Reference no: EM131955405
Business Analytics Assignment
Unit Learning Outcome (ULO)
ULO 2: Apply quantitative reasoning skills to analyse business performance.
This assignment assesses the ability to use the appropriate technique to analyse the data, correctly interpret the analysis output and draw appropriate conclusions.
ULO 4: Use contemporary data analysis tools to analyse business performance.
This assignment assesses proficiency in the use of data analysis tools within Microsoft Excel (one of the most widely used data analysis tools).
Graduate Learning Outcome (GLO)
GLO 1: Discipline-specific knowledge and capabilities: appropriate to the level of study related to a discipline or profession.
GLO 4: Critical thinking: evaluating information using critical and analytical thinking and judgement.
General Description / Requirements
The assignment requires that you analyse a data set, interpret and draw conclusions from your analysis, and then convey your conclusions in a written email.
Scenario
Supermart is one of Australia's leading supermarket chains. There are 150 stores in the chain. Originating from a family based chain of general stores, Supermart now has stores all over Australia, with the first one being established 30 years ago. In 2016, the company introduced an online channel for stores to enable customers, in selected suburbs, to make their purchase online. In terms of operation, individual store management has wide-ranging powers about day-to-day operations of their stores. However, broad company planning and direction take place in the company Head Office in Melbourne. Included in the Head Office is the Research and Analysis Department.
Having compared the company's position in the market and against the competitors, the General Manager - Grace Wong has asked you, Stephen Hennigsson, to conduct an exploratory and descriptive analysis to gain a better understanding of Supermart's performance.
Email from the General Manager
To: Stephen Hennigsson
From: Grace Wong
Subject: Analysis of the Store data
Dear Stephen,
The board is very keen to see how we have performed over the last financial year, in order to make sure we are keeping pace with our main competitors. As a result, can you investigate the following?
1. Can you provide me with an overall summary of Gross Profit?
2. The board wants to revisit the issue of whether it should now be compulsory for our stores to be open every day of the week, including Sunday, to aggressively compete with our major competitors. Can you provide a gross profit comparison for our stores that open on Sunday and those that do not?
3. As you know, our latest initiative has been the creation of our store online channel. I know many of our stores have included the online channel as part of their business operations. I have heard that Mall stores are leading the way when it comes to setting up online stores. Is there any evidence of this?
4. Wastage (unsold stock) is expensive to the organisation, especially if maintained at high levels.
a. Can you provide me with an overall breakdown of wastage?
b. I would also be interested in how the States compare when it comes to high levels of wastage in their stores?
5. I would like to see whether factors listed below provide any explanation in the variation of Sales between stores. If so, can you also indicate which factor is the most important?
a. Advertising expenses
b. Number of staff
c. Number of car spaces
d. Number of trading hours
Finally, I would also like an interactive Dashboard for me to explore performances of our stores. I am particularly interested in exploring our Sales and Gross Profit performance from different dimensions. I will leave the design details to you.
I look forward to your response and the Dashboard.
Sincerely,
Grace Wong General Manager
Assignment instructions
The assignment consists of three parts:
Part 1: Data Analysis
When conducting the analysis, you will apply techniques from descriptive analytics and visualisations, and hence will use various tables, graphs and summary measures. Sometimes we refer to this type of analysis as "exploratory analysis". When exploring data, we often produce more results than we eventually use in the report, but by investigating the data from a number of angles, we can develop a much better ‘feel' for the data: a deeper understanding of the data.
In order to prepare a reply to the General Manager, you will need to examine and analyse the dataset thoroughly. The General Manager has asked a number of questions. The following guidelines for each question should be considered carefully:
1. A summary of Gross Profit
Here you should only analyse "Gross Profit" by itself. The importance of other variables is considered in other questions. You should derive summary measures and check for unusual data. In addition, there may be well suitable tables and graphs that will illustrate, further and more clearly, other important features of the variable.
2. Gross Profit by Sundays
Investigate any particular relationship between the variables "Gross Profit" and "Sundays".
3. Online Channel by Location
Investigate any particular relationship between the variables "Online channel" and "Location".
4. Wastage; Wastage by State
Summarise the variable "Wastage". Also, investigate any particular relationship between the variables "Wastage' and "State"
5. Variation in Sales with other variables
Investigate any particular relationship between the variables "Sales" and other variables (a pair at a time).
The analysis section you submit should be no more than 8 pages of computer output (ie. output that you have copied into a Word document from Microsoft Excel). When you conduct your analysis, you will produce much more than this initially, but you should trim it down to only show the most relevant results in your maximum of 8 pages. Where possible, it is always useful to produce both numerical and graphical statistical summaries as sometimes, something is revealed in one that is not obvious in the other. Within the Word document, your analysis should be presented in the same sequence (and contain that same numbered sequence) that the questions have been asked by Grace Wong (the General Manager), and be clearly labelled and grouped around each question. Poorly presented, unorganised analysis or excessive output (more than 8 pages) will be penalised.
It is usual, when writing any professional document, to annotate any tabular or graphical output professionally. For example, TABLE 1: Summary statistics for the measure Gross Profit.
Save your computer analysis frequently.
Part 2: Email
You are required to reply by email, detailing essential information and conclusions from your data analysis. You are allowed no more than 2 pages to convey your written conclusions.
Keep the English simple and the explanations succinct. Avoid the use of technical statistical jargon. Your reader will not necessarily understand even simple statistical terms, thus your task is to convert your analysis into plain, simple, easy to understand language.
Further IMPORTANT instructions:
- The email is to be written as a stand-alone document (assume that the Grace Wong will only read your email). Thus, you should not have any references in the email to your analysis, nor should you include any charts and tables within it.
- Use an email format for your reply. That means the email heading (eg. To:, From:, Subject:) should be included, the recipient should be addressed at the beginning and the signature or name of the sender should be included at the end.
- When composing your reply, make sure that you actually answer the questions asked. Cite (state) the summary statistics of importance without referring to your analysis section.
- Sequentially number your answers in both your email and your analysis (1, 2 ... 5) to match the General Manager's email.
- Include a simple introduction at the start of the email and a summary/conclusion at the end.
- Marks will be deducted for the use of technical terms, irrelevant material, poor presentation / organisation / formatting and emails that are over two pages long.
When you have completed the email, it is a useful exercise to leave it for a day, return to it and re-read as if you knew nothing about the analysis. Does it flow easily? Does it make sense? Can someone without prior knowledge follow your written conclusions? Often on re-reading, you become aware that you have made some points in a clumsy manner, and you find that you can re-phrase them much more clearly.
Part 3: Interactive Dashboard
The minimum requirement is a neat, functional, interactive dashboard. Following questions will guide you designing an interactive dashboard.
1. What are the most appropriate visualisations for the dashboard?
2. What about choices of colour?
3. How can I use hierarchy and dimension?
4. How can I make the dashboard interactive?
Only Part 3 needed