代写COMM1110 Evidence-Based Problem Solving

日期：2024-03-09 08:30

COMM1110 Evidence-Based Problem Solving

Due date: Week 5: 11.59am, Friday 15th March

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You are a consultant at Solution-X, a leading consulting firm well-regarded for its innovative

and comprehensive problem-solving solutions that blend analytical scrutiny, statistical

insights, and ethical considerations.

We've partnered with GreenMart, a retail supermarket chain facing a pressing issue: a

notable increase in food waste, especially in the fresh food (Fruit and Vegetable)

section. GreenMart is eager to delve into the root causes of this waste surge and

seeks actionable recommendations to tackle the problem head-on.

GreenMart's fresh food section, brimming with fruits, veggies, dairy, meat, seafood,

and bakery delights. Yet, a rising trend in food waste threatens to dampen the

excitement. Whether it's items nearing expiry, facing damage, falling short of quality

standards, or spoiling due to storage mishaps, the waste is both a financial setback

and an environmental headache.

Now, GreenMart isn't just about profits; they're deeply committed to operational

efficiency, reducing their environmental footprint, and championing sustainability.

1. Investigate the factors contributing to the rise in food waste in GreenMart’s fresh

food section.

2. Develop and present well-considered and actionable recommendations to

GreenMart to assist them in implementing effective strategies to reduce food

waste.

2

Your Role and Responsibilities

Solution-X has formed a team of consultants and business analysts to provide thorough

analysis and actionable recommendations to GreenMart. At the project's end, we'll compile a

comprehensive report. Your role, assigned by the team lead, is crucial to crafting practical

solutions. Let's get started on making a insightful business analysis report.

Your Tasks:

Assessment 3: Preliminary Analysis Pack (25%):

? Prepare a preliminary business analysis report for an internal meeting on the rise in food

waste at GreenMart's fresh food section. Use analytical, statistical, and ethical tools to

understand the drivers behind this increase. This analysis will guide discussions and shape

future solutions.

? Focus Areas:

? Analytical Toolbox: Identify potential factors and drivers contributing to the food

waste problem.

? Statistical Toolbox: Examine the data provided by GreenMart to identify food waste

trends and patterns. This analysis will aid in pinpointing the potential causes of the

issues, directing more detailed analysis, and focusing solution development on key

issues to prioritise your problem-solving effort.

? Ethics Toolbox: Identify any ethical dilemmas associated with food waste

? Word limit: 1,500 words (excluding graphs, figures, and reference list). An additional 10% buffer

(1,500 + 150 words) will be applied if you exceed the word count.

? Structure and Format: An introduction or executive summary is NOT required. You should

structure your responses to directly answer each question in the Initial Analysis Pack. Write in a

business report style, utilizing formal language, clear headings, and subheadings to organize your

responses to each question. The clarity, coherence, and organization of your report are crucial,

and each section should be well-integrated to offer comprehensive insights into the addressed

questions.

? Referencing Style: Please use the Harvard referencing style for any sources cited in your report

(see The 'In-Text' or Harvard method for more information).

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Guidelines for your Business Report

Section 1: Scoping the Problem Using the Analytical Toolbox (40%):

This section is approximately 600 words (guide only, not a word limit).

1) Define the Problem: Define the problem concisely to provide clarity on the main issue

requiring resolution for this assignment.

2) Scope the Problem: Utilize the 5Ws framework (What, Where, When, Who, Why) to frame

and scope the problem. For each 'W', formulate questions to explore various dimensions

of the problem and identify evidence required to substantiate the answers. Choose only

two 'Ws' for your report.

Instruction: Use the table below to organise your questions, evidence, and types of

evidence. You are required to provide at least three points for two ‘W’s (you can choose

any 2 “W” s from the 5 W).

Please integrate the 5W table provided directly into your report and type out your response

as text. All content within the table will count towards the 1,500-word limit, so avoid using

screenshots

2ws Questions to Explore the Problem Identified Evidence Type of Evidence

W.. 1.

2.

3.

1.

2.

3.

1.

2.

3.

W.. 1.

2.

3.

1.

2.

3.

1.

2.

3.

3) Break Down the Problem Using a Logic Tree: Construct a logic tree to systematically

analyse the increase in food waste at GreenMart, dividing the problem into its parts and

sub-parts to pinpoint specific areas of concern and contributing drivers.

Instruction:

a) Include a clearly labelled logic tree in your submission. The tree needs to meet the

Mutually Exclusive, Collectively Exhaustive (MECE) Requirements.

Instructions for creating a clear logic tree using PowerPoint are available on our

course Moodle page (Week 2's folder). Ensure all details in your logic tree are

clearly visible. Marks may be deducted if your tutor cannot read the details due to

blurriness. Attach your logic tree as an image to your report. The logic tree image

will NOT count towards the 1,500-word limit.

b) Prioritisation: Determine and justify which branches and/or sub-branches should

be prioritized for further analysis. Ensure coherence between the logic tree and

provide explanation to detail your analytical process, providing a clear rationale for

your choices.

