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INFS5720 Descriptive Analytics for Sustainability

创建日期：2024-05-30 16:09:55

所属分类：管理Management

标签： INFS5720

Descriptive Analytics for Sustainability

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INFS5720 Individual Assessment: Descriptive Analytics for Sustainability

Individual Assessment Instructions
1. An Overview
The objective of this assessment is to test your application of the business analytics
lifecycle model, as shown in Figure 1, by using visualization techniques on a real-world
data set from the company GPT. The data set from GPT documents its sustainability
data at various property assets that the company manages. Please read the following
sections of this instruction document and develop a business report based on the tasks
specified. Please refer to Appendix B for the marking rubric of this assessment.
Figure 1. Business analytics lifecycle model
2. Key Dates
Task Deadline
Submitting an individual report
Naming convention “StudentID-StudentName-
CourseID”
3:00pm Friday 23 June
(Week 4)
3. Case Description
GPT is a leading property group in Australia and manages a
portfolio of properties including offices, logistics, and retail assets. The company aims
to “provide high quality real estate spaces that enable people to excel, and customers
INFS5720 Individual Assessment: Descriptive Analytics for Sustainability
3
and communities to prosper in a sustainable way”1. GPT ranked first among 800 real
estate companies listed in the S&P Global 2022 Annual Corporate Sustainability
Assessment. Sustainability is one of the top strategic priorities at GPT. Over the years,
the company has made significant achievements in attaining sustainability goals and
developing sustainability innovations, which are manifest in various aspects including
energy consumption, carbon emission, water consumption, and waste management.
Energy consumption:
GPT commits to reducing its energy consumption and increasing the use of renewable
energy. For example, the company developed a smart energy plan to prioritize
renewable energy (e.g., on-site solar energy) and innovative technologies (e.g., smart
meters) for monitoring energy usage. The energy reduction commitments have directly
contributed to the company’s carbon neutrality.
Carbon emission:
GPT is the first organization that attain carbon-neutral certification issued by Climate
Active across Scope 1, 2, and 3 emissions (for a definition of each emission type,
please refer to https://www.sustaim.earth/post/scope-1-2-and-3-emissions). The
company has retained the highest GRESB (Global Real Estate Sustainability
Benchmark) rating of 5 Stars. The company’s decarbonization has greatly benefited
from the use of renewable energy (e.g., solar, battery storage).
Water consumption:
GPT also has deliberately reduced its water consumption and strategically managed
stormwater. The company has achieved 62% improvement in its water intensity (i.e.,
net water usage per square metre of the lettable area of managed space) since 2005.
GPT proposes a “clean up/slow down” approach to ensure the quality of the water that
flows into the environment. Specifically, “clean up” includes activities such as
minimizing potential pollutants that could enter into stormwater. “Slow down” includes
activities such as reducing the speed of stormwater leaving a building so that it
reduces potential damage to the local environment. Based on its experiences in
1 https://gpt.com.au/sites/default/files/inline-
files/GPT%202022%20Climate%20Disclosure%20Statement_10.pdf
INFS5720 Individual Assessment: Descriptive Analytics for Sustainability
4
managing energy consumption, the company is moving towards achieving water
neutrality.
Waste management:
GPT proposes a close-loop waste management approach with the aim of maximizing
A-grade recycling and minimizing materials that end up in the landfill. The company
classifies waste into four categories: A-, B-, C- grade, and landfill. A-grade recycling
(also refer as close-loop) is about recovering materials without subsequent hazards to
the environment. For example, if cardboard is separated and processed properly, it
can be recycled into new cardboard. B-grade recycling is about downcycling original
materials to less valued materials, with a limited number of recovery cycles. C-grade
recycling is about waste materials that can be used for only one additional application.
Over time, GPT has Over 7,000 tonnes of materials being recovered based on close-
loop principles. The company also has achieved 3.3 NAMBERS (National Australian
Built Environment Rating System) waste rating for its office portfolio.
4. Tasks
Assuming you are a business analyst at GPT. You have been provided with a data
set: GPT data-individual assessment-INFS5720 (see data set uploaded to Moodle:
Assessments). Each student needs to upload this data set to SAS Viya platform by
following the instruction file and video provided on Moodle. Using this data set and
SAS Viya platform, you should use data visualization analytics to help the board of
directors understand the sustainability performance of GPT, and its financial
implications (e.g., cost reduction). Based on your visualization analysis, you also need
to identify the opportunities for GPT to improve its sustainability activities in the future.
You shall perform the following tasks:
• Identify specific sustainability issues (e.g., energy consumption, water
consumption, etc) that you aim to gain insights;
• Select and justify appropriate variables to analyze the performance of a
sustainability issue you identified;
• Apply visualization techniques (e.g., bar chart, histogram, line chart, etc) to
describe the sustainability performance;
INFS5720 Individual Assessment: Descriptive Analytics for Sustainability
5
• Recommend actionable insights for GPT to improve their sustainability
performance in the future.
Some generative questions for you to consider:
• What is GPT’s sustainability performance such as energy consumption, water
consumption, waste management, or carbon emission?
• What are the changes in GPT’s sustainability performance over time?
• What are the changes in GPT’s sustainability performance across geographical
regions?
• What are the factors (e.g., renewable, non-renewable energies) that have
contributed to GPT’s decarbonization?
• Are there associations between GPT’s sustainability performance and its
financial performance? If so, how would you explain the associations you
discovered?
• Are there changes in GPT’s sustainability performance before and after
COVID-19? If so, how would you explain the changes?
5. Description of Data Attributes
Attribute Label Meaning
Location Name Location of a GPT asset
Region Geographical region (e.g., Melbourne, Sydney)
Year Calendar year when sustainability data is
collected
Total Portable Water Total consumption of potable water
Total Non-portable
Water
Total consumption of non-portable water
Total Non-Renewable
Energy
Total consumption of non-renewable energy
Total Renewable
Energy
Total consumption of renewable energy
Gas Avoided Cost Financial cost avoided due to the reduction of
gas consumption compared to an estimated
baseline
Electricity Avoided Cost Financial cost avoided due to the reduction of
electricity consumption compared to an
estimated baseline
Energy Avoided Cost The sum of gas avoided cost and electricity
avoided cost
INFS5720 Individual Assessment: Descriptive Analytics for Sustainability
6
Total Scope 1
Emissions
Total emission in scope 1 – refer to the
footnote for explanations of scope 1, 2, and 3
emissions2
Total Scope 2
Emissions
Total emission in scope 2 – refer to the
footnote for explanations of scope 1, 2, and 3
emissions3
Total Offsets Carbon emissions (in tonnes) that have been
offset
Emission Avoided Carbon emission avoided (in tonnes) in scope
1 and scope 2 compared to an estimated
baseline
Landfill Weight (in tonnes) of material categorized as
landfill
A Grade Weight (in tonnes) of material categorized as
landfill A grade – refer to Appendix A for a
classification of recovery outcomes at GPT
B Grade Weight (in tonnes) of material categorized as
landfill B grade – refer to Appendix A for a
classification of recovery outcomes at GPT
C Grade Weight (in tonnes) of material categorized as
landfill C grade – refer to Appendix A for a
classification of recovery outcomes at GPT
Total Material Recycled Weight (in tonnes) of material recycled
NLA Net lettable area

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