Discuss about the case study Revenue Management for Mixture of Science.
Revenue management is a mixture of science and art to enhance the revenue obtained through various conditions. Revenue management is a tool used in management whose primary aim is enhancement of sales revenues through manipulation of the prices at which availability of fixed products such as airline seats or hotel rooms are made for sale in respect to the forecasted and current demand (Edwards 94-95, 2012). Consumer are nowadays very noticeable about the fact that whatever price they will have to pay for a hotel rooms or airline services it varies greatly based upon the point of how they make their decision of purchase and the availability of hotel rooms and airline e seats. This become different in the manner that customers understand the cost of these services/products has been comparatively new but accepted worldwide. Along with the development of the revenue management, usage of various analytical procedures for predicting customer demand and enhancing the inventory and to enhance revenue through price availability became much more technical and disciplined. To understand the perception of the customers and product price alignments properly, availability and placement with each and every customer segment is the main essence of this disciplines.
The catalyst for revenue management is the deregulation in the field of airline industry. Often the terms yield and revenue management gets confused, yet there is a major difference between both the disciplines. Prediction of the consumer behavior through forecasting demand and optimizing prices for several different types of products and segmenting markets whereas yield management refers that through inventory control revenues must be maximized. Hence a tactical application within the expanding field of revenue management is the yield management (Talluri and Van Ryzin, 2004). To cover fixed operating expenses by filling least number of seats was the reason revenue management was born. Once the expenses were met, the remaining capacity can be sold at higher prices to enhance revenue along with profit.
The benefits of using the revenue management were understood by the hotel industry by witnessing the benefits the airlines industry received and due to that reason they also adopted the strategy but initially the technique’s growth was held by. The reason behind this is the shortage of appropriate availability of the technology to manage date and the lack of meaningful in formations regarding the guests. The final challenge that the hotel industry face how to administer to manage the length of stay a feature which was not faced by the airlines industry (Vaeztehrani, Modarres and Aref 97-119, 2015).
Occupancy
A hotels occupancy rate is among the most important signs to measure success. It’s a KPI Calculation of a hotel which portrays the percentage of rooms rented for a certain period of time. To recognize the average daily rates, forecast and apply revenue management it is important for hotels to keep a track of their occupancy rates. The occupancy rate of a hotel is evaluated by the division of the total number of occupied rooms with the total number of vacant rooms of that particular hotel (Soon Kim 25-47, 2010). For example, if a hotel consists of 200 rooms and 150 rooms of the hotel are occupied and the remaining 50 are vacant, then the occupancy rate of the hotel will be = (Total number of rooms occupied / Number of rooms total of the hotel) multiplied by 100 = (150 / 200) * 100 = 75% of occupancy.
To increase occupancy rates of the hotel it has to use some strategies by using the length of stay procedure. For example, firstly when high demand period is anticipated the hotel must apply a rule of maximum length of stay which means only giving rooms to customers who will stay for longer periods instead of shorter periods. Secondly when rooms can given on high rates at that time also the above strategy can be applied an lastly, when there is a huge demand for rooms in the hotel, the hotel should apply the closed to arrival strategy which states giving rooms to those guest who were staying through from previous nights instead of them who arrived on the day in question. Hence this strategies can enhance the occupancy rate of any hotel (Agarwal 9-17, 2002).
Average Daily Rate or ADR is a statistic used mainly in the hospitality sector which states or indicates average room rent per day. It is a KPI (Key Performance Indicator) for calculating the average price or rate for each and every room that is sold for a particular day. Other KPIs except ADR are occupancy rates which we have described earlier and Rev PAR which will be described next (“Modelling And Prediction Of A Destination’S Monthly Average Daily Rate And Occupancy Rate Based On Hotel Room Prices Offered Online”, 2015). All of these KPIs are used for measuring the performance of operating of a particular lodging unit which can be either a hotel or a motel. It is one of the most common financial indicators for measuring whether the performance of a particular hotel is successful against other hotels which have the similarity in the characteristics such as clientele, location, size, etc. Against the historical performance of a hotel ADR can be calculated. Calculation of ADR is very simple. It can be evaluated by division of the room revenue by the number of rooms sold or rented. For example = Room Revenue/Rooms Sold (Jeffrey 509-522, 1985).
Complimentary rooms and house rooms are not included in the denominators. Rooms that are occupied by the hotel employees or management members are known as ‘House Use’ are not included as they cannot be rented or sold hence they cannot generate income. Whereas complimentary rooms do not possess a concrete value hence for the calculation of sale hence they are also excluded.
