COMM1110 Evidence-Based Problem Solving
Assessment 3: Case project part 1
Guideline and Marking Rubric

Due date: Week 5, 11.59 am (Midday), Friday 11 October
________________________________________________________________
Project Overview
Assume in September 2024, you are an intern consultant at Deloitte, a leading consulting and
financial firm in Australia.
Your client, Greenleaf Grocery, a mainly Sydney-based retail grocery chain facing a pressing
issue: a notable increase in food waste, especially in the fresh food (fresh dairy products and
Bakery) section. GreenLeaf Grocery is eager to delve into the root causes of this waste surge and
seeks actionable recommendations to tackle the problem head-on.
GreenLeaf Grocery offers a range of fresh dairy products including milk, yogurt, cream, cheese,
and more. Their bakery section features freshly handmade bread, croissants, muffins, cakes, and
other delights. Due to their handmade nature, these products have a relatively short expiry date.
Unfortunately, the rising trend in food waste poses a significant challenge, contributing to both
financial losses and environmental concerns.

Objective for “Assessment 3 - Case Project Part 1”
Scenario: As an intern Business consultant at Deloitte in September 2024, your primary task is
to prepare an initial business analysis report for an internal meeting on the rise in food waste at
GreenLeaf Grocery’s fresh food section. You are preparing some analysis for a Deloitte internal
meeting before presenting results to GreenLeaf Grocery.
• Analytical: Identify potential factors and drivers contributing to the increase in food waste.
• Statistical: Analyse GreenLeaf Grocery’s data to identify trends and patterns in food waste.
• Ethics: Assess the ethical dilemmas associated with food waste.

This type of report is typical for a manager in the workplace, making it an excellent practice for
your future career. Please note that this Assessment 3 report will set the foundation for your
final report, Assessment 4 - Case Project Part 2, which is due in Week 11.
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Academic Integrity in COMM 1110 and UNSW
You may use AI software for brainstorming ideas initially, but your final submission should
primarily be your own work. Avoid relying on AI tools to generate your report. UNSW employs a
tool to detect AI-generated writing with a high AI score.
Always ensure your assignments are completed independently, without asking others, such as
paid academic cheating companies, to complete them for you.
Our university's integrity department investigates cases of academic misconduct. If confirmed,
students will receive a grade of 0 for the course and an academic cheating record, or face
exclusion from UNSW. Please don't take the risk.
Additional learning and Free Writing Feedback on your draft:
Get individual feedback on you draft: https://www.student.unsw.edu.au/feedback-hub
• Word Limit: 1,500 words with a 10% buffer, allowing for a maximum of 1,650 words without penalty.
There's no minimum word requirement, so any word count below 1,650 is acceptable.
• The word count rule is straightforward – everything in your report, such as headings, subheadings,
and in-text citations, contribute to the word count, except for the reference list (bibliography), and
any inserted screenshots or images. Use your Word document's built-in word count feature to check
your word count accurately.
• Structure and Format: No need to include an introduction or executive summary. Start your report
directly with Section 1. Write in a business report style (e.g., using an essay format, formal
language, headings, and subheadings to make your report clear and easy to read). Ensure you
include your full name and student ID in the footer of each page.
• Referencing Style: While referencing is optional, if you choose to cite external information, adhere
to the Harvard referencing style for any sources cited in your report. (see the guideline link - How to
Cite Different Sources with Harvard Referencing | UNSW Australia)
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Guidelines for your Assessment 3 report
Section 1: Use Analytical Tools to Explore the Main Problem (40%)
This section is approximately 600 words (guide only, not a word limit).
1) Define the Main Problem: Define the main problem concisely to provide clarity on the main
issue requiring resolution for this assignment. Ensure that your report readers grasp a clear
understanding of the background story and the primary focus of your report.

