People Analytics: Prediction of Performance & Prescription of Policy

2021/2022

Academic Year

ENG

Instruction in English

4

ECTS credits

Delivered at:

International laboratory for Applied Network Research

Course type:

Elective course

When:

2 year, 1, 2 module

Course Syllabus

Abstract

The focus of this course, which is based on practical approaches, is on effective People Analytics and how companies can create business value from their Big Data assets. Mainly, the course outlines how to inject data analytics at every stage of the talent management process, from talent acquisition through retention. Throughout the course, seven stages of People Analytics Success in the context of Big Data will be considered, providing examples for each stage to help illustrate the key concepts to effective People Analytics.

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

• 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

• Workforce Planning Analytics
• Employee Wellness, Health, and Safety 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
• Introduction to People Analytics

Assessment Elements

• 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.
• Exam in the LMS
  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
• Team-based project “How the components of human capital affect applicants’ salary expectations”
  The team-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 LMS not later than the deadline agreed at the beginning of the course and set at LMS. No grades will be given if files are not uploaded at LMS. The paper should include the following parts: 1. Introduction with a description of the sample (age groups, education, etc.). 2. Problem statement and description of people analytics for this purpose. 3. Short description of statistical analysis methods. 4. Results and 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. The group should be no more than four members.

Interim Assessment

• 2021/2022 2nd module
  0.3 * Exam in the LMS + 0.35 * Class activities + 0.35 * Team-based project “How the components of human capital affect applicants’ salary expectations”

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