COMM1110 Assessment 3: Evidence-Based Problem Solving | UNSW Sydney
| Category | Assignment | Subject | Business |
|---|---|---|---|
| University | UNSW Sydney | Module Title | COMM1110 Evidence-Based Problem Solving |
COMM1110 Project Overview and Main Objective
Assume in June 2024, you are an intern consultant at PWC, a leading consulting and financial firm in Australia.
Your client, YammyMart, an Australian retail supermarket chain facing a pressing issue: a notable increase in food waste, especially in the fresh food (Meat and Vegetable) section. YammyMart is eager to delve into the root causes of this waste surge and seeks actionable recommendations to tackle the problem head-on.
YammyMart’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, YammyMart isn’t just about profits; they’re deeply committed to operational efficiency, reducing their environmental footprint, and championing sustainability.
Your main task and objective in this “25% Assessment 3″are toprepare a business analysis report for an internal meeting on the rise in food waste at YammyMart’s fresh food section. Use analytical, statistical, and ethical tools to understand the drivers behind this increase.
Analytical Toolbox: Identify potential factors and drivers contributing to the food waste problem.
Statistical Toolbox: Analyse YammyMart’s data to identify food waste trends and patterns. This will help pinpoint potential causes, direct detailed analysis, and focus solution development on key issues.
Ethics Toolbox:Identify any ethical dilemmas associated with food waste.
Section 2: Data analysis 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 YammyMart, it has been identified that a substantial portion of the increase in food waste is due to an abundance of freshly packed meat 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.
Yammy Marthas 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 meat and vegetable items. The dataset provides insights into the quantities wasted due to items remaining unsold before their expiration date.
YammyMart’s Operational Protocols: When orders arrive at the YammyMart 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 meat: Target is to have the items on the shelf for at least 8 days before the expiry date, given an expiration date of 10 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.
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Statistical Toolbox Analysis Instructions:
1) Analyse Food Waste:
- Summary Statistics: Calculate the mean and standard deviation of food waste (variable “Quantity_Wasted”) separately for meat and vegetables. Next, compare these results with YammyMart’s food waste allowance target.
- Monthly Analysis: Based on what we learnt from our tutorials, creating PivotTable in Excel to conduct a separate monthly analysis of meat and vegetable waste, using the “Order_Arrival_Date” column to determine the order month. The primary objective is to illustrate the changes in meat and vegetable waste on a monthly basis. Choose suitable visual diagrams to visualize your analysis effectively in your report.
2) Investigate Logistic Issues and Shelf Time
Yammy Martsuspects 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.
- Create a new variable:Create a new column named “Shelf_Lasting_Time” to calculate the shelf time (in days) of each order. This variable represents the duration each order stays on the shelf before expiration
Shelf_Lasting_Time= Order_ Expiration_Date-Shelf_Restocking_Date - Summary Statistics and Monthly Analysis: Based on the concepts covered in our lectures and tutorials, conduct a monthly analysis to demonstrate how the key summary statistics of “Shelf_Duration” for meat and vegetables change over time. Perform the analysis separately for meat and vegetables and choose a suitable diagram to present it in your report.
3) Analyse Number of Orders, Prices, and Additional Insights
- Order and Price Analysis: Let’s analyse the monthly trends in the number of “orders” and “prices”for meat and vegetables separately over time, based on the data analysis concepts covered in our lectures and tutorials. You can select the key statistics you want to focus onand then choose suitable diagrams to present your analysis in your report.
- Create an additional new column: you are required to create a new column in your Excel file containing information relevant to your analysis of the food waste issue. This new column should be based solely on the existing Excel data. Once you have created the new column, provide a clear explanation of the rationale behind it and how it contributes to addressing the food waste issue in your report. Additionally, include a screenshot displaying the first 10-15 rows of this new column in your Excel file. Insert the screenshot into your report alongside your explanation. The screenshot is not in 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 clear summary of the main findings and key insights from your analysis. Emphasize their relevance to helping you solve 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).
Select a stakeholder impacted by YammyMart’s food waste issue. Stakeholders may include YammyMart, 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 YammyMart. 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 YammyMart’s food waste issue.
For this section, you are NOT requiredto apply the full 7-step Ethical Decision-making Framework; your task is merely to identify one potential ethical dilemmarelated to the food waste issue at YammyMart, considering the perspective of your chosen stakeholder.
