support@essaywritingexpert.orgBA Project Report – Part A (Individual)
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BA Project Report – Part A (Individual)
Due 7 Apr by 23:59
Points 35
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Available until 11 Apr at 23:59
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Assignment Overview
Part A is the Individual assignment component of the BA Project. This assignment is designed to avoid group members
not knowing the context of the BA Project while doing the group assignment and hence become a liability for the entire
group. This assignment focuses on the analysis of a case. As an organisation in an increasingly competitive
environment, the organisation faces many challenges internally and externally.
There are many opportunities for the organisation to grow and to be more competitive. Understanding of Data and
Business Analytics role in informing the management and to provide a basis for decision making activities is crucial as a
way to facilitate more strategic growth and competitiveness for the company.
Assignment/Case description
Optimising Donations for Global Impact – A Challenge for ReachOut
Worldwide
ReachOut Worldwide (ROW) is a leading international charity organisation headquartered in Denver, Colorado, with a secondary
headquarters in Melbourne, Australia. For over 15 years, it has championed the cause of Global Health Initiatives, working tirelessly
to improve health outcomes and access to healthcare for underserved communities around the world. With a growing global
presence and a commitment to maximising impact, ROW has recognised the critical need to leverage data analytics for informed
decision-making. This case explores the organisation’s current landscape, the challenges it faces in a competitive fundraising
environment, and the potential of a data-driven approach to address these challenges.
ReachOut Worldwide’s Current Operations
ROW operates through a network of regional offices across various countries. Traditionally, fundraising campaigns have been driven
by a combination of established channels like direct mail appeals, telemarketing, and community events. While these channels have
yielded success, the organisation seeks to move beyond a reactive approach to a proactive one, where data analysis guides
campaign strategies and resource allocation.
The Evolving Landscape of Global Philanthropy
The landscape of global philanthropy has undergone significant transformations in recent years. The rise of online giving platforms,
increased competition from other NGOs, and growing public scrutiny of fundraising practices all necessitate a data-centric approach
for charities seeking to optimise their impact. Furthermore, the current global economic uncertainties with rising inflation and
potential recessions are casting a shadow on donation volumes, making efficient resource allocation crucial.
Data as a Driver of Change
Submission Summary Assignment/Case Description & Tasks Marking Rubric Important Files
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Data-driven insights have the potential to significantly transform ROW fundraising operations. By segmenting donors and tailoring
communication strategies, the organisation can cultivate deeper relationships with individual donors, increasing the likelihood of
repeat donations in support of Global Health Initiatives. Evaluating campaign effectiveness allows for resource allocation based on
proven strategies, maximising impact with every dollar raised for Global Health Initiatives.
Engaging the Business Analytics & Visualisation (BA&V) Consultancy
To address this data challenge, ROW has engaged with your consultancy company in Australia. Your team possesses the expertise
and tools to analyse the vast donation data collected. Ultimately, the organisation anticipates valuable insights from your company to
enhance:
Donor Segmentations: Identify key donor segments based on demographics, donation history, preferred channels, and giving
capacity. This allows for targeted communication and campaign strategies tailored to specific donor groups interested in
supporting various Global Health Initiatives.
Campaign Effectiveness: Evaluate the success of existing campaigns across different geographic regions and channels. Data
will reveal which appeals resonate most with different donor segments, allowing ROW to tailor messaging for maximum impact
on specific Global Health Initiatives.
Donor Retention: Analyse donor behaviour patterns and identify factors contributing to donor churn. Develop strategies to
nurture relationships, encourage repeat donations, and cultivate long-term donors who are passionate about supporting Global
Health Initiatives.
Predictive Capability: Utilise advanced analytics to predict future donor behaviour and potential donation volumes. This allows
for proactive resource allocation and informed budgeting decisions, ensuring ROW can maximise its impact on Global Health
Initiatives even in uncertain economic times.
Marketing Channel Effectiveness: Analyse the effectiveness of different fundraising channels (online platforms, events, etc.) and
payment methods. This ensures that ROW can raise more funds to support critical Global Health Initiatives in the future.
HOWEVER, as part of its due diligence before awarding the consultancy contract to your company, ROW has provided a
representative sample of its historical donation data (2019-2023). ROW has requested that your company produce an A&V report.
