BUSA90520
Data Wrangling and Visualisation

Muesli Pty Ltd – Production Planning


BUSA90520 2025 S1 1 Group Assignment 2
Overview
This assignment is worth 18% of the overall subject grade.
This assignment is due on Monday, May 5, 2025 at 11:59 AM.
The assignment must be submitted via the University of Melbourne LMS.
One person must upload one single ZIP or RAR file on behalf of the group, containing:
• One Tableau workbook. A single file must contain your dashboard, data sources and visualisations.
• 2-3 minute video with your brief analysis and recommendations.
It is to be completed in groups of up to 4 students. You will be assessed as a group. All group members are
expected to contribute equally to your group’s effort. Each group is responsible for managing the
distribution of the workload for completing the project.
Learning Outcomes
This assignment will allow you to develop your ability to analyse data and prepare and present information
to support operational and strategic decision making using a variety of technologies such as databases,
programming languages and visualisation software.
More specifically:
• Use data visualizations to compare aggregate measures between subsets of data or over time, to identify
patterns, trends and exceptions present in data.
• Interpret data visualisations to explain financial and/or operational outcomes and make
recommendations for actions likely to improve those outcomes.
• Design the layout and content of an interactive dashboard to support decision making.
• Implement an interactive dashboard with TableauTM software.
o Import/connect data for analysis.
o Select chart types that are relevant to identified areas of analytical inquiry.
o Create charts to visually display data in ways that aid interpretation of that data.
o Make appropriate use of interactivity to make additional detail available on demand.
o Implement a simple prediction model and use it to forecast future outcomes.
Preparation
Download and install Tableau Desktop software and any necessary drivers to retrieve data from SQL server
databases. See the relevant LMS pages for instructions.
Obtain and enter a license key to register Tableau for educational use.
Refer to the briefing document for relevant information about Muesli Pty Ltd.
Download the additionally provided data files.

BUSA90520
Data Wrangling and Visualisation

Muesli Pty Ltd – Production Planning


BUSA90520 2025 S1 2 Group Assignment 2
Objective
The Supply Chain and Logistics Manager (SCLM) at Muesli Pty Ltd has asked you to design and develop an
interactive dashboard to support short-term operational planning. The SCLM’s goal is to ensure sufficient
product is available for sale at the right locations and times. In this industry, short-term sales
performance is strongly influenced by inventory availability. Key decisions focus on production scheduling at
the main factory and allocating finished goods to the three distribution centres.
The industry comprises 10 small manufacturers, few of which produce all 12 products. An industry association
facilitates data sharing, where each member uploads weekly sales data. This data is then aggregated and
redistributed to all members. However, due to collection and distribution delays, this dataset may be less
current than the company’s internal records.
Muesli Pty Ltd operates on a 10-day production cycle, with planning occurring at least a week in advance to
allow time for raw material procurement. A rough plan is made for which of the six active products will be
produced on each day. Producing the same product over multiple days is more efficient, as switching
between products requires several hours for cleaning, reconfiguring, and staging materials. To avoid
inefficiencies from frequent changeovers, the company mandates that each production run lasts at least one
full day.
Initially, the company focused on building stock at the main warehouse. It has since adopted an inventory
policy that caps the main warehouse at 100,000 units and each of the three distribution centres at 50,000
units. With only six products in focus, this translates to maximum stock levels of 8,000 to 11,000 units per
product per distribution centre. Resupply shipments are sent every few days to maintain these levels.
In discussion, the SCLM highlighted the need to predict when current inventory will run out:
“ We’d love to know where we’re going to run out first, so we can prioritise resupply before it happens. It’s been
hard to get inventory levels right because demand varies by location and over time. Setting max inventory
levels based on days of supply, instead of fixed quantities, would be much more effective. I asked the sales
team to calculate average daily sales for each product at each location — they’ve sent me a file with those
figures, which I’ll share with you.”
Dashboard
The design of your dashboard must directly support production planning for each 10-day cycle, monitor
inventory availability, and keep an eye on related key performance indicators (KPI).
Your dashboard must, at minimum, support the following inquiries:
• At-a-glance assessment of sales, production yields, and pending production (in units); and shipping
and warehousing costs (in $). Totals for the previous 28 days.
• Current inventory of each product in each location, including a stockout prediction (quote above).
• The remaining, unproduced, part of the current production schedule.
• Production yields vs sales for the previous 28 days, by product.
• Inventory levels over the previous 28 days, by product and by location.
• Sales demand trends, by product.
• Product margins, to assist with production prioritisation between the products.


