McDonald’s restaurant was chosen for my observations. Data was collected three times a day: 9:00 a.m., 12:00 p.m. and 6:00 p.m. All observations were made during four days: 20.06.09 (Saturday), 21.06.09 (Sunday), 22.06.09 (Monday) and 23.06.09 (Tuesday). Number of persons was recorded in the first minute of the defined time for each cash desk.
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Write My Essay For MeThis data, collected in the fast food restaurant can help restaurant managers to supervise long queues. A long queue can discourage clients form buying food in a particular restaurant.
The process observed was a little bit inadequate. The length of the queue varied at each cash desk. An inefficiency of cashiers in rush hours was also observed. Cashiers did not try to make the process more efficient, but worked with the same pace as with lower number of customers. The maximum length of queues was 12. None of the potential customers, who came when the length of queues varied from 9 to 12, stayed in the restaurant. Statistical analysis can help with defining the queue length, which is critical for the restaurant. Without defining a critical queue length a particular restaurant can lose precious customers in two ways: 1) customers, who constantly purchase food; 2) customers, who quit using services of the restaurants due to continious restaurant overload. With the help of statistical methods all problems can be found together with a way to solve them.
The first step in data analysis is defining of the distribution type for this data sample:
| Queue length | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| Number of observations | 2 | 5 | 8 | 13 | 9 | 6 | 5 | 3 | 2 | 1 | 2 | 2 | 2 |
Tab. 1
The mean for this data sample is 4.47, so the distribution is a shifted normal distribution.
The data, collected after McDonald’s restaurant visits is represented in the Tab. 2.
| Cash desk | 20.06.2009 | 21.06.2009 | 22.06.2009 | 23.06.2009 | ||||||||
| 9:00 | 12:00 | 18:00 | 9:00 | 12:00 | 18:00 | 9:00 | 12:00 | 18:00 | 9:00 | 12:00 | 18:00 | |
| 1 | 3 | 4 | 5 | 4 | 5 | 5 | 6 | 10 | 1 | 7 | 9 | 2 |
| 2 | 3 | 3 | 5 | 2 | 4 | 6 | 7 | 5 | 2 | 3 | 11 | 1 |
| 3 | 2 | 4 | 6 | 2 | 3 | 7 | 3 | 8 | 2 | 3 | 10 | 2 |
| 4 | 1 | 3 | 4 | 2 | 4 | 3 | 5 | 8 | 1 | 3 | 12 | 1 |
| 5 | 3 | 4 | 3 | 3 | 4 | 4 | 6 | 12 | 0 | 6 | 11 | 0 |
With these data a decision on improvement of processes in the restaurants can be slightly changed. After performing z-test the next conclusion can be made: Sunday’s and Monday’s samples are more similar with the whole data sample, Saturday’s and Tuesday’ data sample differs more from the whole sample.
Thus, general methods of solving the problem of long queues can be found performing descriptive statistics and inferential statistics having such sample. To make a concrete decision, better sample shall be used. The best way is to collect data samples for each day of the week for several days. Having a better data sample, conclusions made based on the statistical analysis, will be of a higher quality.
References
Descriptive Statistics. Retrieved from http://www.physics.csbsju.edu/stats/descriptive2.html
Distribution Tables. Retrieved from http://www.statsoft.com/textbook/sttable.html#z
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