BUSA3015 - Business Forecasting Assignment - Macquarie University

Assignment Task

The Case Study

You have been appointed as a consultant for the Australian Building Approvals company. Given the current economic condition in Australia has given your company an insight to perform forecasting on the value of building approvals in New South Wales (NSW).

As part of your role in the Business Analytics and Data Analytics team, you have been asked to forecast ‘Value of Building Approvals, NSW’, as part of a wider report being commissioned by the Australian Building Approvals. Your role requires you to follow the “Assessment Instructions” in the next page and complete report 1.

Skills in focus for this assessment

• Critical Thinking and Problem Solving
• Data, Information, and Digital Skills
• Discipline Knowledge - Business Analytics

Questions

1. Obtain the ABS statistics for Building Approvals, Australia

2. For the purposes of this report you are to consider the ‘Total value of building jobs; Total (type of building) work’ data. There are three series in Table 30: Original, Seasonally-adjusted, and Trend (please choose carefully throughout this report!)

3. Use Excel and no other statistical software for the purposes of this report.

4. You may use Minitab for constructing correlograms.

Exercise

1. Application

For the Seasonally-adjusted data for the Total Type of Building available in Table 30: Value of building approved - New South Wales: Forecast the out-ofsample values for every month in the period February 2023– January 2024 (both months inclusive) using only one appropriate exponential smoothing model (either simple exponential smoothing or Holt exponential smoothing models that you think is most appropriate given the data).

Once you identify and develop an appropriate exponential smoothing model with the starting values for parameter(s)= 0.5, what are the following numerical values:

1. The within-sample forecast for July 2022.

2. The out-of-sample forecast for May 2023.

3. The out-of-sample forecast for January 2024.

4. The MAPE.

5. The MAE. Critically think for a way to optimize alpha and beta (if there is no beta, you can input ‘0’ for question 7) via the MSE, and report the following values after your optimisation:

6. Alpha.

7. Beta.

8. The MAPE.

9. The within-sample forecast for July 2022.

10. The out-of-sample forecast for January 2024.

2. Application

For the Original-adjusted data for the Total Type of Building (Series ID: A422168F) available in Table 30: Value of building approved - New South Wales: Forecast the out-ofsample values for every month in the period February 2023 – January 2024 (both months inclusive) using Winter’s Exponential Smoothing.

Once you perform Winters Exponential Smoothing with alpha, beta and gamma, what are the following numerical values:

11. The seasonal component for November 2022.

12. The out-of-sample forecast for December 2023.

13. The out-of-sample forecast for January 2024.

14. The MAPE.

15. The MAE. Critically think for a way to optimise alpha, beta, and gamma via the MSE, and report the following values after your optimisation:

16. Alpha

17. Beta

18. Gamma

19. The MAPE

20. The out-of-sample forecast for January 2024.

3. For the model in Exercise 2, given that you have the actual data for the out-of-sample period (you considered the within-sample period to end in January 2023 – but you do have data for February 2023 and onwards) – discuss your forecasting method, your forecasts, and the business insights from these, using the following steps:

• Attribution
• Scope
• Application
• Analysis
• Articulation of Issues
• Critique
• Position

Pointers

For each of these sub-headings below, at least consider the notes that follow (you can consider more!). If you use a generative artificial intelligence (AI) tool (such as ChatGPT or similar), without citing the source, you will be penalised for violating academic integrity. As we have around 400 students in the unit, you also run the risk of plagiarism against other students by using such tools.

If you wish, you may include screenshot/s of any such AI response, and then showcase your own response (in typed words) which exhibits your critical thinking where you have modified the AI response to display higher-level thinking skills in line with the unit’s learning outcomes.

Scope

Explain the model in Exercise 2 by using language that is understood by a nontechnical audience. You will need to critically think about whether you discuss the preoptimised or post-optimised models.

Application

Describe and explain how you applied the data and your knowledge to perform the forecasts in Exercise 2. Describe and explain using language that is understood by a technical audience. You will need to critically think about whether you discuss the preoptimized or post-optimised models.

Analysis

• Consider the marking rubric, to assist you, you should include:
• A plot of the considered sample (February 2014 to January 2023) and the forecasts (within and out-of-sample) on one chart.
• You will need to critically think about whether you plot the pre-optimised or postoptimised models. A description of the chart and an analysis of your forecast is expected.
• Another plot of the actual data that is beyond the considered sample (February 2023 to January 2024) and the forecasts.
• A description of the chart and an analysis your forecast.

Articulation of Issues

Consider the marking rubric, to assist you, you should: Perform the appropriate check/s and test/s – provide some of this evidence. What are the issues based on your check/s and test/s above? Note: we have discussed and conducted several check/s and test/s when we are forecasting in this unit – and it is up to you to determine which checks and tests are appropriate – to determine issues, if any.

Critique

Consider the marking rubric, to assist you, you should: Critically evaluate your model, and critically evaluate the factors you would need to consider when forecasting in light of recent events. Compare and contrast alternative models. In the context of business forecasting, critically think and discuss any other considerations that need to be taken into account for your forecasts/forecasting to be useful for business purposes.

Position

Consider the marking rubric, to assist you, you should consider: This is an informed and justified conclusion that draws upon your discussion above. Given all of your discussion/s above, state your position regarding the business insights to be obtained by your forecasts, by referring to the evidence and ideas that you have discussed above.

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