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The Water Cooler

A blog of fresh ideas and findings from organizational leaders and researchers on how they’re making work better, shared regularly.

HR Information Systems 2.0: Integrating People Analytics

Filed under: People Analytics
HR Information Systems 2.0: Integrating People Analytics
How Human Resource Information Systems (HRIS) is taught hasn’t changed much in decades while workplaces have undergone a technological and data revolution. To prepare future business leaders, we have the opportunity to rethink how business schools teach and leverage HRIS.

In 2016, we set out to transform a course for human resource management (HRM) undergraduate students at Portland State University. The course was Human Resource Information Systems, a staple at business schools everywhere, which hadn’t changed much in the 25 years since Talya took it herself as a student.

Our goal was to re-envision what this class could be. The first step was to rename it to signal the changes in store so we decided to call the course “HRIS & People Analytics.” We chose this course because understanding HRIS, including data management, integration, and storage, is a key part of effective people analytics. To build students’ competence in people analytics, we developed lectures, activities, and assignments that required students to apply their knowledge of psychological theory, business, communication, ethics, and employment law to solve problems and to answer questions using data. Each class meeting was divided into two components:

  1. A lecture on key concepts
  2. A hands-on data management, analysis, and visualization activity using the open-source (and free!) statistical software package R (learn more about using R)

As a major component of the course, students completed an in-depth case on a fictitious company with simulated datasets as part of a team. In one scenario, students read about the company’s training initiative for online customer service representatives. Students received a dataset that included pre- and post-training assessment scores for trained and untrained employees. It was up to the student teams to analyze the data and determine whether the training had an effect.

The project resulted in an extensive report and portfolio that students could take with them on the job market. The feedback from students has been strong and their enthusiasm has encouraged us to continue to offer the course multiple times each year as well as expanding the offering to MBA students in our Data Analytics program.

Some key lessons learned include:

  • Context matters. Our HRM students take statistics courses as part of their undergraduate business degree. Statistics courses provide students with a foundation in statistical concepts but often lack key connections to business and HR examples. Students tell us that our course brings statistical concepts to life through real-world scenarios and cases, hands-on data management, analysis, and visualization exercises.

  • A lot can be learned in a single term. Throughout the 11-week term, students learn and practice multiple techniques for managing, analyzing, and visualizing data. They learn the basics of the R program, which involves writing scripts using object-oriented programming language. At first, many students are daunted and intimidated, but by the end of the term, students – many of whom had limited or zero programming experience – are writing and annotating R scripts and interpreting R statistical output in front of the class.

  • Provide opportunities for practice. For each topic and technique, we provide students with at least three opportunities to practice: once in class, once on a small homework assignment, and once for their final project. At each practice opportunity, we introduce additional complexities in the datasets that they might encounter in the real world.

  • Focus on ethical and legal issues. Our mantra throughout the class is: “Just because you can, should you?” Talya’s own work on a National Science Foundation cyber-security grant with Donald Truxillo and Mark Jones addresses potential privacy tradeoffs in balancing convenience and privacy compliance. There are already too many real examples where HR processes have lead to ethical and privacy concerns. In one case, we discuss potential privacy concerns associated with scanning or “scraping” social media websites for applicant or employee data.

Talya Bauer is the Cameron Professor of Management at the Portland State University School of Business Administration and has written for re:Work about “Connections, onboarding, and the need to belong.” David Caughlin is an Instructor of Management at the Portland State University School of Business Administration.

This blog is the part of a series from business school professors who are pushing the study and teaching of human resources forward by employing data, science, and analytics in their curricula. Read more from the series here: