Swizz Hotel’s Revenue Management Plan

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Table of Contents

Introduction
Revenue Management Plan for Swizz Hotel
Revenue Management Processes
Conclusion
References

Introduction

This report presents a Revenue Management Plan for Swizz Hotel in Switzerland. The Plan would help Swizz Hotel to determine the best room rate and allocation at the right time. It would ensure that all rooms are sold at optimal prices to guarantee the highest revenues. Some economic principles are used for room capacity management, discount allocation, forecasting, and pricing. The Plan will assist Swizz Hotel in three critical areas related to demand and yield management decisions. With the structural decisions, the Plan will assist the team to decide on the selling format, differentiation strategies, and discount terms. On pricing strategies, the Plan will help the team to determine appropriate prices, offer prices, and reserve prices, as well as pricing for a given period across products, and the most effective discount model to prevent revenue loss. Finally, the Plan will also focus on quantity management decisions. Specifically, room quantity allocation to various consumer segments would be important. Moreover, it would be appropriate for the Hotel executive to determine when to reject or admit guests and the most effective time to withhold services and sell later.

Revenue Management Plan for Swizz Hotel

Location and Positioning

Swizz Hotel will be located on the shore of Lake Geneva to offer spectacular views of the Mont Blanc, the Jura Mountain, and the Alps. It will be conveniently located near the airport, train station, and the city center.

Swizz Hotel will be positioned as a luxurious hotel with high-end services, including 24 hours room service, laundry service, business center, and concierge service for business travelers, tourists, and leisure visitors among others.

Marketing

Different marketing strategies will be used to reach various market segments. Swizz Hotel will consider marketing publications in the local dailies, magazines and other traditional channels. Pricing promotion will be applied during low seasons to increase demands and sales volumes. Swizz Hotel will rely on modern tools of communication such as social media to conduct wide marketing campaigns globally while advancing the promise of e-commerce in the industry. In addition, Hotel executives will attend tourism exhibition programs to network with industry peers and competition.

Target Market

Swizz Hotel will only target high-end clients consisting of business travelers, tourists, world political leaders, and leisure visitors, backpackers and solo travelers, couples, and families.

Market Targeting

Swizz Hotel will adopt a differentiated marketing strategy by focusing on different market segments with various services.

Market Penetration

To penetrate the market, Swizz Hotel will use its highest level of services, modern multi-purpose auditorium with large capacity, meeting rooms, and in-house conference/congress and exhibition facilities.

Market Strategies

Only effective channels will be used. For instance, Swizz Hotel will use cost-cutting channels to reach its market segments. It will heavily rely on data from competition and leisure and tourism authorities to understand market conditions and consumer behaviors. All these channels will be coordinated to increase revenues.

Type of Market

Swizz Hotel will operate in a highly competitive market with limited differentiation among established hotels.

Pricing

Swizz Hotel will apply Yield Management strategies to determine what to charge its customers and ensure that services are sold to the right clients, at the most appropriate time, and price (Kimes, Barrash, & Alexander, 1999).

A dynamic pricing method has been adopted for Revenue Management. This pricing strategy would optimize total revenues for Swizz Hotel. It takes into account nights, the pricing factor of a given night and the reserved rooms for the night (Aziz et al., 2011). No reservations for a given night will exceed the capacity for the night.

The pricing model looks into pricing categories consisting of low-priced rooms and high-priced rooms. Low-priced rooms will be left for early bookings. The dynamic pricing model recognizes that more rooms for the low-priced group will result in an increased reservation, but with the possibility of losing significant revenues from high-priced rooms. This implies a lost opportunity for the Hotel. Conversely, when several rooms are reserved in the high price groups, there are possibilities that many rooms could be left vacant. In addition, room pricing is dynamic and could fluctuate across time.

Hence, to overcome this optimization challenge, the pricing model relies on effective forecasting for room future demands. As such, the Hotel will have various scenarios for room demand forecast and determine percentile differences. Every percentile will be used as an estimate figure for demands during price analysis. The dynamic pricing model will assist the Hotel to determine various prices for a given day during the forecasted period. The price reflects the demand. That is, a low demand will have low prices while higher demands will attract higher prices. This pricing model requires multiple demand forecasts to enhance accuracy.

