Business Analytical Report

Posted: August 26th, 2021

Business Analytical Report

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Business Analytical Report

The report is a summary of data collected in five London boutique hotels from a random sample of 40 guests staying in each of the hotels in July 2019. The summary examines the distribution of age, the amount spent by guests, and the number of nights that the guests spent in the restaurant. Various analytical tools are used, which include the measures of central tendency, correlation, and regression analysis to establish various customer characteristics across the five hotels.

Data and Results Presentation

Grouped Frequency Distribution

Figure 1 shows the analysis of the distribution of the age of guests that visited the five hotels during July 2019.

Figure 1: Grouped Frequency Distribution of the age of participants in the hotel

As shown in figure 1, participants 1 -5 contributed highly in the number of visits that were made in the hotel across all the three age categories at 70 visits. It closely followed by category 36 – 40, with about 68 visits. Category 31 – 35 scores the least.

Table 1: Summary Analysis of the Hotels

	Beaufort House	The Beaumont Hotel	Cheval Kingsbridge	The Goring	41 Hotel
Student name:
Variable : Age
Mode(s)/Modal class	2.00	4.00	4.00	1.00	3.00
Median	2.00	4.00	3.00	1.00	3.00
Mean	2.05	3.20	3.00	1.78	2.65
Shape of distribution	Kurtosis => -0.2 Skewness => 0.5	Kurtosis => -0.36 Skewness => -0.92	Kurtosis =>-0.91 Skewness =>-0.51	Kurtosis=>-0.10 Skewness=>1.01	Kurtosis=>-0.65 Skewness=>0.01
Range	3.00	3.00	3.00	3.00	3.00
Sample Variance	0.66	0.98	0.97	0.95	0.75
Sample standard deviation	0.81	0.99	0.99	0.97	0.86
Coefficient of variation (95.0%)	0.26	0.32	0.32	0.31	0.28
Variable: Amount spent
Mode(s)/Modal class	#N/A	1,323.43	889.88	867.05	#N/A
Median	488.77	1,320.43	722.15	867.05	954.95
Mean	516.67	1,208.56	709.92	962.02	854.79
Shape of distribution	Kurtosis => -0.66 Skewness => 0.28	Kurtosis=>1.26 Skewness=>-0.92	Kurtosis => -0.38 Skewness => 0.15	Kurtosis=>1.02 Skewness=>0.86	Kurtosis=>0.45 Skewness=>-0.71
Range	619.21	1,411.52	807.76	2,394.87	1,239.93
Sample Variance	25,129.97	87,818.09	40692.85	273,532.97	72,404.85
Sample standard deviation	158.52	296.34	201.72	523.00	269.08
Coefficient of variation	50.70	94.77	64.51	167.26	86.06
Quartiles
	Age	Amount Spent	Age	Amount Spent	Age	Amount Spent	Age	Amount Spent	Age	Amount Spent
Q1	1.75	406.66	2.25	973.35	2	570.22	1	552.82	2	662.208
Q3	2.25	642.45	4.00	1412.29	4	874.81	2	1296.59	3	1061.66
IQR	0.5	235.80	1.75	438.95	2	304.59	1	743.78	0.5	399.45
Outliers?	Yes	No	No	Yes	No	Yes	No	no	no	yes
Correlation and Régression
Correlation coefficient	0.75	0.62	0.71	0.87	0.56
r	0.75	0.62	0.71	0.87	0.56
a	124.50	520.38	244.53	317.73	439.18
b	45.33	63.97	54.43	142.38	63.69
R2	0.57	0.38	0.50	0.762	0.31

Analysis and Discussion

The section includes analysis and discussion on the results presented in the data and results section. The purpose is to compare, review and address issues regarding the analysis results on the age of hotel guests, the amount paid by hotel guests and the correlation and regression results between the number of nights guests spent in a hotel and the amount they spent.

Beaufort House

Analysis of age distribution among guests that visited each of the five hotels reveals a mean visit of two (2) guests in Beaufort House. The median distribution was two (2) guests within a range of 3.0 visits. The sample age variation from the assessment was 0.66. The distribution of the guests was positively skewed at 0.5. In terms of the amount each of these guests paid, the mean distribution was GDB 516.16 per visit, with a standard deviation of GDB 158.52 (Table 1). The coefficient of variation at a 95% level of confidence for the age of hotel guests was 26% and the amount guests spent in the hotel was GBP 50.70. Coefficient of variation measures the level of dispersion from the mean, hence the higher the coefficient, the higher the dispersion.

  Moreover, correlation and regression analysis, which was used to examine the impact of the number of nights the guests spent in Beaufort Hotel, revealed that at any time of the day, holding other factors constant, guests spent about GBP 124.54 per night. Besides, a unit increase in the number of nights spent in the hotel increases the amount spent at Beaufort House by 45.33 (Table 1). In terms of correlation, the number of nights a guest spent in the hotel is positively related to the amount spent by the guest per visit, with a correlational coefficient of 0.75.  Therefore, it implies that an increase in the number of nights spent in the hotel increases the amount of money guests spent.

The Beaumont Hotel

The case of Beaumont Hotel reveals almost a similar trend or distribution, as exhibited by Beaufort House. Analysis of age distribution among guests that visited each of the five hotels reveals a mean score of three (3) guests per visit. The median distribution was four (4) guests with a range of 3.0 visits. The sample variance for the age assessment was 0.98. The shape of the distribution of the guests was negatively skewed at -0.92. In terms of the amount each of these guests paid, the mean distribution was GDB 1208.56 per every visit with a standard deviation of GDB 296.34 (Table 1). The coefficient of variation at a 95% level of confidence for the age of hotel guests was 32% and the amount guests spent in the hotel was GBP 94.77 from the mean.