BUSA90520
Data Wrangling and Visualisation

Muesli Pty Ltd – Production Planning


BUSA90520 2025 S1 3 Group Assignment 2
Analysis and Recommendation
To demonstrate how your dashboard supports decision-making, you’ll give a 2–3 minute live walkthrough
showing how to effectively use it to plan the next production cycle. You must make a specific
recommendation: exactly which products to produce, in what order, and for how many days—effectively
assigning a product to each of the 10 days following the current schedule.
The SCLM also wants to see what insights the dashboard provides about the current inventory management
policy (maximum stock levels per product per location). In your video, share your opinion of the policy and
suggest any improvements.
All recommendations must be justified using your live dashboard only—no spreadsheets or extra slides. You
may include ONE single external slide or page (e.g., outside Tableau) to summarise your recommendation.
Keep your tone informal. Your goal is to offer thoughtful guidance and show how the dashboard helps draw
reasoned conclusions—not give a feature tour or training session. Avoid guesses or vague hunches—explain
your thinking clearly.
Only one or two team members need to speak in the video. No face recordings are required—just voiceover.
The dashboard should be visible throughout, using live screen share rather than static screenshots.
Technical Considerations
To estimate how long current inventory will last, you must use the provided average daily sales data file. This
file will be updated regularly, so your solution should allow it to be replaced without requiring
reconfiguration or manual edits.
Use the industry sales and product cost data to help prioritise products—those with higher profit margins or
demand should generally take precedence. However, keep in mind that the dashboard’s primary purpose is
production planning and inventory management, not deep sales analysis.
You must build the dashboard in Tableau, directly connected to the source data. You may not use any
external tools (e.g., Excel) to modify data, perform calculations, or create new files for Tableau to ingest.
You can use a combination of Tableau and SQL, as long as all SQL is included in Tableau as Custom SQL
queries. These queries must run live against the database. It’s acceptable to write and test SQL in Data Studio,
but the final queries must be embedded in Tableau—not pre-run and copy-pasted as static data. Note:
Tableau does not support Common Table Expressions (CTEs), so use nested sub-queries instead.
The dashboard is intended as a real-time operational tool. It should be designed with the expectation that
data updates daily and the SCLM may check it at any time for the latest insights.
Use of GenAI tools
You may use ChatGPT or similar AI tools to assist with building your dashboard—for example, to write or
refine SQL queries or help with Tableau calculated fields. Attribution for AI-generated code is not required.
However, you may NOT use AI to prepare or deliver your analysis or video. This includes using AI to write a
script for you to read during the recording.


BUSA90520
Data Wrangling and Visualisation

Muesli Pty Ltd – Production Planning


BUSA90520 2025 S1 4 Group Assignment 2
Marking Guide
Note that ALL weightings below are subject to adjustment if objectives and guidelines are not met.
Dashboard Design
Choices assist the viewer to assess performance and investigate areas of interest.
Weight
40%
The choice of KPIs and data are relevant to objectives, and comprehensive. 8
Chart types are well chosen to reveal important performance trends or patterns.
Charts are clear and not overloaded trying to support multiple purposes or too much detail.
12
Layout and placement convey hierarchy between levels of detail and or filtering actions.
The user can interact with the dashboard by means of filters and tooltips. The choice of
interactions provided are useful (“detail on demand”) and relevant to operational goals.
The design, look, and feel of components is consistent.
12
The colour scheme is intentional and chosen to convey semantic meaning, highlight key
patterns or emphasize key elements to focus attention on specific areas.
Colour choices are consistent.
8
Dashboard Clarity and Correctness
The implementation of the dashboard is well executed and free from errors.

35%
Charts are accurate, free of computational, aggregational or data importation / filtering errors.
Filters are transparently observable, and do not make point-in-time assumptions.
Interactivity functions correctly and does not lead to distorted or non-sensical displays of data.
15
Data are labelled directly and are intentionally sorted.
Proportions are accurate and well chosen; intervals are equidistant for interval and ratio data.
Titles are short, well-chosen, and clearly indicate what performance measures are being shown
in what context.
Charts are free from unneeded decoration; redundant labels; over-precision; distracting grid
lines, tick marks or axis lines.
10
The implementation is simple and tidy. All components are in a single Tableau file.
The number and content of data sources is balanced to facilitate analysis; each one well named
with a distinct purpose containing only relevant content (minimal overlap, redundancy, or
irrelevance)
Dimensions, measures, and parameters are organised and well named. Worksheet tabs are well
organised and well named.
10
Analysis & Recommendation (Video Content)
The analysis and recommendations are clearly made, and well-reasoned.

25%
The presentation accurately summarises the relevant charts and tables, with no
misinterpretations—including awareness of potential selection bias in the data. The final
recommendation clearly aligns with the company’s goals and objectives.
15
Spoken audio is clear and easy to understand, with a natural pace and well-structured
sentences. Key points are made once and explained effectively.
The presentation flows logically, with each part reinforcing the overall message and supporting
a coherent narrative.
The presentation does not exceed 3 minutes.
10


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