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Regular version of the site

People Analytics: Prediction of Performance & Prescription of Policy

2021/2022
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Elective course
When:
2 year, 1, 2 module

Instructor

Course Syllabus

Abstract

This practice-oriented course focuses on effective People Analytics as a source of business value creation in the context of Big data. The core objective is to explore how to efficiently integrate data analytical approaches to each stage of the talent management process, from talent acquisition to talent retention. Throughout the course, examples for each People Analytics Success stage will be provided to help illustrate the key concepts to effective HRM.
Learning Objectives

Learning Objectives

  • Develop high-impact People Analytics in order to generate business value from the Big Data and little data available to the organization.
  • Identify types of people analytics used in a company.
  • Obtain valuable people analytics to improve the efficiency of workforce planning, hiring, placing and retaining the best employees.
  • Choose relevant data science methods for specific problems in human resource (HR) management.
  • Analyze outcomes of HR practices and identify their effects on both the staff members’ attitudes toward the company and the organizational performance.
  • Explain how data-driven decision-making affects organizational performance and HR practices.
Expected Learning Outcomes

Expected Learning Outcomes

  • Able to choose tools, modern technical means and information technologies to process information for the assigned scientific task in management
  • Able to develop his/her intellectual and cultural level, build a trajectory of career development
  • Able to identify the data required for the solution of research tasks in management; to gather data from both the field research and desk research as well as from the social and economic sources
  • Able to prepare and manage the consultancy project.
  • Able to present the results of the study in various forms, such as a report, an article or a presentation.
  • Able to reflect (evaluate and process) obtained scientific and work methods
  • Able to self-study of new research methods, change the scientific and professional profile in his/her practical activities
  • Able to work out the organizational development programs and put them into practice.
Course Contents

Course Contents

  • Introduction to People Analytics
  • Workforce Planning Analytics
  • Sourcing Analytics
  • Talen Acquisition Analytics
  • Analytics for Onboarding and Organizational Culture Fit
  • Employee Engagement Analytics
  • Employee Life Time Value and Cost Modeling
  • Retention Analytics
  • Employee Wellness, Health, and Safety Analytics.
Assessment Elements

Assessment Elements

  • non-blocking Individual-based project “Examining the role of talent management practices using fsQCA"
    The individual-based project includes two parts: 10-page paper (50% in grading) and presentation in the class (50% in grading). Both files must be uploaded at Ms Teams not later than the deadline agreed at the beginning of the course and set at Teams. No grades will be given if files are not uploaded. The paper should include the following parts: 1. Introduction with a problem statement (research motivation and research question) 2. Brief review and analysis of academic literature, proposition development. 3. Methodology: Sample description, data collection approach, short description of the statistical analysis method(s). 4. Findings and theoretical/practical implications. 5. Conclusions References. The paper should be single-spaced throughout; Times New Roman 12-point font (except for the title page); A4 size page formatting; 2.5 cm margins on all sides.
  • non-blocking Class activities
    (1) Kahoot game. At the beginning or at the end of some lectures a 15-minute Kahoot game is conducted. If the student missed the class, there is no option to participate in this activity. (2) Individual assignment during seminars. At the beginning or at the end of some seminars students will get a written task for 10-15 min based on their home reading or materials discussed during the previous classes. If the student missed the class, there is no option to rewrite this task, except for sickness absence. In this case, the student should notify the instructor about his/her sick leave.
  • non-blocking Exam in the Ms Teams
    The exam consists of 22 test questions (up to 2 marks for each positive answer), 2 open questions with the explanation of your ideas (up to 3 marks for each positive answer), and one practical exercise (up to 4 marks). No negative marks for wrong answers. Total time: 60 min. Total questions: 25
  • non-blocking Coursera course "Qualitative Comparative Analysis (QCA)"
    All students are required to take the Coursera course "Qualitative Comparative Analysis (QCA" , https://www.coursera.org/learn/qualitative-comparative-analysis?
Interim Assessment

Interim Assessment

  • 2021/2022 1st module
  • 2021/2022 2nd module
    0.3 * Class activities + 0.3 * Exam in the Ms Teams + 0.4 * Individual-based project “Examining the role of talent management practices using fsQCA"
Bibliography

Bibliography

Recommended Core Bibliography

  • Isson, J. P., & Harriott, J. (2016). People Analytics in the Era of Big Data : Changing the Way You Attract, Acquire, Develop, and Retain Talent (Vol. 1). Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1226538

Recommended Additional Bibliography

  • Edwards, M. R., & Edwards, K. (2019). Predictive HR Analytics : Mastering the HR Metric (Vol. 2nd Edition). New York: Kogan Page. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2037089
  • Fitz-enz, J., & Mattox, J. (2014). Predictive Analytics for Human Resources. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=812792