By analysing this data and presenting actionable insights & foresights, your team has the opportunity to demonstrate its capabilities
and expertise in the not-for-profit sector. A compelling report that unlocks valuable insights from ROW’s data will position your
consultancy as the ideal partner to empower ROW’s mission and achieve greater impact in the years to come.
Business Analytics & Visualisation Consultancy Engagement
As part of our engagement with the (potential) client, our firm has been granted access to a sample dataset from the
client. This dataset constitutes the sole data provision at this juncture. It’s customary in data consultancy that prior
to formal selection, a prospective firm is expected to furnish a ‘sample’ analysis. This serves as a demonstrative
showcase of the firm’s analytical capability and ability to analyse the provided data.
Your line manager decided to ask you to produce a preliminary report to showcase the following:
1. Assessment of the quality of the data. If the dataset is of poor quality, you are required to clean the data and
provide assurance the post-cleaning, the data will be of good quality to produce a trustworthy insights;
2. Six key insights that would be highly valued by our client’s key decision-makers. These key insights must be
driven by the analysis of the dataset and supported by the appropriate data visualisations stemming from the
analysis of the data.
In your analysis of the case grounded by the A&V of the dataset, you need to consider some of the following key
issues, challenges, and opportunities:
The competitive landscape and the strategic positioning of the organisation in the competitive landscape of its
industry (appropriate to the context of the case study);
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industry (appropriate to the context of the case study);
The key challenges/barriers, opportunities and values for growth, further developments of products and services
through/associated with the use of the data;
The key challenges/barriers, opportunities, and further developments of strategy and management practices in
the attempt to effectively capitalise on data;
Potential of strategic alliances in data acquisition, management, and use of data.
Deliverables
1. A Report containing the data quality assessment, the insights supported by the A&V, the references/reference
list, and the appropriate/relevant appendices.
2. Tableau workbook package file (i.e., .twbx) containing the worksheets/dashboards for the Part A, and the
Tableau Prep Builder file.
Please Note:
1. You should not rewrite parts of the case study.
2. As part of a case study analysis, critical thinking, synthesis, analysis, and your
professional views are critical to the task. These need to be informed and supported by
the appropriate literature (i.e., in-text references).
3. A minimum of four scholarly references (i.e., journal papers, conference papers) is
required. It is important that you employ only resources which are accepted as being
scholarly and academically reliable (i.e., journal papers, conference papers). Wikipedia
or to the individual opinions expressed in some Blogs and Web articles are nice to read
and may contain valuable information, but these are not regarded as “scholarly
references”. The Swinburne University library database features many useful and high
quality references. If you have difficulty in using this database you will find the library
tutorials helpful
4. Marks on the scholarly aspect will not be allocated solely based on the number of
quality references, but rather, on how the references are used to support/enrich the
statements/analysis within the report
5. All references should be appropriately cited using the APA referencing style
6. It is expected that all work submitted would have been proof-read & edited to avoid
spelling & grammar oddities/mistakes. The resulting written work needs to be
presented in a professional manner and format: i.e., Pages need to be numbered,
evidence of attention to layout and structure needs to be demonstrated. The written
submission is to be formatted as a report, word-processed in 12 point font and 1.5 line
spacing. The word count does not include the executive summary, table of contents,
references and appendices.
7. Analysis of the data provided and its presentation would be a key element of this
assignment. Some of the data analysis outputs can be presented as an appendix (but
this needs to be referred to in the main body of the report). However, it is always best
to present the visualisation(s) immediately before or after the insight narratives to
provide a stronger and more relatable support to the insights.
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INF70008 BA Project Report – Part A (Individual)
Criteria Ratings Pts
5.25 pts
12.25 pts
Assessment
of Data
Quality
5.25 to >3.68 Pts
Excellent – Very Good
Critical elements of the dataset are
appropriately reviewed, most data
integrity issues and data anomalies
have been reviewed. Implications of
data quality issues is well articulated
with sensible suggestions provided
while acknowledging the challenges
and constraints.
3.68 to >2.63 Pts
Developing
Some critical aspects of
the issues related to the
dataset are addressed.
However, more work
needs to be done to
ensure dataset is of
acceptable quality to
produce an accurate
analysis
2.63 to >0 Pts
Needs Improvements
Limited or no demonstration of
a cogent review of the data
quality issue. Poor articulation
of sensible approach to
improving data quality in
relation to the given dataset.
