Running head: BUSINESS DECISION MAKING
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Business Decision Making
Cherrie Blackman
QNT/275
May 22, 2017
Robert Schaller
BUSINESS DECISION MAKING
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Business Decision Making
Elite Technologies Company is one of the best companies globally, and it has a relatively
bigger market share, which is attributed to its ability to provide quality products and service to its
customers. The company deals with assembling and sale of electronics ranging from household
electronics to entertainment appliances. The company also has a subsidiary service branch that
deals with all the service problems from the company and any other services brought to them. The
existing combination could to forge a strong relationship with customers improving the companycustomer relationship. The company has been enjoying higher profits due to its suitability and
good business relations, unlike other companies who do not have a renowned service affiliated
company that can be able to improve its customer satisfaction.
Despite having better business deals, recent seasons have seen a slight decline in the sales
of some of its best-suited products. However, the organization remains adamant that the low season
will soon be over and it will achieve its set sales objectives. Therefore, the organization depends
on assumptions rather than engaging its customers into finding out what the problem might be.
The fact that the company is customer dependent, there is need to establish better strategies that
the organization can be able to know if there is anything wrong which should be achieved as well.
The company has been making abnormal profits, which have made it more adamant in addressing
the basic needs of some of its longstanding stakeholders who played a huge role in the rise of the
company by providing invaluable advice and support which have placed the organization at its
current level of success.
BUSINESS DECISION MAKING
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A research variable is an important factor that is put into consideration when developing a
research analysis. It is important to identify the research variables before commencing any data
collection because the whole research will ultimately depend on these variables to make a
conclusion about the situation of the company. In any given research, the variables may assume
different roles depending on how the study is developed. In this case scenario, one of the variables
will be sales, which will constitute the dependent variable (Male, 2015).
A dependent variable, in this case, will depend on other independent variables, which will
provide the organization with the mush needed information regarding the fluctuations in sales. The
independent variables are factors that are not influenced by other occurrences but are rather
reflective. The independent variable will provide the best picture to know if the company’s
assumption that the sales are lower because the season is low is held true. Therefore, in this respect,
some of the independent variables that can be considered include attitude, prices, low season and
any other that the organization may consider and are considered effective (Powell and Grossman,
2015).
In this case, the method selected for data collection should be able to capture the details
involving the research variables both independent and dependent. Data collection method will
involve various strategies that can be employed to obtain an unbiased outcome. In any statistical
research data collection, a lot of emphases is placed on the method undertaken to obtain data
mainly because biased data cannot provide the most effective result since it will be influenced by
other factors that are not considered in each research. In this case, the company has a large
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customer base, and the best response involving the subject matter can only be obtained from the
individuals who consume the company’s products (Powell and Grossman, 2015).
Since the total population is much greater, the company should effectively identify the best
sampling design that they will use to get the sample population, which they will be able to work
with. In this case, the best sampling design would simple random sampling. Simple random
sampling will be the best sampling technique that will ensure that the sample selection is not biased
in any way. This procedure ensures that the research assistants who will be undertaking the survey
randomly pick the selected samples or respondents. The total sample should be able to reflect
equally to the total population since the fishers formula will be best suited to get the best reflective
sample of the total population (Shields et.al, 2016).
After the establishment of the sample size, the research then will employ the use of a
questionnaire, which will be administered to the selected sample to provide an honest opinion
regarding the question involving the variables. The questionnaire is commonly referred because if
the questions are perfectly framed, the outcome will be very much a true representation of the total
population. The data collected in this case would include both qualitative and quantitative (Male,
2015).
However, it will significantly depend on how the questions in the study have been framed.
Incorporating both qualitative and quantitative detail will provide a much-detailed outcome.
Qualitative data will provide the descriptive part of the research where the respondents will be able
to provide information regarding how the situation is by use of more data that can be observed but
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not measured. Quantitative data, on the other hand, will provide important information regarding
the exact numbers, which can be measured and effectively analyzed (Shields et.al, 2016).
After the establishment of the sample size, the research then will employ the use of a
questionnaire, which will be administered to the selected sample to provide an honest opinion
regarding the question involving the variables. The questionnaire is commonly referred because if
the questions are perfectly framed, the outcome will be very much a true representation of the total
population. The data collected in this case would include both qualitative and quantitative (Male,
2015).
However, it will significantly depend on how the questions in the study have been framed.
Incorporating both qualitative and quantitative detail will provide a much-detailed outcome.
Qualitative data will provide the descriptive part of the research where the respondents will be able
to provide information regarding how the situation is by use of more data that can be observed but
not measured. Quantitative data, on the other hand, will provide important information regarding
the exact numbers, which can be measured and effectively analyzed (Shields et.al, 2016).
Ensuring reliability of data collected depends on some aspects that need to be monitored
closely to develop a better data that can be accurately analyzed and present the best solution that
can help the organization in making rightful decisions. Reliability of data means that the data
collected can be used to produce undisputed outcome while validity means that the data collected
is accurate and correct without any bias or influence from non-accounted for factors in research
(Male, 2015).
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One of the methods to ensure reliability and validity of research data are use of reliable
data sources. This means that the sample population chosen should be able to provide accurate
information without any influence to help the company make necessary changes. Another method
of ensuring that the data collected is reliable and valid is to ensure that the data capture methods
used in data collection are accurate and are highly recommended in a study. It is also important to
ensure that the respondents in the research know perfectly well, what they are supposed to do in
ensuring that they are trained or guided on how to answer the questions as presented to enhance
reliability and validity (Powell and Grossman, 2015).
To conduct a study that can form basis of policy formulation or change of strategy, it is
important to effectively outline the best possible research design that will be adopted for the
implementation of the whole research.
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References:
Hilemon, C. G., Nelson, T. E., Skeirik, R. D., Hayzen, A. J., & Horn, D. M. (2016). U.S. Patent
No. 20,160,048,110. Washington, DC: U.S. Patent and Trademark Office.ser
Powell, M., & Grossman, A. (2015). Quality indicators in pituitary surgery: a need for reliable and
valid assessments. What should be measured?. Clinical endocrinology.
Rosen, D. L., & Olshavsky, R. W. (2015). Interactive Data Collection: Implications for Laboratory
Research. In Proceedings of the 1984 Academy of Marketing Science (AMS) Annual
Conference (pp. 82-86). Springer International Publishing.
Shields, A. L., Shiffman, S., & Stone, A. (2016). Recall Bias: Understanding and Reducing Bias
in PRO Data Collection. EPro: Electronic Solutions for Patient-Reported Data, 5.
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