Business simulation case study

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BUS660

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Review "Simulation Case Study: Phoenix Boutique Hotel Group" for this topic's case study, in which you provide guidance to Phoenix Boutique Hotel Group (PBHG) founder Bree Bristowe.

In addition to creating a simulation model, prepare a 500-750-word recommendation for Bristowe's best course of action. Explain your model and the rationale for your recommendations. 2-3 references needed

Use an Excel spreadsheet file for the calculations and explanations. Cells should contain the formulas (i.e., if a formula was used to calculate the entry in that cell). Students are highly encouraged to use the "Simulation Case Study: Phoenix Boutique Hotel Group Template" Excel resource to complete this assignment.

Mac users can use StatPlus:mac LE, free of charge, from AnalystSoft.

Prepare the assignment according to the guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.

This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.

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Simulation Case Study: Phoenix Boutique Hotel Group Phoenix Boutique Hotel Group (PBHG) was founded in 2007 by Bree Bristowe. Having worked for several luxury resorts, Bristowe decided to pursue her dream of owning and operating a boutique hotel. Her hotel, which she called PHX, was located in an area that included several high-end resorts and business hotels. PHX filled a niche market for “modern travelers looking for excellent service and contemporary design without the frills.” Since opening PHX, Bristowe has invested, purchased, or renovated three other small hotels in the Phoenix metropolitan area: Canyon Inn PHX, PHX B&B, and The PHX Bungalows. One of the customer service enhancements Bristowe has implemented is a centralized, toll-free reservation system. Although many customers book specific hotels online, the phone reservation system enables PBHG to find the best reservation match at all properties. It has been an excellent option for those customers who have preferences regarding the type of room, amenity options, and the best price across the four hotel locations. Currently, three agents are on staff for the 6 a.m. to 2 p.m. call shift. The time between calls during this shift is represented in Table 1. The time to process reservation requests during this shift is in Table 2. Table 1: Incoming Call Distribution Time Between Calls (Minutes) 1 2 3 4 5 6 Probability 0.13 0.23 0.27 0.19 0.15 0.09 Table 2: Service Time Distribution Time to Process Customer Inquiries (Minutes) 1 2 3 4 5 6 7 Probability 0.19 0.17 0.16 0.15 0.11 0.08 0.03 © 2018. Grand Canyon University. All Rights Reserved. Bristowe wants to ensure customers are not on hold for longer than 2 minutes. She is debating hiring additional staff for this shift based on the available data. Additionally, Bristowe and PBHG will soon be featured in a national travel magazine with a circulation of over a million subscriptions. Bristowe is worried that the current operators may not be able to handle the increase in reservations. The projected increase for call distribution is represented in Table 3. Table 3: Incoming Call Distribution Time Between Calls (Minutes) 1 2 3 4 5 6 Probability 0.26 0.27 0.24 0.14 0.11 0.06 Bristowe has asked for your advice in evaluating the current phone reservation system. Create a simulation model to investigate her concerns. Make recommendations about the reservation agents. 2 Arrival Interval Distribution Random Number Lower Limit Probability 0.13 0 0.23 11 0.27 32 0.19 54 0.15 74 0.09 90 Service Time Distribution Random Number Lower Limit Probability 0.19 0 0.17 20 0.16 39 0.15 57 0.11 74 0.08 87 0.03 97 Customer Number 1 2 3 4 5 6 7 8 9 10 11 12 Random Number 43 61 41 61 69 21 89 17 86 53 12 36 Range Upper Limit Arrival Gap Minute 10 31 53 73 89 99 1 2 3 4 5 6 Range Upper Limit Service Time (minutes) 19 38 56 73 86 96 99 1 2 3 4 5 6 7 Arrival Gap Random Number 77 29 39 26 54 96 77 71 31 5 4 69 Service Time Arrive Time Summary for This Trial Run max 13 14 15 27 45 70 20 59 75 Service Start Service End Time in System Summary for This Trial Run Average: maximums Time on Hold Time Server Idle Percent Utilization
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Filename: call center simulation exercise PLAG.docx Date: 2018-06-04 13:11 UTC
Results of plagiarism analysis from 2018-06-04 13:13 UTC
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PlagLevel: 3.0%
[0] (2 matches, 1.7%) from your PlagScan document "milestone 3.docx" dated 2018-05-31
[1] (1 matches, 0.7%) from https://en.wikipedia.org/wiki/Pascal's_constants
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Analyzed document
=====================1/7======================
Running head: PBHG SIMULATION 1
PBHG Simulation
(Name)
(Course)
(Date)
=====================2/7======================
PBHG SIMULATION 2
PBHG Simulation
The present report summarizes the key conclusions derived from the simulation analysis
carried out. The main goal of such simulation is to evaluate whether or not the customers are on
hold for more than 2 minutes when calling to the call center at the Phoenix Boutique Hotel
Group. Tables 1 and 2 summarize the collected information by the manager. In this regard, table
1 summarizes the time between calls, while table 2 summarizes the time to process the
reservation of the customer during the call.
Table 1. Arrival calls
Probability
Arrival Gap
Minute
0.13 1
0.23 2
0.27 3
0.19 4
0.15 5
0.09 6
Table 2. Service time
Probability
Service Time
(minutes)
0.19 1
0.17 2
0.16 3
0.15 4
0.11 5
0.08 6
0.03 7
Table 3, on the other hand, summarizes the expected arrival intervals resulting after the
potential increase in the reservations due to the advertising of the hotel on a national travel
magazine.[0]
=====================3/7======================
PBHG SIMULATION 3
Table 3. New expected arrival intervals

Probability
Arrival Gap
Minute
0.26 1
0.27 2
0.24 3
0.14 4
0.11 5
0.06 6
Description of the simulation process carried out
The simulation process used in the evaluation of the hold time of customers calling to
reserve a room at the Phoenix Boutique Hotel Group estimates the hold time of the calls
considering both the time incoming calls arrival rate and the service rate. In this regard, it assigns
two random numbers to a potential customer, corresponding to both the minutes of arrival gap
and the service time. The limits used to delimit the assigned random numbers are based on the
probability recorded or expected by the hotel manager. For instance, considering that the sum of
the probabilities corresponding to a service time of up to 7 minutes is of 89%, the assigned
random numbers vary between 0 and 89, as shown on table 4:
Table 4. Random n...


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