Marriott Rooms Forecasting
Marriott Rooms Forecasting
Executive Summary
In the case of the Hamilton hotel, Snow needs to make a decision as to if 60 additional rooms reservations should be accepted which could lead to overbooking (Weatherford & Bodily,1990). It is a problem of capacity utilization that is being faced in this particular case where revenue maximization is aimed while minimizing customer dissatisfaction.
In this report the case is put forward and various methods have been chosen to come to a sensible conclusion. Firstly the raw data provided is used and the exponential smoothing model (ESM) is used to predict the outcome of guests on Saturday the 22nd of August. Next basic statistics are used and standard deviation is calculated with which the probability of the number of outcomes is concluded. Finally the most likely situations are analyzed and discussed like a lay man and the revenue is calculated to conclude which option should be suitable and concluding that the most likely scenario will be the 5th option.
In all the calculations through different methods used one can conclude that Snow should accept the 60 rooms reservations as the turnout in weekends is comparatively low when the historical data is analyzed. Thus to maximize capacity utilization and revenue the tours reservations should be accepted.
Table of Contents
Sr. No. Title Page No.
1 List of Tables and Figures 4
2 Background and Issue Statement 5 • Background 5 • Issue Statement 6
3 Analysis of the Problem 6 • Data Analysis and Forecasting: Choice 1 7 • Data Analysis and Forecasting: Choice 2 8 1. Scenario 1
2. Scenario 2
3. Scenario 3
4. Scenario 4
5. Scenario 5
6. Scenario 6
7. Scenario 7 9
9
9
9
10
10
10
4. Limitations and Recommendations 10 • Limitations 10 • Recommendations
1. Occupancy Maximizing
2. Minimize Cancellations
3. Forecasting and Reservation Policies
4. Customer Loyalty 11
11
11
11
12
5 References 12
6 Appendences 13
List of
Executive Summary
In the case of the Hamilton hotel, Snow needs to make a decision as to if 60 additional rooms reservations should be accepted which could lead to overbooking (Weatherford & Bodily,1990). It is a problem of capacity utilization that is being faced in this particular case where revenue maximization is aimed while minimizing customer dissatisfaction.
In this report the case is put forward and various methods have been chosen to come to a sensible conclusion. Firstly the raw data provided is used and the exponential smoothing model (ESM) is used to predict the outcome of guests on Saturday the 22nd of August. Next basic statistics are used and standard deviation is calculated with which the probability of the number of outcomes is concluded. Finally the most likely situations are analyzed and discussed like a lay man and the revenue is calculated to conclude which option should be suitable and concluding that the most likely scenario will be the 5th option.
In all the calculations through different methods used one can conclude that Snow should accept the 60 rooms reservations as the turnout in weekends is comparatively low when the historical data is analyzed. Thus to maximize capacity utilization and revenue the tours reservations should be accepted.
Table of Contents
Sr. No. Title Page No.
1 List of Tables and Figures 4
2 Background and Issue Statement 5 • Background 5 • Issue Statement 6
3 Analysis of the Problem 6 • Data Analysis and Forecasting: Choice 1 7 • Data Analysis and Forecasting: Choice 2 8 1. Scenario 1
2. Scenario 2
3. Scenario 3
4. Scenario 4
5. Scenario 5
6. Scenario 6
7. Scenario 7 9
9
9
9
10
10
10
4. Limitations and Recommendations 10 • Limitations 10 • Recommendations
1. Occupancy Maximizing
2. Minimize Cancellations
3. Forecasting and Reservation Policies
4. Customer Loyalty 11
11
11
11
12
5 References 12
6 Appendences 13
List of
References: Ferguson, M. E., Crystal, C. R., Higbie, J., & Kapoor, R. (2007). A Comparison of Unconstraining Methods to Improve Revenue Management Systems (ed. 3). Netessine, S., & Shumsky, R. (2002). Introduction to the theory and practice of yield management. INFORMS Transactions on Education, 3(1), 34–39. Retrieved from http://archive.ite.journal.informs.org/Vol3No1/NetessineShumsky/ Noone, B. M., & Lee, C. (2011). Hotel Overbooking: The Effect of Overcompensation on Customers’ Reactions to Denied Service. Journal Of Hospitality & Tourism Research, 35(3), 334. doi:10.1177/1096348010382238 Weatherford, L., & Bodily, S Weatherford, L., & Bodily, S. E. (1990). Seasonality in time forecasting. Darden Business Publishing. (UVA-QA-0407).