2) Scope the Problem: Based on what we've learned in lectures and tutorials, use the "5Ws
Framework Tool" (What, Where, When, Who, Why) to analyse and define the problem. Select
any two 'W', and for each 'W' you choose, create at least three questions to explore different
dimensions of the problem. Next, identify the evidence required to answer each question you
created. For each piece of evidence, specify the type of evidence needed (e.g., Scientific
Literature, Organisational Evidence, Practitioner Expertise, or Stakeholder Evidence).
Instruction: Use the table below to organise your questions, evidence, and types of evidence.
Please integrate the 5W table provided directly into your report and type out your response as
text. All content within the 2W table will count towards the 1,500-word limit, so avoid using
screenshots.
3) Break Down the Problem: The "Logic Tree" is another tool commonly used to analyse
problems. Based on what we've learned in lectures and tutorials, construct a logic tree to
systematically analyse the problem. Break the problem down into its sub-parts to pinpoint
specific areas of concern and identify the key drivers contributing to the issue.
Instruction:
a) The logic tree needs to meet the Mutually Exclusive, Collectively Exhaustive (MECE)
Requirements. You can create the logic tree using PowerPoint (instruction video available in
Week 2's folder on Moodle) or any other tool you prefer. Ensure that all details in your logic
tree are clearly visible. Marks may be deducted if your tutor cannot read the details due to
blurriness. Please attach your logic tree as an image to your report. The logic tree image will
NOT count towards the word limit.
b) Prioritisation: Determine and justify which branches and/or sub-branches of your logic tree
should be prioritized for further analysis. Provide a detailed explanation of your analytical
process and clearly explain the rationale behind your choices. This prioritization will help guide
your data analysis later.
2ws Questions to Explore the
Problem
Evidence to collect Type of Evidence
W.. 1.
2.
3.
1.
2.
3.
1.
2.
3.
W.. 1.
2.
3.
1.
2.
3.
1.
2.
3.
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Section 2: Data and Statistical Analysis (40%):
This section is approximately 600 words (guide only, not a word limit).
Context:
After presenting your logic tree and having a detailed discussion with GreenLeaf Grocery, it
has been identified that a substantial portion of the increase in food waste is due to an
abundance of freshly made Dairy and Bakery products reaching their expiration dates before
being sold. GreenLeaf Grocery has shared a dataset with you, concentrating on these two food
items. A detailed description of the dataset is provided on page 6.
Order Details: Each record in the Excel dataset represents a single order, comprising 200 pre-
packed Dairy and Bakery items. The dataset provides insights into the quantities wasted due
to items remaining unsold before their expiration date
GreenLeaf Grocery Food Waste Allowance Target: GreenLeaf Grocery’s food waste allowance
percentage for Dairy is capped at 7.5%, implying that in any given order of 200 pre-packed
Dairy items, a maximum of 15 items should be wasted due to reaching expiration before being
sold. The waste percentage for Bakery is capped at 11.5% (a maximum of 23 Items per order).
GreenLeaf Grocery's Operation: When orders arrive at the GreenLeaf Grocery store, they are
initially placed in the storage area before being stocked on the shelves for sale. Operational
protocols with specific targets for shelving fresh food items are implemented to optimize the
availability of fresh products to customers while minimizing waste due to expiration.
• For Dairy: Target is to have the items on the shelf for at least 7 days before the expiry date,
given an expiration date of 12 days post-arrival at the storage area.
• For Bakery: Target is to have the items on the shelf for at least 6 days before the expiry
date, given an expiration date of 8 days post-arrival at the storage area.
Data and Statistical Analysis Instructions:
1) Analyse Food Waste:
a) Summary Statistics: Calculate the mean and standard deviation of food waste (variable
"Quantity_Wasted") separately for Dairy and Bakery. Next, compare these results with
GreenLeaf Grocery’s food waste allowance target.
b) Monthly Analysis: Based on what we learnt from our tutorials, creating PivotTable in Excel to
conduct a separate monthly analysis of Dairy and Bakery waste, using the "Order_Arrival_Date"
column to determine the order month. The primary objective is to illustrate the changes in
Dairy and Bakery waste monthly. Choose suitable visual diagrams to present your analysis
effectively in your report.

