2080 Global Human Capital Analytics
Assoz.Prof Priv.Doz.Dr. Mihaela Dimitrova
Contact details
Weekly hours
Language of instruction
09/21/22 to 09/26/22
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Day Date Time Room
Monday 10/03/22 02:00 PM - 05:00 PM LC.-1.038
Monday 10/17/22 02:00 PM - 05:30 PM LC.2.064 PC Raum
Monday 10/31/22 02:00 PM - 05:30 PM LC.2.064 PC Raum
Monday 11/07/22 02:30 PM - 06:00 PM LC.2.064 PC Raum
Monday 11/14/22 02:00 PM - 05:30 PM LC.-1.038
Monday 11/28/22 02:00 PM - 06:00 PM LC.2.064 PC Raum

As more and more organizations continue to expand globally, the need to manage and sustain a global workforce has become vital. Increased digitization and technological advancements have made it possible to have a data-driven approach to making strategic decisions regarding multinational organizations’ human resources. This course will introduce you to global HR strategic planning and will explore methods and tools used to make data-driven decisions about recruiting, selecting, developing, evaluating, and retaining employees.

Learning outcomes

Upon successful completion of this course, you will be able to:

  1.       Identify and describe the central aspects of the strategic approach to HR.

  2.       Demonstrate an improved understanding of methodologies for analyzing data.

  3.       Analyze data to aid various HR functions.

  4.       Use the skills and tools you learned in this course to make accurate data-driven decisions.

  5.       Demonstrate improved research, critical thinking, teamwork, and presentation skills.


Attendance requirements

This course is to be held in person on campus. In case of disruptions due to the pandemic, the sessions will be held virtually in real time. As you are expected to attend the class in-person, it is NOT possible to attend this course remotely.

Regular attendance is a requirement to pass this course. Please note that any absences will negatively impact your participation grade. You will fail the course if you are absent for more than 20% of the total course time. Attendance of the first session is mandatory. In case of online classes, your computer cameras must be switched on.

Teaching/learning method(s)

The sessions are designed in a way to maximize your learning by balancing between lecture and your involvement in discussions, cases,and exercises. You will also participate in a hands-on team project, which will give you an opportunity to develop your analytical skills and gain experience in using data to make strategic HR decisions. As part of an individual research report, you will also have the chance to explore in depth an area of HR analytics that is of interest to you. The course will end with a comprehensive final exam that will test your ability to analyze data using statistical methods and interpret the results.


Assessment will be based on both individual and team performance. Breakdown of assignments with percent of total grade:

  1. Individual final exam: 20% of total grade
  2. One individual written research report: 30% of total grade
  3. Team project presentation (final grade partially depends on peer evaluations): 30% of total grade
  4. Participation: 20% of total grade

Please note that successful participation involves thoughtfully contributing to the discussion by answering questions, engaging in a thoughtful analysis of the discussed cases, building on other students’ ideas, actively participating in activities, and synthesizing across readings and discussions. You are expected to have read in advance all the required reading materials and cases and be prepared to discuss them.

More information on assignments and required course readings will be provided on the course website at the start of the course.

Grading key:

90-100% = 1

80-89% = 2

70-79% = 3

60 - 69% = 4

Below 60% = 5

1 Author: Martin Edwards & Kirsten Edwards

Predictive HR Analytics, mastering the HR metric

Publisher: KoganPage
Edition: Second Edition
Remarks: The book is available as an e-book through the WU library
Year: 2019
Content relevant for class examination: Yes
Recommendation: Essential reading for all students
Type: Book
Recommended previous knowledge and skills

Prior knowledge of human resource management and basic statistics is helpful but not necessary.

Availability of lecturer(s)

Mihaela Dimitrova, PhD

Department of Global Business and Trade

Office: D1 3.032

I am available for individual meetings by appointment, e-mail address:

Last edited: 2022-05-02