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School of Business

Semester Two Examinations, 2023

MGTS3609 People Analytics: Theory, Strategy and Practical Application

Introduction (for questions A-G)

As of September 2023, you are a newly appointed Head of HR analytics at a Brisbane Car Sales Firm with 15 Branches. The organisation employees 1,210 employees in Queensland (801 in Brisbane; 202 in Ipswich and 207 in Logan).

Upon joining, you identify a high level of staff turnover (40%) and what seems to be a problem of high levels of sickness absence in the organisation. People seem to be taking time off work giving “burnout” as a reason. Just before resigning (August 2023), the CEO (Bob – who is based in the Brisbane Head Quarters) carried out a staff attitude survey, by sending electronic questionnaire survey links to staff by text on their phone. The survey responses could be tracked back to individual employees. In the text sent to staff, Bob stated “I want you to complete this survey. I will monitor who fails to complete the survey”. You get hold of the attitude survey dataset that was collected, calculate some variables from the data collected, and carry out some analysis (presented in the Appendix) to see if there is any information that might help you improve the situation.

 Information about the variables in the dataset linked to the output in the Appendix 

1 Location

Which Location the employee works in; there are three divisions: 1 =  Logan; 2 = Brisbane; and 3 = Ipswich

Employee Attitude Measures

2 Intention to Quit

A composite average measure constructed from questions relating to employees’ intentions to leave the organisation. This measure is an average of 3 questions using a scale ranging from 1=definitely will stay to 5=definitely will leave. Higher numbers mean greater intention to leave.

3 Job Burnout

A composite average measure constructed (average) from 4 questions relating to the extent to which various symptoms of “burnout” are present. The scale responses ranged from 1 = no burnout apparent to 5 = symptoms of burnout apparent. Higher numbers mean more stress.

4 Job Autonomy

A composite average measure constructed (average) from 4 statements relating to the autonomy in employees’ jobs. The employees could respond using a scale of 1 = strongly disagree to 5 = agree strongly. Higher numbers mean greater autonomy.

5 Job Engagement

A composite average measure constructed (average) from 4 statements relating to job engagement. The employees could respond using a scale of 1=strongly disagree to 5=agree strongly. Higher numbers mean greater engagement.

6 Coworker Pressure

A measure is constructed (average) from 3 questions relating to how much pressure their coworkers put them under to sell cars. The response scale ranged from 1=no pressure to 5=high levels of pressure. Higher numbers mean more pressure. 

7 Manager Pressure

A measure is constructed (average) from 3 questions relating to how much pressure their managers put them under to sell cars. The response scale ranged from 1=no pressure what-so-ever to 5=huge amounts of pressure.  Higher numbers mean more pressure.

8 Organisational Training

A measure is relating to how many hours training they received in the last 6 months. Higher numbers mean more training.

Questions a – g

Note, the introduction to this question can be found above

Outline of the analyses

Statistical analyses were carried out to investigate factors that predict employees’ intention to quit across the organisation. Results of correlation and regression analyses are set out in the Appendix (pages 5 & 6). 

a) Why is engagement and burnout an important thing for an HR function to try to manage? (10 marks) 

b) Drawing on material from the course, explain why measuring burnout might be considered an important predictor of intention to leave? (10 marks) 

c) Describe and interpret the results of the regression analysis presented on Page 6, citing any relevant statistics. (15 marks)

d) What problems might there be with using these results to draw conclusions about why people are leaving across this organisation? Specifically with reference to:

a. How robust the people analytic project is as a research activity (10 Marks)                                                      

b. The potential for the analyses to help the analytics team present causal evidence to explain why people are leaving the organisation (10 Marks)                                                       

e) Discuss the analytics project outlined with regard to an ethical approach to HR analytics. (10 marks)

f) When you discuss the results of the analyses with the finance director of the company, he suggests that you could add information on how many hours employees spend a month surfing social media sites on their work computers (during work hours - which apparently was “a huge amount”) to the dataset and potentially run the model again “predicting slacking in the work-place”. Can you see any problems with these additional analyses as an HR analytics activity? (10 marks)

g) What other HR analytics activities could the team engage in to understand why people are experiencing burnout? Provide a rationale for everything you suggest. (25 marks)

(Total: 100 marks)