Regarding correlation and regression analysis, it was shown that at any time of the day, holding other factors constant, guests spent about GBP 520.38 per visit. Besides, a unit increase in the number of nights spent in the hotel increases the amount spent at The Beaumont Hotel by 63.98 (Table 1). In terms of correlation, the number of nights a guest spends in the hotel is positively related to the amount spent by the guest per visit, with a correlational coefficient of 0.61. 

Cheval Kingsbridge

             Analysis of the age distribution of hotel guests indicated that the mean visits of any age category were three (3) with a mode of four (4) visits and a standard deviation of 0.99 within a range of three (3) guests per every visit. The distribution for Cheval Kingsbridge is negatively skewed at -0.51. When analyzing the amount each guest spent, it was shown that guests incurred a mean of GBP 709.92 per night with a standard distribution of GBP 201.72 within a range of GBP 807.76 (Table 1). The assessment on the coefficient of variation at 95% confidence, the age of hotel guests reported a score of 31% while the amount spent by guests in the hotel varied by GBP 64.71 from the mean. Cheval Kingsbridge reported the highest prices compared to other hotels. Hence, the variation in the two variables is still favorable to sustain the hotel activities as it is below the mean. The correlation analysis of the impact that the number of visits has on the amount spent by guests in this hotel room indicated a positive correlation with a coefficient of 0.7094. In the same line, the results of the regression analysis indicated that at any time of the day, whenever there is a visit, the hotel earns GBP 244.56. Equally, an increase in the number of visits to the hotel increases the amount spend by guests by GBP 54.432 (Table 1). Thus, the number of nights spent at the hotel has a positive impact on the amount the hotel earns.

The Goring

An examination of the behavior in the age of guests that visited the hotel indicated that at least there were a mean of two (2) guests per visit with a mode of one (1). The distribution shape for the age of guests visiting this hotel was positively skewed at 1.01 (Table 1) with a standard deviation of 0.97 (Table 1). Equally, an assessment of the amount spent by guests in this hotel indicated a mean score of GBP 962.02 with a standard deviation of GBP 523.00. About the dispersion of age and amount hotel guests spent based on the coefficient of variation at a 95% level of confidence, it was 31% for the age and GBP 167.26. In this case, the variation is favorable, as it is below 50%. Similarly, correlation and regression analysis revealed a positive relationship between the number of nights and the amount spent by guests in the hotel. According to the regression model, the hotel at any time, holding other factors constant, earns GBP 317.74 per night. Any increase in the unit of the number of nights spent in the hotel by any guest increases the hotel earnings or the amount earned by GBP 142.384 (Table 1).

41 Hotel

Analysis of the data obtained about the age of the guests visiting this hotel revealed a mean score of 3 visits per night with a median score of three (3) visits within a range of three (3). Equally, the assessment of the mean amount spent by guests in the hotel was GBP 854.79 per visit with a mode of GBP 867.05. When examining the coefficient of variation at a 95% level of confidence, it was noted that the dispersion of the age of hotel guests from the mean is 0.28. While the dispersion of the amount the guests spent from the mean was GBP 86.06. The results indicate a favorable figure since the lower the dispersion, the higher the probability that the hotel is assured of frequent visits. Correlation analysis reported a positive relationship between the number of nights guests spent in the hotel and the amount each guest spent, with a coefficient of 0.55. Regression analysis exhibited that any increase in the number of nights that guests spend in 41 Hotel increases the amount that the hotel collect by GBP 63.93. Besides, without a change in other factors, the hotel is guaranteed GBP 439.18 per night the guests spend.

Recommendations

The business analytical aspects present in the above section are critical in understanding both the market and business situation of the hotel industry. However, performance analysis can be enhanced through the inclusion of some of the following metrics. First, the analysis should incorporate analysis of the average daily rates that examines the daily rates that guests paid for each room on a particular day(Guffey, & Almonte, 2009). Although the data and analysis included payment based on age, the number of nights and the amount paid per guests across each of the hotels, allowing average rates analysis enables the business to understand the general performance situation. Hence, the management is equipped with required metrics over which they can benchmark in projecting the expected returns of the facility.

Secondly, undertaking cross-sectional average occupancy rates is critical in understanding how hotels are occupied within a given period. In the hotel industry, annual fluctuations are frequent due to the seasonality nature of the business. Hence, getting information about how guests occupy hotels can help facilitatethe planning of the facility(Rummler & Brache, 2013). According to the data in the report, which looks at the number of nights that a guest spent in the hotel and its impacts on the amount that each guest spent, the accuracy of the regression model could have been enhanced by incorporating factors such as occupancy rates. In this way, the results would be reliable hence helpful in enhancing the decision-making process.

Lastly, to enhance the understanding of the hotel’s performance about its competitors in the industry, it is critical to include data about market penetration. Analysis, in this case, should focus on rates of penetration across the industry. In this way, the management can attain an in-depth understanding of their respective hotel (Hales, 2005). Therefore, they can devise strategies to maintain their penetration level or enhance their competitiveness in the industry.

References

Guffey, M. & Almonte, R. (2009). Essentials of business communication. Toronto: Nelson Education.

Hales, J. (2005). Accounting and financial analysis in the hospitality industry. Burlington, MA: Elsevier Butterworth-Heinemann.

Rummler, G. & Brache, A. (2013). Improving performance: how to manage the white space on the organization chart. San Francisco: Jossey-Bass.