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Section 2: Gaining Insights Using the Statistical Toolbox (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 GreenMart, it has

been identified that a substantial portion of the increase in food waste is due to an

abundance of freshly packed fruits and vegetables reaching their expiration dates before

being sold. This insight has refined the focus of your investigation, necessitating a more

targeted analysis to comprehend the waste generated from these specific items.

GreenMart 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 150

pre-packed fruits and vegetable items. The dataset provides insights into the quantities

wasted due to items remaining unsold before their expiration date

GreenMart Food Waste Allowance Target: GreenMart’s food waste allowance percentage for

fruit is capped at 6.67%, implying that in any given order of 150 pre-packed fruit items, a

maximum of 10 items should be wasted due to reaching expiration before being sold. The

waste percentage for vegetable is capped at 12% (a maximum of 18 Items per order).

GreenMart's Operational Protocols: When orders arrive at the GreenMart retail 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 fruit: 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 vegetable: Target is to have the items on the shelf for at least 5 days before the

expiry date, given an expiration date of 8 days post-arrival at the storage area.

Statistical Toolbox Analysis Instructions:

1) Analyse Food Waste:

a) Summary Statistics: Calculate the mean, and standard deviation of food waste

(variable "Quantity_Wasted") for fruits and vegetables. Then, compare these

results with GreenMart’s food waste allowance target

b) Monthly Analysis: Create pivot tables in Excel to conduct a monthly analysis

of fruits and vegetables waste, using the variable "Order_Arrival_Date" to

determine the order month. Choose an appropriate visual representation you

see fit to showcase this result in your report.

2) Investigate Logistic Issues and Shelf Time

Management at GreenMart 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.

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a) Create a new variable: Create a new column named "Shelf_Duration" to

calculate the shelf time (in days) of each order. This variable represents the

duration each order stays on the shelf before expiration

Shelf_Duration = Expiration_Date_Of_Order – Inventory_Replenishment_Date

b) Summary Statistics and Monthly Analysis: Calculate the summary statistics

of “Shelf_Duration” for fruits and vegetables separately. Then, perform a

monthly analysis and choose a suitable diagram to present it in your report.

3) Analyse Number of Orders, Prices, and Additional Insights

a) Order and Price Analysis: Select suitable statistical analysis tools and

visualizations (diagrams) to examine the trends in the number of orders and

prices for fruits and vegetables over time.

b) Create another new column: Now, you're required to create a new column in

your Excel file. This column can contain any information you consider relevant,

ensuring that it's solely based on your existing Excel data. Clearly explain the

rationale behind creating this new column and how it can help you address the

food waste issue. Furthermore, include a screenshot displaying only the first

10-15 rows of this new column. Insert the screenshot into your report

alongside your explanation for this question. The screenshot does not count

towards the word count.

Instruction: Include clear tables or graphs to display the results of each statistical analysis

part (1-3). Ensure they are well-labelled and easy to read. Provide a summary of the main

findings from your analysis above, highlighting key insights obtained. Emphasize their

relevance to helping you solve the food waste issue. (Note: Tables, Diagrams, or Graphs

in this section are NOT in the word count)

Section 3: Ethical Dilemmas with the Ethics Toolbox (20%)

This section is approximately 300 words (guide only, not a word limit).

Select a stakeholder impacted by GreenMart's food waste issue. Stakeholders may include

GreenMart, residents and consumers, the Local council, or Regulatory Agencies like ACCC,

waste management companies, or product manufacturers.

Consider one ethical dilemma faced by your chosen stakeholder due to the increase in

food waste. Reflect on the various ethical concerns and challenges related to food waste

at GreenMart. Assess the potential harm to individuals or entities, such as the

environment, and elaborate on your reasoning (Please refer to our tutorial materials from

Week 4 for additional details and support).

Instruction: Ensure clarity and conciseness in your explanation, focusing on the ethical

implications and considerations of the identified dilemma within the context of

GreenMart's food waste issue.

For this section, you are NOT required to apply the full 7-step Ethical Decision-making

Framework; your task is merely to identify one potential ethical dilemma related to the

food waste issue at GreenMart, considering the perspective of your chosen stakeholder.

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You can access and download your personalised dataset for Assessment 3 through

the COMM1110 R-Shiny website using the following link:

Click this link to download your data - https://comm1110.shinyapps.io/comm1110/

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

? The COMM1110 R-Shiny website is only used for downloading data set.

? Each student is provided with a personalized Excel file containing 500 orders.

? 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 analyze 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 with downloading your personal Excel file from the above

link, please contact our Course email at COMM1110@unsw.edu.au

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Dataset Overview:

Each student will receive a personalised dataset consisting of 500 records, collected over the

span of the 1/01/2023 to 31/12/2023. Each observation in the dataset represents detailed

information about individual food orders at GreenMart.

Variables:

The dataset encompasses 8 variables, each providing different insights into the food waste

issue at GreenMart. 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. Fruit or

Vegetable

Price The Selling Price at which GreenMart sells

the item (Fruit and Vegetable) to their

consumers.

$28.46

Order_Arrival_Date The date the order arrives at the GreenMart

store (storage area).

*Note: Multiple orders can arrive at the