Restaurant Revenue Management at Chevys: Determining the Best Table Mix

Abstract

Revenue management has been used in a variety of industries and generally takes the form of managing demand by manipulating length of customer usage and price. Supply mix is rarely considered, although it can have considerable impact on revenue. In this research, we focused on developing an optimal supply mix, specifically on determining the supply mix that would maximize revenue. We used data from a Chevys restaurant, part of a large chain of Mexican restaurants, in conjunction with a simulation model to evaluate and enumerate all possible supply (table) mixes. Compared to the restaurant's existing table mix, the optimal mix is capable of handling a 30% increase in customer volume without increasing waiting times beyond their original levels. While our study was in a restaurant context, the results of this research are applicable to other service businesses.

Restaurant Table Management to Reduce Customer Waiting Times

“…The result on seat occupancy confirms the logic that the best table assignment policy produces high flexibility of seating large parties and contributes to high seat occupancy by serving more customers. Our logic is consistent with the conclusion made in other studies that the best table mix resulted in more effective capacity and increased RevPASH with an increase in customer volume (Kimes & Thompson, 2004;Thompson, 2002Thompson, , 2003. Bertsimas and Shioda (2003) developed mathematical models to assist in deciding when to seat an incoming party to enhance revenue.…”

“…Matching a larger party of customers with combined tables can achieve higher seating occupancy, which eventually leads to higher revenue (Kimes & Thompson, 2004;Thompson, 2002Thompson, , 2003. Restaurants configured with combinable tables offer the flexibility to serve larger parties.…”

“…For a 200-seat restaurant, the 50% combinability level yielded higher Rev-PASH than did dedicated tables for 54% of the possible configurations. As an extension of the previous study, Thompson (2003) Kimes and Thompson (2004) examined the table mix for a specific mid-scale, full-service restaurant, and recommended and implemented the ideal table mix that resulted in more effective capacity and increased RevPASH with an increase in customer volume. Bertsimas and Shioda (2003) developed optimization models using mathematical models to determine when to seat a party to achieve higher revenue.…”

“…According to Bertsimas and Shioda's (2003) communication with the owner and manager of Soto's in Atlanta, restaurant floor managers make a considerable difference in the financial outcome by deciding when and where to seat customers. Efficient table management can increase revenue by increasing table turnover (Kimes & Thompson, 2004;Thompson, 2002Thompson, , 2003. For example, restaurant tables can be combined to handle parties of any number of customers.…”

“…This strategy should lead to higher service quality and increased customer satisfaction. Despite recognizing the benefit of managing tables, researchers have traditionally limited their focus to revenue management (Bertsimas & Shioda, 2003;Kimes & Thompson, 2004;Thompson, 2002Thompson, , 2003. For the objective of revenue maximization, those studies incorporated maximum tolerance wait time into their table mix model and used the wait time as a constraint.…”