Monitoring Front Office Performance

Every hotel contains a front office that acts as a public face, and its primary function is to welcome hotel customers and check-in guests. It is the hub of all hotel operations. All types of transactions are performed by this department. The staff of the front office is the main contact source for the public. The duties of staff members involve registering new guests, handling incoming calls, providing information, handling check-outs when guests exit, handling reservations, dispensing keys, handling outgoing emails, taking messages for paying guests and listing 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. The 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 acquires 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, InterContinental Hotel Group, Marriott, etc., have announced substantial investment plans due to improved travel results (Asad Mohsin, 2010).

The DSS models can be implemented by new and uprising fields 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 calculate the high-value rated customers who are willing to pay for a room. Another goal is to reduce the seasonality of request and 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: 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 the hotel’s productivity. Specifically, hotels that 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), and room-night occupancy (Marianna Sigala, 2005).

While having information related to guest 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 and successful and raised average occupancy rates (Judy A. Siguaw, 1999) after the collection of data from the reservation process, room forecast or forecasting (giving room for sale for a specific period) is a natural next step (Chamelian, 2011). A room forecast is used to preview the income statement. It allows the manager to calculate the project’s income and expenses for a specified period. The front office manager estimated total room occupancy to be 100 rooms with an average rate of room $75 per week, which 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 understand how customers judge the service and how important it is to meet the expectations of guests. The front office manager must maintain a balance 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., 201. 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.