Syllabus

Title
5959 Global Human Capital Analytics
Instructors
Assoz.Prof Kyle Ehrhardt, Ph.D.
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/14/23 to 02/28/23
Registration via LPIS
Notes to the course
Subject(s) Master Programs
Dates
Day Date Time Room
Tuesday 05/02/23 02:00 PM - 05:30 PM LC.-1.038
Thursday 05/04/23 02:00 PM - 05:30 PM LC.2.064 PC Raum
Tuesday 05/09/23 02:00 PM - 05:30 PM LC.-1.038
Thursday 05/11/23 02:00 PM - 05:30 PM LC.2.064 PC Raum
Monday 05/15/23 02:00 PM - 04:00 PM LC.-1.038
Wednesday 05/17/23 02:00 PM - 05:30 PM LC.-1.038
Thursday 05/25/23 03:00 PM - 06:00 PM TC.3.02
Contents

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:

  • Identify and describe the central aspects of the strategic approach to HR.
  • Demonstrate an improved understanding of methodologies for analyzing data.
  • Analyze data to aid various HR functions.
  • Use the skills and tools you learned in this course to make accurate data driven decisions.
  • Demonstrate improved research and critical thinking skills.
Attendance requirements

This course is to be held in person on campus. Regular attendance is a requirement to complete this course. Please note that absences may negatively impact your participation grade. Aligned with WU guidelines for PI courses, students not meeting the university’s attendance requirement (attending at least 80% of the time) may be de-registered from the course. Please also note that the final class meeting date will include an exam.

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 regularly work hands-on with data, giving you an opportunity to develop your analytic skills and gain experience in using data to make strategic HR decisions. The course will additionally include an exam, which will cover core course concepts and test your ability to analyze data using statistical methods and interpret the results.

 

Assessment

Assessment will be based on both individual and team performance. Below is a summary with point values for each component:

 

Participation.................................... 50 points (25.0% of total grade)

Analytic Assignment #1................... 45 points (22.5% of total grade)

Analytic Assignment #2................... 65 points (32.5% of total grade)

Exam............................................... 40 points (20.0% of total grade)

Total:............................................... 200 points

 

Please note that successful participation involves thoughtfully contributing to class discussion, engaging in thoughtful analysis of any cases, actively participating in class activities, and synthesizing across readings. You are expected to have read in advance any assigned readings and cases and be prepared to discuss them.

 

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

 

Grading Key:

 

1 = 90.00-100%    

2 = 80.00-89.99% 

3 = 70.00-79.99% 

4 = 60.00-69.99%

5 < 60.00%                                                                                                   

Prerequisites for participation and waiting lists

READINGS

Required Text

Author: Edwards, M., & Edwards, K.

Title: Predictive HR Analytics: Mastering the HR Metric

Publisher: KoganPage

Edition: 2nd

Year: 2019

Remarks: The book is available as an e-book through the WU Library

Content Relevant for Class Examination: Yes.

Recommendation: Essential reading for all students.

Type: Book.

 

Other Required Readings

Any other required readings (e.g., articles, short cases, etc.) will be made available to students.

 

Optional Text:

Author: Nell, P.C.

Title: Analyzing Data for Business Decisions: A Concise Guide for Novices

Year: 2022

Remarks: The book is a short data analytics guide authored by a WU chaired professor. It is written with a target audience of managers and management students in mind.

Recommendation: Especially if students have little or no prior experience with data analytics, you may find this book to be a useful supplement to the required text and topics that we will cover in class.

Type: Book. You may find a table of contents at this website: https://www.amazon.de/-/en/Prof-Dr-Phillip-C-Nell/dp/B09S67NNSP/ref=tmm_pap_swatch_0?_encoding=UTF8&qid=&sr=.

Readings

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

Recommended previous knowledge and skills

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

Availability of lecturer(s)

Kyle Ehrhardt, Ph.D.

Lecturer – Department of Global Business and Trade

Office: TBD – I will provide this information at the start of the course.

 

I am available for individual meetings by appointment. Please email to set up an appointment using the contact information provided above. Alternatively, you may also reach me by email at kyle.ehrhardt@ucdenver.edu. I would recommend using this alternative “ucdenver” email if you would like to reach me before the start of the Summer 2023 semester.

 

I will be teaching this course while visiting WU during the Summer 2023 semester, and more specifically, during May 2023. My “home” university is the University of Colorado Denver in the United States, where I am on the faculty of Management in the Business School. You can find more information about my background and interests on my University of Colorado Denver faculty profile: https://business.ucdenver.edu/about/our-people/kyle-p-ehrhardt.

Last edited: 2023-01-17



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