Underlying issues/concerns of
plagiarism in the report.
Quality of
the Data
Visualization
12.25 to >9.8 Pts
Excellent
Overall the data
visualisations
were of
exceptional
quality. No
omissions or
further
clarifications
required. The well
designed data
visualisations
(with appropriate
metrics and data
visuals, i.e.,
appropriate preattentive
attributes,
segmentations,
groupings, use of
multiple viz types)
added additional
value to the data
and provide the
reader with an
effective overview
of the analysed
data.
9.8 to >8.58 Pts
Very Good
The data visuals
provided were
designed
appropriately with
the
user/viewer/reader
in mind. Only
minor omissions
and clarifications
required in
improving the data
visuals..
8.58 to >7.35 Pts
Good
The data visuals
met the
requirement very
well. But there
were some areas
that required
further revision,
also some of the
visuals were not
as effective as
needed to
accurately reflect
the data. Some of
the data was not
present
7.35 to >6.13 Pts
Developing
The data visuals
met the basic
requirements of
this assessment.
But there were
several instance
where
improvements
and additional
clarifications was
required. Also
several required
areas were either
missing or
incomplete
6.13 to >0 Pts
Need
Improvements
The data
visuals
presented were
either
incomplete or
missing too
many required
elements that
rendered the
majority of the
data ineffectual.
Underlying
issues/concerns
of plagiarism in
the report.
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Total points: 35
12.25 pts
5.25 pts
Quality of
Insights
12.25 to >8.58 Pts
Excellent
The analyses & insights are highly
relevant to the dataset and the
context of the tasks, closely
intertwined and supported by the
data analysis & viz, and presented
using language and expressions
that are clear and succinct.
Excellent level of analyses,
showcasing segmentations,
groupings, drill-down, and
aggregate level of details. The
insights & the overall report are
well written and clearly organised
ideas, characterised by elements
of a good writing style and mostly
free from grammar, punctuation,
usage, and spelling errors.
Excellent conclusion and/or
summary, and recommendations
clearly supported by the literature
and/or the data analysis
8.58 to >6.13 Pts
Good – Developing
The analyses & insights are reasonable and
are supported by data analysis & viz, but
further refinements are required to improve
the accuracy and the credibility of the
insights. Reasonable level of analyses, but
may require further use of segmentations,
groupings, drill-down, and aggregate level of
details to improve the depth of the analyses.
The insights & the overall report are
expressed using language that is
satisfactory, but better proofreading is
required. Several odd/confusing grammar,
sentence structure, verbose and
colloquialism which can/should be avoided.
Conclusion and/or summary and
recommendations are reasonable but require
further refinements and supports from the
literature and/or the data analysis Several
issues with clarity of expressions and/or
meaning in describing/explaining the key
concepts and/or insights.
6.13 to >0 Pts
Need
Improvements
Statement of
insights is/are
not relevant,
inaccurate,
and/or not
supported by
the data
analysis and
viz. The
statement of
insights lacks
clarity,
significant
issues with the
grammar and/or
spelling.
Underlying
issues/concerns
of plagiarism in
the report.
Research &
Scholarships
Academic
rigor and
references,
justifications,
literature
sources and
evidence of
wider
readings
5.25 to >4.2 Pts
Excellent
Consistently demonstrates
skilful use of high-quality,
credible, relevant literature
sources (of four or more
scholarly literature) to
support and develop
appropriate ideas.
Consistently demonstrates
appropriate APA
referencing style (as in-text
refs and in the reference
list)
4.2 to >3.68 Pts
Very Good
Demonstrates skillful use
of high-quality, credible,
relevant literature sources
(of four or more scholarly
literature) to support
appropriate ideas.
Demonstrates appropriate
APA referencing style (as
in-text refs and in the
reference list) subject to
minor amendments.
3.68 to >2.63 Pts
Good –
Developing
Limited reference
list (i.e., three – or
less – scholarly
literature) but using
the correct APA
referencing Style.
Moderately
incomplete,
inaccurate, or
improper use of intext referencing
(where required).
2.63 to >0 Pts
Need
Improvements
No reference list
using the correct
APA referencing
style. Poor or nonexistent in-text
referencing (where
required).
Underlying
issues/concerns of
plagiarism is/are
demonstrated in
the response.