Revenue per available room also known as (RevPAR) in short, is a statistic used for measuring financial performance in the industry of hospitality. It is a statistic which measures both the room occupancy and rates is among the most valuable measuring device of health within the hotel operators. It is calculated by multiplication of ADR (Average Daily Rate of rooms) by its rate of occupancy. It can also be calculated by division of total room revenue of a hotel by the total number of available rooms while the calculation is on process (Kimes 138-144, 1999).
For example, the first method of calculation:
(Total Room Revenue in a particular period, Net of Discounts, Sales Tax, and Meals)
(Number of rooms available at that particular period)
Another procedure to evaluate RevPAR is:
Among all ratios used in the hotel industry RevPAR is the most important one. The rason behind it is that it calculates room rates as well as occupancy, a easy picture of how properly and effectively a company can fill its rooms is provided by this ratio and how much the company can charge is also portrayed. On the basis of per room RevPAR is calculated due to which one organization might accquire higher RevPAR than the other one yet revenues can be low if the other organization possess more rooms. This quality of RevPAR also makes it not helpful for a person who might try to assess two hotels or hospitality properties. Moreover growth in RevPAR never means that there is a increase in the hotel’s profit. The reason behind it is that it does not any information on profits or use any measures of profitability. Hence solely focusing on RevPAR, might lead to decline in revenue as well as profitability (Fabiola 315-323, 2007). Many managers of different hotels are turning completely towards the ADR (Average Daily Rate) as their measurement for performance. The reason behind it is positioning of price is found as one primary drivers of a hotel occupancy. Hence, if rooms of a property is accurately priced, there must be a rise in its occupancy and there should also be an increase in its RevPAR.
According to the STR report the 3 key findings are :
Porter’s Five Forces analysis is done on measuring the following five primary areas:
1. The power of buyers
2. The threat of entry
3. The power of suppliers
4. Competitive rivalry (advantage), and
5. The threat of substitutes.
Forecast Demand
The starting stage is to gauge vitality for your bound thing. Any person who is in this business for at whatever time period have absolutely seen there’s a subject with reference to when vitality for rooms blows hot and cool. We undeniably understand that booking an over the top number of one-night keeps concentrated understood night like a Saturday assembles we are obliged to release more customers who need to book distinctive night stays taking everything into account that hot Saturday and a less-pervasive “shoulder” night (a night interfacing an ordinarily fathomed night). The trap is to assess early what number of rooms we have to keep down for those more beneficial, multi-night customers. While we can make some sensible suspicions in the setting of a day of the week, time of year, even current money related conditions, we can never be 100% certain that there will be a willingness for X number of rooms on either specific date (Emeksiz, Gursoy and Icoz 536-551, 2006).
Driving revenue by using different rates:
Rise your costing when there’s a huge demand, and offer useful discounts to lure deal petitioners when demand is not high.
You can do this according to:
Procedures such as sell-up and cross-selling every customer are another ways to drive incremental revenue. It’s a win-win situation as long as the customers are offered relevant extras: you’re improving their experience residing with you, and even making it valueable your while.
Some ideas:
Yield connection is the umbrella term for a procedure of structures that pull in most remote point obliged alliance business tries to see flawless pay from operations. Inside considered yield association is for giving the correct sponsorship of the exact client on accurate time at the exact cost. That idea wires careful essentialness of connection, client, time, and cost. The association can be depicted by estimations of the connection, how and when it is passed on, and how, when, and whether it is saved. Timing joins both the sorting out of the connection transport and the arranging of when the client makes known the stinging for the alliance, whether by reservation or by strolling around the business. Cost can be set by the timing of the association, the building of the reservation, the kind of connection, or as appeared by a different rule that has every one of the stories of being sensible. At long last, the client can be portrayed by qualities identifying with the alliance, the sorting out, and the cost. The perfect consequence of a compensation connection structure is to match clients’ chance and alliance credits to their ability to pay-guaranteeing that the client gets the required relationship at the hurt for the time at a commendable cost, while the affiliation gets the most astounding pay conceivable given the client and business qualities(Bayraktaroglu and Kutanis 149-154, 2003). The fundamental levels of yield alliance can be abridged as four Cs: to be specific, date-book, clock, cut off, and cost. They are bound together by a fifth C: the client. The critical levels of yield connection are set up to sorting out alliance timing and surveying to clients’ energy to pay for the relationship in a relationship with its masterminding. In the setting of clients’ breathing room levels and qualities, the association can move the vitality of those clients who are in light of current circumstances regard unsteady yet time wanton to off-crest times. Moving that interest clears prime times for clients who are all around time delicate yet brought wanton.
