(HRMT5502)


SEMESTER 1, 2021 EXAMINATIONS

WITH R OUTPUT

Note: the R output will be provided 48 hours prior to the exam

Management & Organisations


(People Analytics)

Practice Exam Paper


Time Allowed: 2:00 hours

INSTRUCTIONS:

This paper contains: 14 Pages (including title page)

This paper contains TWO parts.

Part A: Short Answer Questions- contains five sections with short answer questions. Complete TWO of the five sections. Marks are identified within each section.

Part A marks: 10

Part B: Mini-Case Analyses- contains five mini-case studies with statistical output. Complete ALL questions. Marks are identified within each section.

Part B marks: 50

Total marks: 60 (to be recalculated to a mark out of 40).

This is an open-book, online examination. You are permitted to bring in to the exam your notes, textbooks, calculators with approved UWA sticker, together with your writing materials.


SUPPLIED STATIONERY

ALLOWABLE ITEMS

  UWA Approved Calculator with Sticker

  Textbook

  Notes

PLEASE NOTE

Examination candidates may only bring authorised materials into the examination room. If a supervisor finds, during the examination, that you have unauthorised material, in whatever form, in the vicinity of your desk or on your person, whether in the examination room or the toilets or en route to/from the toilets, the matter will be reported to the head of school and disciplinary action will normally be taken against you. This action may result in your being deprived of any credit for this examination or even, in some cases, for the whole unit. This will apply regardless of whether the material has been used at the time it is found.

Therefore, any candidate who has brought any unauthorised material whatsoever into the examination room should declare it to the supervisor immediately. Candidates who are uncertain whether any material is authorised should ask the supervisor for clarification.

Candidates must comply with the Examination Rules of the University and with the directions of supervisors.

No electronic devices are permitted during the examination.

All question papers and answer booklets are the property of the University and remain so at all times.

PART A: 

PLEASE ATTEMPT TO ANSWER ANY TWO OF THE FOLLOWING FIVE QUESTIONS IN THIS SECTION. Each question is worth 5 marks.

Total marks for this section: 10. Marks are identified with each question. Please answer the questions in the booklet provided and respond in your own words.

Question A1: Human Resource Analytics (5 marks)

a) What is Human Resource (HR)/People Analytics? Provide a definition of HR/People analytics in your own words. (2 marks)

b) What is the difference between HR metrics and HR analytics? Provide examples of each. (2 marks)

c) Describe one main statistical tool and/or technique used for HR analytics and provide a workplace example. (1 mark)

Question A2: Employee Turnover (5 marks)

Employee turnover costs can be substantial for organisations. To estimate these costs, many organisations simply calculate the cost of turnover as 150% of the departing employees’ salary. With your understanding of HR analytics, discuss how turnover can be costed to more accurately reflect the ‘real’ cost to the organisation? (5 marks)

Question A3: Employee Performance (5 marks)

Your CEO requests the following: “What is the value of good versus great performance? Is it necessary to have great performance in every job and on every job element? Where should I push employees to improve their performance, and where is it enough that they meet the minimum standard?” Discuss. (5 marks)

Question A4: Correlation and Regression (5 marks)

Your CEO requests the following: “I see that there is a high correlation between employee engagement scores and sales revenue across our different regions. Does that mean that if we raise engagement scores, our sales go up?” As the HR manager, how would you respond to this request given your knowledge of HR Analytics and your understanding of correlation and regression? Discuss. (5 marks)

Question A5: A HR Analytics Framework (5 marks)

The LAMP model is a framework for decision-making in Human Resource Management. In your own words, answer the following questions about the LAMP model.

a) Describe each of the four components of the LAMP model, and illustrate the components with examples. (4 marks)

b) Discuss how the four components relate to each other in the overall framework. (1 mark)

PART B: 

ALL QUESTIONS ARE COMPULSORY in this section. PLEASE ATTEMPT TO ANSWER ALL QUESTIONS. Each question is worth 10 marks.

Total marks for this section: 50. Marks are identified with each question. Please answer the questions in the booklet provided and respond in your own words.

