Park Winter Hotel Case Study

Embry Riddle Aeronautical University

MGMT 524
Abstract

This case study will focus on the restructuring of the Park Winter Hotel front desk to reach an optimum level of staff efficiency and guest service. At present, the hotel has five clerks on duty, each with a separate waiting line, during peak check-in time of 3:00 P.M. to 5:00 P.M. Observation of arrivals during this period shows that an average of 90 guests arrive each hour (although there is no upward limit on the number that could arrive at any given time). It takes an average of 3 minutes for the front-desk clerk to register each guest. Ms. Shader believes the key to reducing her wait time is in one of the three plans she is considering. First would like to consider making a line for corporate guests only, second she is considering making a single queue and feeding the five tellers from the single queue. The final option Ms. Shader is considering is using an automated teller machine (ATM). This case study will show Ms. Shader of Winter Park Hotel how to reduce waiting times for her guests during peak hours. The data collected during this case study will be presented along with a recommendation to Ms. Shader on which option has the shortest wait time for guests.

Introduction

First, the researchers determine the average amount of time a guest spends checking in and how this wait time would this change under each of Ms. Shrader’s three options. We will provide her with a recommendation as to which option would best serve her guests.

Baseline Data

The current system has five clerks each with their own waiting line or five independent

queues, each with an arrival time of = 90/5 = 18 per hour. The service rate is one every three

minutes or m = 20 per hour. Assuming Poisson arrivals and exponential service times, the

average amount of time that a guest spends waiting and checking-in is given by:

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Baseline Data

Deriving 30% of the arrivals, which corresponds to = 0.3 x 90 = 27 per hour are

diverted to a quick-serve clerk who can register them in an average of two minutes (m = 30 per

hour), their average time in the system is be 20 minutes. The other 90-27= 63 /hour distribute

themselves in the four remaining slow servers each with = 63/4 = 15.75 per hour, with each of

whose mean service time is 3.4 minutes or 0.5667 hours, which means m = 1/0.5667 = 17.65 per

hour. The average time in the system for these guests will be 0.53 hours or 31.8 minutes. The

average time in the system for these guests in the slow servers is 0.53 hours or 31.6 minutes. The

average time for all arrivals would be 0.3 x 20 + 0.7 x 31.8 = 28.3 minutes.

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Quick Server

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Slower Servers

A single waiting line for the five clerks yields an M/M/5 model, in this case = 90 per

hour, m = 20 per hour. The average time in the system is Ws = 7.6 minutes.

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Single Waiting Line

By using an ATM having the same service rate as the clerks, which is 20/hour to 20% of

arrivals, which is 18/hour would give the same average time as for these guests in the current

system, which is 30 minutes. The remaining = 72 per hour form an M/M/4 or M/M/5 system.

With four servers, average time in the system is 8.9 minutes, resulting in an overall average is:

0.2 x 30 + 0.8 x 8.9 = 13.1 minutes.

With five servers, we find the average time is 3.9 minutes resulting in an overall average is

0.2 x 30 + 0.8 x 3.9 = 9.1 minutes

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Utilize ATM

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Four Servers

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Five Servers

Based on all this analysis, the single waiting line, with five clerks is the best option

among all the options explored with Ws = 7.6 minutes.

Reference

Render, B., Stair, R. M., & Hanna, M. E. (2012). Quantitative analysis for management (11th ed.). Upper Saddle River, NJ: Pearson Education, Inc.