A Tool for Optimizing the Efficiency of Drive-Thru Services

Abstract

Daily, companies compete for customers in order to increase their revenue. The food industry, and in particular, very large restaurant chains, are no different. Customers are drawn to the opportunity to conveniently retrieve their food with minimum wait times using drive-thru services. While such services are not new and are used by a large number of restaurants, the fundamental paradigm (i.e., the configuration of employee agents and their interaction with consumer agents) through which drive-thru services continue to be used is difficult to observe in a meaningful way. Recently, with the onset of the COVID-19 pandemic, drive-thru services were heavily relied upon to provide much of the limited person-to-person contact service necessary to help reduce the spread of disease. While this presented many opportunities for existing businesses to scale their operations, it also revealed many inefficiencies with drive-thru services and the way they conduct their business, leading to longer waiting times. This paper addresses this issue by developing a simulation-based tool for identifying inefficiencies in existing drive-thru services. The tool allows a range of both employee and customer agent scenarios to be tested, providing important situational awareness for restaurant owners. Questions that the tool can help businesses answer include: identifying the most optimized configuration for minimizing customer wait times due to resources constraints (e.g., employee availability), possible impacts to business with switching strategies, and service point bottlenecks. A set of best practices, in line with industry standards and based on a review of the literature, were used in the design phase of this work. The developed tool is open-sourced1 and presents an interactive and easy-to-use interface that businesses can use to improve their service wait times.