760819 :HR Analytics

General info

Instruction language English
Type of Instruction Plenary lectures and compulsory tutorials (Lecture schedule)
Type of exams Written exam (Examination schedule)
Level:Master
Course load:6 or 3 ECTS credits depending on the programme, see below.
Registration:Enroll via COMAP.
Blackboard InfoLink to Blackboard (When you see 'Guest are not allowed in this course', please login at Blackboard itself)

Lecturer(s)


dr. S. Batistic (Coordinator)

E.M. Kunst MSc


Objectives

At the end of the course the student is able to:

  • Understand what academics and practitioners understand with HR analytics, its history and to reflect on future directions of this domain
  • Be able to calculate the cost of HR problems (e.g., absenteeism and turnover)
  • Be able to evaluate the strengths and weakness of various HR practices and/or interventions (e.g., the effects of leadership development practices on employee performance), with specific statistical methods (e.g., moderation and mediation, multiple regression), and packages (e.g., SPSS and PROCESS)
  • Be able to present and defend – “sell” the results of HR problems to top and line management (e.g., to be able to show the impact, weather beneficial of detrimental of various HR practices towards employee performance) and provide policy suggestions
  • Develop critical thinking and logic – how to develop testable models from theory and understand how such models can be tested (e.g., moderation and mediation, multiple regression), and what software can be used (e.g., SPSS and PROCESS)


Contents

A lot of organizations do not know the benefits and costs of the HR interventions they apply. When organizations proclaim that "People are our greatest assets", they are often not able to measure the value of the human capital and to calculate the benefits of investments on their employees. That's why this course is focused on helping future HR practitioners understand and apply the benefits of analytics in the organizational settings. This requires the measurement of HR practices, HR outcomes and the valuation of job performance and can help answer important questions like: What are good metrics for measuring HR activities and outcomes? What are the benefits of specific HR policies in terms of the growth of human capital? Are these policies profitable in the sense that the benefits are larger than the costs? Are investments in human capital similar to investments in physical capital? These and others similar questions are central to the HR analytics field and the analytical tools provide great support for evidence based management and it decision making process. As a consequence, in recent years, this subfield of Human Resource Studies has received a lot of attention amongst academics and in organizations.

More specifically, the course discusses the following topics:

  1. What is HR analytics and why is important
  2. The need for logic and analytics in metrics
  3. The financial consequences of HRM: evaluating absenteeism and turnover
  4. Predictors, prediction and predictive modelling
  5. How and what to present to support your case


Specifics

Type of Instruction:

5 lectures and 6 practicals.

Examination:

A practical individual exam at the end of the course (100%). The minimum grade to pass the exam is 6.0. The exam is composed of two parts: the analytical part (50%) and the report part of 2000 words (50%). The exam is scheduled in November and the re-sit date is to be communicated later on. The report part will be due seven days after the analytical part. The written analytical and report part concerns the content from the core readings, some background readings and the contents of the lectures and practicals.

Practicals:

The most important goal of this course is that you will be able to practically explore problem modern organizations face on daily basis and to provide management with possible solutions based on your learned critical and analytical skills. During weekly classes, you will learn to apply the relevant analytical skills with the help of exercises and cases. In order to practice, it is important that you bring a calculator and your laptop along.

As the practicals are the core of this course they are compulsory. You are allowed to miss one practical without notice. If you miss more than one practical, you will have to make an additional assignment in January 2018. In case of specific circumstances (e.g., serious illness) please contact the course coordinator and we will find a solution.


Compulsory Reading

  1. Edwards, M. & Edwards, K., Predictive HR Analytics: Mastering the HR Metrics, Pearson Education, 2016, ISBN 978-0749473914.
  2. Additional literature will be announced on Blackboard


Recommended Prerequisites

This course builds on theoretical (Human resource management and Organizational behavior) and statistical knowledge and skills already acquired from the bachelor or pre-master. We expect that you have refreshed your knowledge and related SPSS skills on the following topics: general research methods, ANOVA, t-tests, chi-square difference test, linear (multiple) regression analysis, logistical regression analysis, factor analyses, moderation and mediation analysis.


Compulsory for

  • MSc Human Resource Studies ( 2014: 3 ECTS, 2015: 3 ECTS, 2016: 3 ECTS, 2017: 6 ECTS )

(24-jul-2017)