Question B1: Diversity Analytics (10 marks)

A HR analyst wanted to check for cultural differences in relation to job performance. To test this, the analyst used a chi-square test for independence. The R output is below. Use a 5% significance (alpha) level.

a) Demonstrate how the expected count of 5.8 for ‘international’ and ‘exceptional’ was calculated. (2 marks)

b) Discuss whether there are significant differences in relation to culture and job performance levels (refer to the appropriate results to support your decision). (4 marks)

c) Provide a conclusion in relation to the results. Make sure you use simple, plain language (no statistical terms). (2 marks)

d) Provide one management recommendation based on the results. (2 marks)

Question B2: Predicting Employee Turnover (10 marks)

A HR Manager wanted to predict employee turnover. The manager used a logistic regression to predict employee turnover (0=stayer, 1=leaver) with the following predictors:

age (in years)

job level (1=administrative staff, 2=customer service staff, 3=team leaders, 4=managers, 5=senior managers) Note: administrative staff are the reference group.

years at company (number of years)

job involvement (1-4 scale, 1=not at all involved, 4= extremely involved)

job satisfaction (1-4 scale, 1= not at all satisfied, 4= extremely satisfied)

work-life balance (1-4, 4=excellent work-life balance)

performance rating (1-5, 5=exceptional)

mentor (0= the employee does not have a mentor, 1= the employee does have a mentor).

The logistic regression output is presented below. Use a 5% significance (alpha) level.

a) Determine which variables make a significant contribution to predicting employee turnover (whether an employee will leave the organisation). Refer to appropriate statistical output to support your answer. (4 marks)

b) Discuss the usefulness/quality of the model. Refer to appropriate statistical output to support your answer. (4 marks)

c) Interpret the Exp(B)/odds ratio for the following two variables: Performance Rating and Mentor(1). (2 marks)




Classification table


Question B3: Predicting Employee Performance (10 marks)

A manager wanted to predict employee performance of new hires (those hired in the past 12 months). The manager used the employee performance rating provided by each of the employee’s manager as the dependent variable (1-5 scale, 5= exceptional). The following predictors were used:

● age (in years)

● gender (0=female, 1=male)

● induction (0=did not attend, 1= attended induction training)

● technical competency (0=not competent, 1=competent)

● verbal reasoning test (1-10, 10=high verbal reasoning).

Refer to the R output presented below to respond to the following questions. Use a 5% significance (alpha) level.

a) Determine which variables are significant predictors of employee performance. Refer to appropriate statistical output to support your answer. (3 marks)

b) Write out the regression equation to predict employee performance. (2 marks)

c) Explain the coefficients for “induction” and “verbal reasoning test”. ( 2 marks)

d) Discuss the usefulness (quality) of the model. (2 marks)

e) Discuss one major concern with this study. (1 mark)

Question B4: Monitoring the Impact of Interventions (10 marks)

A team of HR Consultants were recruited for an organisation experiencing high absenteeism levels (higher than the industry average). These consultants believed the increase in absenteeism was linked to the declining fitness of their employees. In order to reduce absenteeism, the consultants implemented a fitness program where employees exercised during their lunch hour. To evaluate the program’s effectiveness, 50 participants were randomly sampled and the number of absent days were recorded for each participant in the 12 months before, and again after, the program began. The data were analysed using a repeated measures ANOVA with age differences included (0=under 30 years old, 1=30 years and older). See the R output below. Use a 5% significance (alpha) level.

a) Has the fitness program been successful? Fully discuss the results and refer to appropriate R output. (Assume the test assumptions have been met). (6 marks)

b) Draw an overall conclusion and provide one recommendation based on the results. (4 marks)

Note: the Test for sphericity was not applied as there is only two time points in the data.

Marginal Means

Means for time

Means for age groups

Means time 1 (0=under 30, 1=30+)

Means time 2 (0=under 30, 1=30+)


B5: Employee Attitudes and Engagement (10 marks)

A HR manager administered a Pulse survey to staff within the organisation. Employee engagement (EE) and job satisfaction (JS) were included on the survey. The HR manager wanted to compare both the department type (sales or information technology) and job level (1=administrative staff, 2= customer service staff, 3= team leaders, 4= managers, 5=senior managers) in relation to JS and EE. Below are the results. Fully discuss the results and in particular whether there are significant differences between departments and between job levels (refer to relevant statistics) in relation to employee engagement and job satisfaction. Use a 5% significance (alpha) level. (10 marks)

Comparing Departments (Sales and IT)

Means

Independent samples ttest for Job Satisfaction

Independent samples ttest for Engagement

Comparing Job Levels

Descriptive statistics

Oneway ANOVA for Job Satisfaction


Oneway ANOVA for Engagement




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