Every Hotel contains Front Office which acts as a public face, and Its primary functions are to welcome hotel customers and checking in guests. It is the hub of the whole hotel operations. All type of transactions is performed in this department. A staff of front office is main contacting source for the public. Duties of staff members involve registering a new guest, handle incoming calls, provide information, handle check-out when guests exits, handle reservations, dispense keys, handle outgoing emails, take messages for paying guests and list the complaints.
One of the essential tasks of management is to check the outcomes of the operations performed by the front office. Efficient managers check the results of department operations on a yearly, quarterly, monthly and daily basis. Front office’s success is measured in the form of occupancy ratios such as revenue per available room, success in leasing the hotel’s guestrooms, the average rate per person, occupancy percentage, average daily rate, sleeper rate and different occupancy statistics. Investors use occupancy percentage to calculate the possible gross income, which is the total amount of sales a hotel acquire at the current level of occupancy, anticipated yield and average daily rate (Bardi, 2003). By analysing average room rates and occupancy ratios several hotels in India such as Accor, Hilton, Inter Continental Hotel Group, and Marriott etc. have announced substantial investment plans due to improved results of travel (Asad Mohsin, 2010).
The DSS models can be implemented by new and uprising field of Revenue management (Revgen, 2014 ). The RM’s main goal is to maximise the average profit per room based on the expectation of the demand and by calculating the hight value rated customers who are willing to pay for a room. Another goal is to reduce the seasonality of request, the occupancy, by estimating the applications that are transferring the spare of the peak in other intervals of time, the rate for the category of each client, and these components can be modelled dynamically (Rus, 2009).
Hotels use a multidimensional approach to evaluate their performances, which includes three dimensions: the efficiency, effectivity, and adaptability. According to the model the effectivity is calculated by average occupancy and daily rate per room (Flavia Dana Oltenia, 2014). The average rate of room for each customer is calculated by dividing revenue (profit) by the total number of rooms sold (Kyoo Yup Chunga, 2004). The score of DEA at different steps can also show the reason for hotel’s productivity. Specifically, the hotels which become efficient from step one to step two can effectively manage and enhance their ARR, non-room revenue (minor operations and profit from the telephone)as well as room-nights occupancy (Marianna Sigala, 2005)
While having information related to guests patterns and hotel occupancy, the hotel’s beverage and food manager can schedule better operations (Sigala, 2003). Market leaders implemented and practised the business rules which determined the success of their business. The hotel named AIMS estimated that all of its hotels are profitable, successful, and raised average occupancy rates (Judy A. Siguaw, 1999). After the collection of data from reservation process, room forecast or forecasting (giving room for sale for a specific period) is a natural next step (Chamelian, 2011). Room forecast is used to get the preview of the income statement. It allows the manager to calculate the income of project and expenses related to it for a specified period. The front office manager estimated total room occupancy to be 100 rooms with an average rate of room $75 for a week, can give a profit of $52,500 (100 x $75 x 7) from room sales. The investor will manipulate the average rate of room to increase it if the expected income is not up to his expectations. for example, from $75 to $80 or from $90 to $95 (Bardi, 2003).
Every hotel should understand the requirements of its customers and the service they deliver. Moreover, they should realise how customer judges the service and how important it is to meet the expectations of guests. A balance must be maintained by front office manager between work procedures and guest service to maintain efficiency.
References
Asad Mohsin, T. L., 2010. Customer perceptions of service quality in luxury hotels in New Delhi, India: an exploratory study. International Journal of Contemporary Hospitality Management, 22(2), pp. 160-173.
Bardi, J. A., 2003. Hotel Front Office Management. 3rd ed. Hoboken, NJ: John Wiley and Sons.
Chamelian, S., 2011. Effective Room Forecasting is Key to the Hotel’s Future Performance. [Online]
Available at: https://ehotelier.com/insights/2011/03/01/effective-room-forecasting-is-key-to-the-hotels-future-performance/
[Accessed 3 April 2018].
Flavia Dana Oltenia, M. R., 2014. Relation Between Information Technology and Performance: an Empirical Study Concerning the Hotel Industry in Mures County. Procedia Economics and Finance, Volume 15, pp. 1535-1542.
Judy A. Siguaw, C. A. E., 1999. Best practices in hotel operations. Cornell Hotel and Restaurant Quarterly, 40(6), pp. 42-53.
Kyoo Yup Chunga, S. Y. O. S. S. K. S. Y. H., 2004. Three representative market segmentation methodologies for hotel guest room customers. Tourism Management, Volume 25, pp. 429-441.
Marianna Sigala, P. J. A. L. D. A., 2005. Productivity in Hotels: A Stepwise Data Envelopment Analysis of Hotels’ Rooms Division Processes. The Service Industries Journal, 25(1), pp. 61-81.
Revgen, K., 2014 . Hotel Revenue Management & Hotel Operations – Working Together. [Online]
Available at: https://www.kriyarevgen.com/hotel-revenue-management-working-with-hotel-operations/
[Accessed 3 ApriL 2018].
Rus, R. V., 2009. The Use Of Information Systems In Hotel Market Of Cluj-Napoca. Studia Universitatis Babes-Bolyai Chemie, Volume 3, pp. 51-58.
Sigala, M., 2003. The information and communication technologies productivity impact on the UK hotel sector. International Journal of Operations & Production Management, 23(10), pp. 1224-1245.
