Assessment 3: HR Policy Recommendation Project (40%) The HR Policy Recommendation Project is an extension of Assignment 2, and will be undertaken individually. Extending the data analysis and presentation in Assignment 2, the Project needs to propose possible casual relationships between the chosen metrics, test these relationships using predictive analytics techniques, and provide recommendations on how the organization should improve staffing practices to enhance profitability. You may adjust (add or remove) the metrics that your team used in Assignment 2 if it deems reasonable and necessary. In writing up the Project, you are advised to refer to what are discussed in the seminar on “Predictive Analytics in Action” and Chapter 6 of the textbook, and apply predictive analytics methods to justify your policy recommendations. The Project should be 2,000 words in length (plus or minus 10%), excluding cover page, reference list and appendix (if any). If you need to use Charts/Tables/Dashboard already presented in Assignment 2, please put them in the appendix. You need to submit the Project via LMS on Thursday, Week 13 at 5pm. The Project should include the following: a. Introduction b. Analyse relationship between key HR metrics using predictive analytics methods c. Provide recommendations on staffing policy to enhance organizational performance d. Conclusion Submission Format: An assignment cover sheet must be attached to the Project. Assignment should be submitted in Size 12 Times New Roman or Arial Font. Word count needs to be identified on the front cover of the assignment. To ensure that your work doesn’t get mixed up with others’, please use a filename which follows the convention: Unit Code, Assignment Number, the first three characters of your last name, your first initial and your Student Number. E.g. MBS603Assign1SmiJ12345678 for student John Smith with student id 12345678. The assignment will be assessed by the following criteria. • Quality of your policy recommendations (12) o Logic of policy recommendations • Justification for your policy recommendations (12). o Evidence from HR data to support policy recommendations • Application of appropriate predictive analytics methods (12). o Basic predictive analytics skills using Excel. • Writing skills and editorial care (4). o A minimum of 5 references cited correctly using APA or Chicago style.. Correct grammar and spelling.
Best HR Analytics Project Award The best HR Policy Recommendation Project will be awarded the “Best HR Analytics Project Award”. The Award winners will be announced when the mark of the Project is released, and will be given a Certificate.
Some other points should be consider are:
1. Correlation and regression?Correlation analysis is optional, while regression analysis is a must.
2. Regression for the whole organization or for individual divisions/branches of the organization?It is sufficient to do the regressions for the whole organization to make predictions, so no need to run regressions for each of the individual business divisions and branches.
3. Report of the regression output?In your report, you need to report and interpret the key content of the regression report as noted in the last seminar. You need to attach the original regression output in the appendix at the end of your report, which does not count toward the word limit.
4. Metrics to be included in regressions? As noted in the UILG, assignment 3 is an extension of assignment 2, so you need to include the metrics as required in assignment 2 in regressions to test your hypotheses about causal relationships as noted in page 13 of UILG.