Forecasting for a Business Problem DATA4400
- Subject Code :
DATA4400
Assessment 3 Information
Subject Code: |
DATA4400 |
Subject Name: |
Data-driven Decision Making and Forecasting |
Assessment Title: |
Forecasting for a Business Problem |
Assessment Type: |
Written Report |
Word Count: |
1000 Words plus figures and references (+/-50%) |
Weighting: |
40 % |
Total Marks: |
40 |
Submission: |
Turnitin |
Due Date: |
Individual report via Turnitin due Wednesday, Week 13 |
Your Task
Develop a real-world forecasting project plan/proposal based on the learnings from the subject.
Assessment Description
This assessment seeks to simulate a real-world task that you may have to undertake in the future. Therefore, the assignment is non-prescriptive and requires you to pose a relevant, small, creative and significant forecasting problem to solve that could result in benefits to the organisation g choice.
In this assessment, you need to consider an organisation in an industry of your choice and articulate the steps this organisation needs to take to enable forecasting for data-driven decision making. You are required to source an example time series to demonstrate expected forecasting outcomes.
It will be much easier to pose a realistic scenario if you are familiar with the organisation and industry.
The report should address:
- The organisation you have chosen and your familiarity with its
- Why forecasting would help this organisation given their current o
- Thetime series you have sourced
- The forecasting technique you would recommend, with your reasons for doing But you are NOT EXPECTED TO fit other forecasting models and compare error statistics; or to compare training and test error statistics.
- The results of applying your chosen technique to your time series, including visual display and the actual forecast.
- The benefits of this forecasting project for the organisation (The benefit could be financial, such as Return on Investment (ROI) or societal benefits).
Assessment Instructions
- By Week 10 identify a company and industry you are familiar with that would benefit from a forecasting application. Note:
- The application needs to be based on forecasting (not some other aspect of analytics).
- Focus on a single, well defined (small)
- Sample datasets maybe sourced from:
an organisation if you work there,
public repositories
Open government data
Open data such as share prices and commodity prices.
- By Week 12 draft some preliminary points pertaining to the report in class. You are encouraged to consider the current mode of operation, possible inefficiencies, available data and how this data may be used to provide efficiencies based on the conceptsand techniques covered in the subject. Think of yourself as a consultant or a
- Your facilitator will advise on the appropriateness of your choice and proposed methodology regarding the requirements for the assessment.
- Include a list of references that are directly related to the content. Each reference needs to be linked to at least one specific point in the content of your assessment. It is expectedthat you will have at least 4 relevant references, web sites are ok, including a reference to the source of the data.
Important Study Information
Academic Integrity Policy
KBS values academic integrity . All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.
What is academic integrity and misconduct? What are the penalties for academic misconduct? What are the late penalties?
How can I appeal my grade?
Click here for answers to these questions:
http://www.kbs.edu.au/current-students/student-policies/.
Word Limits for Written Assessments
Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.
Study Assistance
Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click here for this information.
Late assignment submission penalties
Penalties will be imposed on late assignment submissions in accordance with Kaplan Business Schools Assessment Policy.
*Assignments submitted at any stage within the first 24 hours after deadline will be considered to be one day late and therefore subject to the associated penalty.
If you are unable to complete this assessment by the due date/time, please refer to the Special Consideration Application Form, which is available at the end of the KBS Assessment Policy:
https://www.kbs.edu.au/wpcontent/uploads/2016/07/KBS_FORM_Assessment- Policy_MAR2018_FA.pdf
Generative AI Traffic Lights
Please see the level of Generative AI that this assessment has been designed to accept:
Traffic Light |
Amount of Generative Artificial Intelligence (AI) usage |
Evidence Required |
This assessment ( ? ) |
Level 1 |
This assessment fully integrates Generative AI, encouraging you to harness the technology's full potential in collaboration with your own expertise. It will highlight your ability to demonstrate how effectively you can work alongside AI to achieve sophisticated outcomes, blending human intellect and artificial intelligence. |
Your collaboration with AI must be clearly referenced and documented in the appendix of your submission, including all prompts and responses used for the assessment. |
|
Level 2 |
This assessment invites you to engage with Generative AI as a means of expanding your creativity and idea generation. It will highlight your ability to complement your original thinking with the capabilities of AI. For example, through brainstorming and preliminary concept development. |
Your collaboration with AI must be clearly referenced and documented in the appendix of your submission, including all prompts and responses used for the assessment. |
|
Level 3 |
This assessment showcases your individual knowledge and skills in the absence of Generative AI support. It will highlight your personal abilities. For example, to analyse, synthesise, and create based on your own understanding and learning. |
Use of generative AI is prohibited and may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. |
This assessment is level 3 |
Assessment Marking Guide
Standards for this Task |
Points |
Feedback |
Topic and ProblemFamiliarity with topic (industry and organisation). The topic is precise and not too general. Clearly defined problem statement that is appropriate for forecasting: Needs and goals for a forecasting model from a business perspective clearly articulated. The problem statement is concise. The relevance of forecasting is clearly stated. Originality and initiative For a higher grade: An original question based on the problem statement is defined and addressed |
/15 |
|
MethodologyIdentified and sourced appropriate sample data. Identified and built an appropriate forecasting model. Output results, in particular forecasts with their prediction intervals, in a manner suitable for interpretation. This should include visual display. Use the forecasts to answer the question posed. For a higher grade: Clear and correct interpretation of the results to address the question posed. |
/15 |
Report :Structured such that the reader can grasp key points from the analysis. Key headings are included. Justification of assumptions and interpretations are clear and concise. In-line referencing is used, and references are relevant and genuine. Visualisations are used to convey key arguments. For a higher grade: Future strategies for the organization based on prediction results are clearly articulated |
/10 |
|
/40 |