2) Investigate Shelf Longevity
GreenLeaf Grocery suspects that logistic issues may be causing delays in moving items from
storage to the shelves. This delay could reduce the display time of food items, contributing to
increased food waste due to items reaching their expiration dates before being sold.
a) Create a new variable: Create a new column named "Shelf_Longevity" to calculate the
shelf time (in days) of each order. This variable represents the duration each order stays
on the shelf before expiration
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Shelf_Longevity = “Order_ Expiration_Date” – “Shelf_Display_Date”
Monthly Data Analysis: Conduct a monthly analysis of “Shelf_Longevity” for Dairy and Bakery
items separately. First, calculate the mean and standard deviation (SD) for each month for
each category. Focus on how these two key summary statistics vary each month. Present
your findings using appropriate diagrams in your report and include a clear summary of the
main findings and key insights.

3) Analyse “Number of Orders” and “Prices”
a) Analyse the monthly trends in "the total number of Orders" (i.e., the total number of orders
each month) for Dairy and Bakery items separately. Provide a detailed explanation of your
analysis and select appropriate diagrams to present your findings.
b) Analyse the monthly trends in “prices” for Dairy and Bakery items separately. First,
calculate the mean and standard deviation (SD) for each month for each category. Focus
on these two key summary statistics in your analysis. Provide a detailed explanation of
your analysis and select appropriate diagrams to present your findings in the report.
c) Additional Analysis and Insights: Let’s conduct further analysis on the monthly trends in
"prices" for Dairy and Bakery items separately. In addition to standard deviation and
average, choose one or two other statistics (such as range, maximum, minimum,
median, etc.) to analyse. Select appropriate diagrams to present your findings and
include a clear summary of the main findings and key insights. Please emphasize how
these insights are relevant to addressing the food waste issue.

Section 3: Ethical Dilemmas with the Ethics Toolbox (20%)
This section is approximately 300 words (guide only, not a word limit).
GreenLeaf Grocery has decided to donate food that is approaching its expiration date (or even
past the expiry date) but is still safe to eat. However, concerns about possible liability and
food safety might prevent donations.
Your task is to select one stakeholder impacted by GreenLeaf Grocery's food donation
decision. Stakeholders may include GreenLeaf Grocery, local residents and consumers, the
local council, Local community organizations, such as shelters, community kitchens, or food
bank, food bank, or product manufacturers.
Please identify one ethical dilemma faced by your chosen stakeholder due to this food
donation decision. Reflect on the ethical concerns and challenges related to food waste at
GreenLeaf Grocery. Assess the potential harm to individuals or entities, such as the
environment, and elaborate on your reasoning. Ensure clarity and conciseness in your
explanation, focusing on the ethical implications and considerations of the identified dilemma
within the context of GreenLeaf Grocery's food waste issue.
Instruction: You are NOT required to apply the full 7-step Ethical Decision-making Framework;
your task is to identify one potential ethical dilemma from the perspective of your chosen
stakeholder. You can consider using the 4 ethical lenses taught in our week 4 lecture and
tutorials.
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Download Your Personal Excel Data for Your Report

You can access and download your personalised dataset for Assessment 3 through
the following link:
Click to download your data - COMM1110 Evidence-Based Problem Solving (shinyapps.io)


Steps to Download Your Personal Excel Data

1. Open the provided link above and then click the "Project Data" button.
2. Enter your student ID (without the "z") and click "Load Project Data" to access
your personalized dataset.
3. Once your data loads, download it by clicking "Download Data" (Note: It will be
in CSV format).
4. Open the downloaded CSV file and save it as an "Excel Workbook (.xlsx)"
before conducting any analysis. This ensures that your work can be properly
saved.
Important Notes
• Follow the provided steps diligently to download your personalized Excel file.
Then, apply the Excel skills you learnt from tutorials and online weekly Excel
questions to analyse the dataset contained within your downloaded Excel file.

• Numeric Variable Errors: If the R-Shiny App displays errors related to non-
numeric variables, please ignore these error messages. Simply download your
Excel data file.

