Improving Restaurant Service Time: Gourmet Delight Case Study

Running head: IMPROVING RESTAURANT SERVICE TIME: GOURMET DELIGHT 1
Improving Restaurant Service Time: Gourmet Delight Paper
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IMPROVING RESTAURANT SERVICE TIME: GOURMET DELIGHT
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Improving Restaurant Service Time: Gourmet Delight
Introduction
The ability of a restaurant to secure and sustain customer royalty is dependent on their
level of service delivery. Service delivery is influenced by several factors such as quality of food
and drinks offered, and service time. In most instances, poor service time will create a negative
perception of the restaurant in the minds of customers (McClellan, Jimenez, & Koutitas, 2017).
Therefore, there is need for management to ensure that service time is not too long such that
clients have to wait for their orders for more than 30 minutes. Most restaurant enforce service
time policies that are guarantee the client delivery of food items within a given period; failure to
which, the client is not expected to pay for his/her meal. By putting in place such policies,
management tries to ensure time optimization and enforce staff competence. If a restaurant is not
operating at maximum efficiency, the service time will be critically handicapped meaning meals
will take considerably long before they are presented on clients' tables.
For a restaurant like Gourmet Delight, the manager needs to run statistical assessments
to discern whether or not the service time is significantly long. Through the use of measures of
central tendency and variability, the restaurant manager can be able to tell whether or not service
time has increased over the last six month beyond 20 minutes. If the service time has indeed
increased, then a plan of action needs to be formulated to ensure that time management by staff
is bettered. (Bajpai, 2009) Such a plan could entail the provision of staff training programs and a
reward & punishment system. The training program will be aimed at improving the competence
of the restaurant staff; while, the reward and punishment system will provide benefits to staff

IMPROVING RESTAURANT SERVICE TIME: GOURMET DELIGHT
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members who deliver quality services within a timely fashion, and place penalties on relaxed
staff performance.
Statistical Assessment
Summary Statistics
Summary statistics are a paradigm of descriptive statistics that encompass measures of
central tendency and variability; as well as minimum and maximum values. Measures of central
tendency are used to assess the central point of a given distribution; examples of these measures
are mean, mode, and median. On the other hand, Measures of dispersion or variability are
employed to assess the spread of data in a given distribution. The most well known measures of
dispersion are variance, standard deviation, range, and inter-quartile range (Debra, 2011). Using
the data retrieved from Gourmet Delight's records we can be able to assess for any change in
service delivery over the past six month using these measures. In this assessment will investigate
the aforementioned measures with regard to service time before and after training. The results
are presented as follows.
Summary
Statistics
Serving Times
prior to training
(minutes)
Serving Times
after Training
(minutes)
Central
Tendency
Mean 40.53 20.00
Mode 35 18
Median 39.5 19
Dispersion Variance 92.05 44.28
Standard 9.59 6.65

IMPROVING RESTAURANT SERVICE TIME: GOURMET DELIGHT
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Deviation
Range 40 24
Interquartile
Range
9.50 10.75
Maximum 65 34
Minimum 25 10
According to the results, the average time it took for a client to be served was around
40.53 minutes before the training and 20 minutes after the training. As such, the training
critically improved service delivery by cutting the serving time by more than half. The mode
gives use the most frequent service time at the restaurant. As such, before the training the most
frequent serving time was 35 minutes; but after the training, this time was reduced by almost half
to 18 minutes. The median specifies the central most value in a dataset given they are arranged in
terms of magnitude. In our cause the central most service time before the training was 39.5
minutes, and after the training this figure was mitigated to 19 minutes. Moving on to the
measures of dispersion, the variance of the data gives the spread of the data from the mean.
Therefore, the data from service before training was conducted is more spread out from the mean
given it has a variance of 92.05 minutes and that of service after training is only 44.28 minutes.
The standard deviation gives the spread of individual data points from the mean.
Therefore, a small standard deviation indicates the points are close to the mean of the data. From
the results above it is evident that data values collected after the training are closer to the mean
(6.65 minutes) compare to those collected before staff training was performed (9.59 minutes).
The maximum time it took to be served before the training was 65 minutes; which is