherwise, the spot should be sold at the discount rate. In this way, it can be easily determined how many parking spots should be reserved for customers willing to pay the regular price.

For one of the world's leading parking companies, we have developed and implemented prediction models and EMSR-based revenue optimization, in combination with smart price differentiation and market segmentation. This has led to a multi-million dollar increase in annual revenue, strongly enhancing the competitive edge of our customer.

To summarize, the use of RM techniques in the airline industry has been successfully applied for one of world's leading parking companies. This case demonstrates the existence of tremendous business opportunities in the parking industry.

The authors are the founders of PreMa, the Dutch national network for Pricing and Revenue Management, in a joint effort of CWI, VU University Amsterdam and the Dutch company ORTEC. The goal of PreMa is to bring together practitioners and researchers to exchange knowledge and experience in the area of RM.

Link:
http://www.prema-netwerk.nl

Please contact:
Rob van der Mei
CWI, Amsterdam, The Netherlands
Tel: +31 20 5924129
E-mail: mei@cwi.nl

Kevin Pak
ORTEC, Gouda, The Netherlands
Tel: +31 18 2540500
E-mail: kpak@ortec.nl

Next issue: October 2019
Special theme:
Smart Things Everywhere
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