Revenue Management Processes

The Revenue Management Plan will focus on demand management strategies, pricing, discount allocation, capacity management, and duration control (Aziz, Saleh, Rasmy, & ElShishiny, 2011).

Forecasting

Swizz Hotel will focus on demand forecast as a component of Revenue Management. Initial data for forecasting would be obtained from various agencies in the sector. The approach is based on the notion that demands are seasonal in the hotel industry. Demand forecasting will help Swizz Hotel to determine approximate number of rooms it can hold back for the most profitable booking during weekends and other popular days. It is certainly impossible to determine the precise demands during such periods. Nevertheless, reasonable assumptions based on data will assist the Hotel to be realistic about its forecasting and revenue projections (Verret, 2004).

First, Swizz Hotel will use historical data to identify consistent trends to predict possible future patterns. For instance, data for daily, weekly, and monthly bookings will be used to predict future demands. Data obtained from bookings driven by specific events such as poor weather and impulse reservations among others should not be included in data for analysis. Swizz Hotel will use the best data analytics tools to identify patterns, interpret the data, and use information for decision-making on demands. Second, data for demand forecasting will include room types, room rates of occupancy, length of stay, advance bookings, and any other relevant information. Finally, forecasting will be done after every three months and with possibilities of short-term demand forecasting to enhance accuracy.

Capacity Management – Inventory and Optimization

Swizz Hotel will use capacity management to control and restrict room supplies while balancing risks associated with overselling rooms. Data for room booking will be reviewed regularly to determine optimal reservation.

It will also help in identifying the possible number of walk-in guests to accommodate during a given day.

In this case, the primary goals of yield management are to optimize room rates and occupancy rates. Consequently, Swizz Hotel will maximize mean revenue for each available room at any given moment.

Swizz Hotel aims to ensure high profit booking rather than high volumes of occupancy (Boahen, Quansah, & Sarpong, 2013).

Time and space reflect services provided by the Hotel, and unsold space and time lead to a loss of revenue. Various demand forecasting approaches will be used to determine the most appropriate time to increase or reduce room rates. It also helps to determine when to accept or reject room reservation with the aim of maximizing incomes.

While the overall objective is to optimize the dollar amount, it would be difficult to achieve this by relying solely on increased room rates because of various factors that influence room demands at any given period. Thus, the Yield Management strategy strives to determine the best approach for balancing costs, room rates, and rates of occupancy for optimal revenues.

Discount Allocation

Swizz Hotel will restrict the period and product and service mix offered at discounted rates. Further, it will restrict discounts based on the type of room while encouraging sales as a reaction to customer behaviors (Donovan, 2005).

Length of Stay

During concerts, sporting activities and any other festivals, the Hotel will benefit from the increased demands by curtailing discounts on room rates or insisting on lesser length of stay and maximum length of stay to restrict large discounts of rooms.

Monitoring

When the low occupancy rates increase and become unavoidable particularly during low seasons, Swizz Hotel will focus on low rate customer segments, concentrate on price-sensitive guest, promote special discounts for various groups, and review new rates to boost revenues (Bartnick, 2014).

Conclusion

This Revenue Management Plan will assist Swizz Hotel, a luxurious hotel to ensure a sustained revenue growth, control costs, and manage inventory. In addition, it would ensure that Swizz Hotel establishes itself among the most competitive hotels in the country.

References

Aziz, H. A., Saleh, M., Rasmy, M. H., & ElShishiny, H. (2011). Dynamic room pricing model for hotel revenue management systems. Egyptian Informatics Journal, 12(3), 177–183.

Bartnick, F. (2014). Changing With the Times: The Need for Hotel Marketing and Revenue Management to Converge.

Boahen, O., Quansah, E. K., & Sarpong, O. K. (2013). Assessing the Benefits of Yield Management in the Hospitality Industry in Kumasi Metropolis of Ghana. International Journal of Business and Social Research (IJBSR), 3(19), 17-25.

Donovan, A. W. (2005). Yield Management in the Airline Industry. Journal of Aviation/Aerospace Education & Research, 14(3), 11-19.

Kimes, S. E., Barrash, D. I., & Alexander, J. E. (1999). Developing a Restaurant Revenue-management Strategy. Cornell Hotel and Restaurant Administration Quarterly, 40(5), 18-29.

Verret, C. (2004). The Revenue Management.

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