• If you have any issues, please contact COMM1110@unsw.edu.au

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Personal Excel Data Details
Dataset Overview:
Each student will receive a personalised dataset consisting of 500 records, collected mainly
over the span of the 1/01/2024 to 31/12/2024. Each observation in the dataset represents
detailed information about individual food orders at GreenLeaf Grocery.
Variables:
The dataset encompasses 8 variables, each providing different insights into the food waste
issue at GreenLeaf Grocery. Here is a brief overview of each variable included in the dataset:

Variable Name Description Example
Values
Order_ID A unique identifier for each order. 43E4X6VIY
Order_Type The type of food item in the order. Dairy or
Bakery
Price The Selling Price at which GreenLeaf
Grocery sells the item (Dairy and Bakery
Product) to their consumers.

The price is in Australian dollar ($).

28.46
Order_Arrival_Date The date the order arrives at the GreenLeaf
Grocery store (storage area).
*Note: Multiple orders can arrive at the
same date.
2/11/2024
Shelf_Display_Date The date when the items are placed on the
shelf for sale.
4/12/2024
Order_ Expiration_Date The expiration date of the food items in
the order.
11/01/2024
Quantity_Ordered The total quantity of food items ordered in
each order, expressed in number of units.
200 units
Quantity_Wasted The total quantity (in number of units) of
food items wasted in this order due to not
being sold before expiration.
11 units

Marking rubric for Assessment 3
Criteria Fail Pass

Credit Distinction High Distinction
1. Analytical
Problem-Solving
40% Does not define or scope
the problem accurately.
The logic tree is missing
or inaccurately
constructed, showing a
lack of understanding of
the problem.
Defines and scopes
the problem with
minor errors or
omissions. The logic
tree is present but
may lack full MECE
compliance.
Clearly defines and
accurately scopes the
problem using the 5Ws
framework. Constructs
a coherent logic tree
that is largely MECE
compliant.
Clearly defines,
accurately scopes the
problem, and constructs
a fully MECE compliant
logic tree. Provides clear
insights derived from
the logic tree.
Defines, scopes the problem thoroughly, and
constructs a sophisticated logic tree that is
fully MECE compliant.

Derives practicable insights and prioritises
branches effectively with sound justification.
Ensure your analysis fully addresses the key
issue highlighted in this report.
2. Statistical
Problem-Solving
40% Does not apply or
inaccurately applies
statistical tools. Visual
representation is unclear
or inappropriate, and
insights are missing or
irrelevant.
Applies statistical
tools with minor errors
or omissions. Visual
representation is clear,
but insights may be
superficial.
Accurately applies
statistical tools, uses
appropriate visual
representation, and
generates relevant
insights.
Accurately and
insightfully applies
statistical tools, uses
sophisticated visual
representation, and
generates deep, relevant
insights.
Accurately and insightfully applies statistical
tools, uses innovative visual representation,
and generates novel, profound insights,
demonstrating a deep understanding of the
data and its implications. Ensure your
analysis fully addresses the key issue
highlighted in this report.
3. Ethical
Dilemma
Identification
20% Provides a partial or
limited description of an
ethical dilemma, which
may not constitute a real
dilemma or the links with
ethics are unclear.
Provides an adequate
description of a
generally appropriate
ethical dilemma with
some focus on
relevant details and
stakeholders.
Provides a sound
description of an
appropriate and well-
specified ethical
dilemma with solid
focus on relevant
details and
stakeholders.
Provides clear and
succinct descriptions of
an appropriate and well-
specified ethical
dilemma with clear
focus on relevant details
and stakeholders.
Provides a clear, succinct, and compelling
description of a clearly specified and
appropriate ethical dilemma with a very clear
focus on relevant details, stakeholders, and
the ethical implications inherent to the
identified dilemma.
Ensure your analysis fully addresses the key
issue highlighted in this report.

When you become a manager or own your own business in the future, you will need to write similar reports for your clients.
Therefore, this report is a valuable opportunity to practice writing these reports and preparing yourself for the future.