DATA-DRIVEN DECISION MAKING
Competencies:
3009.1.1: The Case for Quantitative Analysis –
The graduate uses decision-making methods
to develop strategies for organizational decision p
rocesses.
3009.1.2: Statistics as a Managerial Tool –
The graduate uses a variety of decision-analysis
tools to evaluate alternatives during the decision-
making processes.
3009.1.3: More Statistical Tools –
The graduate uses quantitative techniques and stat
istical
tools to identify the most appropriate decision alt
ernatives.
3009.1.4: Quality Metrics and Tools –
The graduate analyzes how work is accomplished and
applies quality metrics and tools to increase effic
iency, effectiveness, and quality.
3009.1.5: Real World Data-Driven Decisions –
The graduate analyzes data from business
intelligence and knowledge-management systems to ma
ke appropriate decisions.
3009.1.6: Improving Organization Performance –
The graduate uses appropriate data to
improve organizational performance.
Introduction:
In this task, you will identify a real-world busine
ss situation that would benefit from a data
analysis in order to find an actionable recommendat
ion. You should select an issue in your
workplace or program specialty area (i.e., IT manag
ement, HC management, or MBA). This
business situation and data will be used to complet
e task 2. Do not work on task 2 until you
have successfully passed task 1, indicating that th
e business situation and data analysis plan
have been approved.
Use the “Decision Tree Presentation” in the Web Lin
ks section to help you identify the
appropriate analysis technique.
Requirements:
Use the attached “Data Driven Decision Making Templ
ate” to complete the following prompts:
A. Describe a real-world business situation that c
ould be addressed by collecting and analyzing a
set of data.
Note: Your selected real-world business situation s
hould relate to an issue in your workplace
or program specialty area (i.e., IT management, HC
management, or MBA). Your data
analysis will be used to make an actionable busines
s recommendation.
1. Summarize
one
question or decision relevant to the real-world bu
siness situation that you
will answer by collecting and analyzing a set of da
ta.
2. Explain why the situation or question would ben
efit from a data analysis.
3. Identify data you will need to collect that is
relevant to the situation or question.
Note: A sample size of 30 or more is suggested to p
rovide a statistically reliable finding.
4. Describe the data gathering methodology you wil
l use to collect data.
5. Identify an appropriate data analysis technique
you will use to analyze this data (e.g.,
linear programming, crossover analysis, t-test, reg
ression).
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a. Explain why the data analysis technique you cho
se is an appropriate technique to
analyze the data collected.
Note: The “Decision Tree Presentation” in the Web L
inks section will help you determine the
appropriate analysis technique for your data and bu
siness situation.
B. When you use sources to support ideas and eleme
nts in a paper or project, provide
acknowledgement of source information for any conte
nt that is quoted, paraphrased or
summarized. Acknowledgement of source information i
ncludes in-text citation noting
specifically where in the submission the source is
used and a corresponding reference, which
includes:
• Author
• Date
• Title
• Location of information (e.g., publisher, journ
al, or website URL)
Note: The use of APA citation style is encouraged b
ut is not required for this task. Evaluators will
offer feedback on the acknowledgement of source inf
ormation but not with regard to conformity
with APA or other citation style. For tips on using
APA style, please refer to the APA Resources
web link found under General Information/APA Guidel
ines in the left-hand panel in Taskstream.
Note: No more than a combined total of 30% of a sub
mission can be directly quoted or closely
paraphrased from outside sources, even if cited cor
rectly.
Note: For definitions of terms commonly used in the
rubric, see the Rubric Terms web link
included in the Evaluation Procedures section.
File Attachments:
1.
Data Driven Decision Making Template link opens in
new window
Web Links:
1.
Decision Tree Presentation link opens in new window
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