Stakeholders of a hotel:
Firstly the General Manager is the important stakeholder of the hotel with whom communication of yield management strategy must be done. He should be given responsibility for enhancing the strategy of ‘Right Hotel Room Pricing; which stated that the rooms should be priced according to the different situations the hotel is facing or might face which can be anticipated such as anticipation of huge demand of room at a particular period or on any occasions. Secondly the Food and Beverage Department is also an important stakeholder of the hotel (Caneen and Gu 109-110, 1998). This department must realize the strategy of yield management as this department is associated with supply of food and beverages to the customers they must also follow the strategy of Up Selling and Cross-Selling. Lastly the Assistant manager is also the main pillar of the company hence he should be communicated about the Forecast demand strategy of yield management for the betterment of the hotel (Verginis and Stephen Taylor 358-376, 2004).
Techniques such as revenue management can be used by hotels for evaluating the total revenue potential from its customers through revenues from :-
References
Agarwal, V. “An Analysis Of Smith Travel Research Occupancy Estimates: A Case Study Of Virginia Beach Hotels”. The Cornell Hotel and Restaurant Administration Quarterly 43.2 (2002): 9-17. Web.
Asad, Mohiuddin. “Porter Five Forces Vs Resource Based View – A Comparison”. SSRN Electronic Journal n. pag. Web.
Bayraktaroglu, Serkan and Rana Ozen Kutanis. “Transforming Hotels Into Learning Organisations: A New Strategy For Going Global”. Tourism Management 24.2 (2003): 149-154. Web.
Caneen, Jeff and Zheng Gu. “Yield Management And Its Practical Application In Hotels”. The Journal of Hospitality Financial Management 6.1 (1998): 109-110. Web.
Edwards, Sarah. “Revenue Management: Maximising Revenue In Hospitality Operations”. Journal of Revenue and Pricing Management 12.1 (2012): 94-95. Web.
Emeksiz, Murat, Dogan Gursoy, and Orhan Icoz. “A Yield Management Model For Five-Star Hotels: Computerized And Non-Computerized Implementation”. International Journal of Hospitality Management 25.4 (2006): 536-551. Web.
Fabiola, Sfodera. “Examining The Determinants Of Room Rates For Hotels In Capital Cities: The Oslo Experience”. Journal of Revenue and Pricing Management 5.4 (2007): 315-323. Web.
Jeffrey, D. “Trends And Fluctuations In Visitor Flows To Yorkshire And Humberside Hotels: An Analysis Of Daily Bed Occupancy Rates, 1982–1984”. Regional Studies 19.6 (1985): 509-522. Web.
Kimes, S. E. and S. Singh. “Spa Revenue Management”. Cornell Hospitality Quarterly 50.1 (2008): 82-95. Web.
Kimes, S. E. “The Relationship Between Product Quality And Revenue Per Available Room At Holiday Inn”. Journal of Service Research 2.2 (1999): 138-144. Web.
“Modelling And Prediction Of A Destination’S Monthly Average Daily Rate And Occupancy Rate Based On Hotel Room Prices Offered Online”. Tourism Economics (2015): n. pag. Web.
Rhee, Hosung Timothy and Sung-Byung Yang. “Does Hotel Attribute Importance Differ By Hotel? Focusing On Hotel Star-Classifications And Customers’ Overall Ratings”. Computers in Human Behavior 50 (2015): 576-587. Web.
Soon Kim, Hong. “Hotel Property Characteristics And Occupancy Rate”. International Journal of Tourism Sciences 10.3 (2010): 25-47. Web.
Talluri, Kalyan T and Garrett Van Ryzin. The Theory And Practice Of Revenue Management. Boston, Mass.: Kluwer Academic Publishers, 2004. Print.
Vaeztehrani, Amirhossein, Mohammad Modarres, and Samin Aref. “Developing An Integrated Revenue Management And Customer Relationship Management Approach In The Hotel Industry”. Journal of Revenue and Pricing Management 14.2 (2015): 97-119. Web.
Verginis, Constantinos S. and J. Stephen Taylor. “Stakeholders’ Perceptions Of The DCF Method In Hotel Valuations”. Property Management 22.5 (2004): 358-376. Web.
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