People Analytics - Harvard Business School MBA Program

People Analytics

Course Number 2028

Professor Jeffrey T. Polzer
Spring; Q3Q4; 3 credits
28 sessions
Option of paper or exam

Career Focus

People Analytics is designed to help students use data — and manage others who use data — to improve people-related decisions and practices in their role as a general manager. Students in most jobs, organizations, and industries will need enough data fluency to be a competent consumer of analyses of employee data, which is rapidly becoming part of the analytics revolution. The best way to achieve this goal is to build hands-on skills by analyzing and interpreting data in ways that complement the frameworks and intuitions that normally guide managerial actions. At a deeper level, students will sharpen their ability to think critically through the lens of rigorous analytics.

Educational Objectives

This course will equip students with an analytic approach to diagnosing the varied forces that influence individual, team, and organizational performance, leading to more effective interventions and actions. Students are not required to have a background related to data analyses or statistics to take this course. The first module will provide a foundation in using and statistically analyzing data that we will then build on throughout the course.

The goal is not to turn students into data scientists, but instead to help them gain an analytic advantage, whatever their formal role. Direct experience analyzing data will help students achieve this goal. While developing analytic skills and trying out tools and techniques, students will come to appreciate the opportunities, limits, and tensions involved in using data analytics to inform people issues, while simultaneously gaining deeper insight into the substance of the business issues in question.

Course Content

Starting in their first job after HBS, many students will have at their fingertips a profusion of new technologies capable of generating data about the people they manage, and themselves. This trend will accelerate in coming years, making it possible for analytic approaches to inform (or even perform) many management activities. Students will need to decide whether and how to gather and use such data, ignoring it at their peril as others amplify their efforts to use it to their advantage.

Given these trends, the premise of the course is that effective leaders must understand how data can be used (and misused) to leverage people’s skills, talents, and insights. This premise is at the heart of the rapidly emerging field of people analytics, which organizations are embracing as they use data to help manage and develop employees.

The course is organized around five modules:

  • Module 1: Foundations of Analytics. We will introduce key statistical concepts and techniques to build foundational skills that are necessary to turn data into actionable insights. To do so, we will use cases that include datasets to be analyzed by students as part of their preparation. Our goal will be to create a community for individual and collective learning, helping everyone gain skills from their own starting point.
  • Module 2: Managing with Analytics. Using the foundational skills developed in the first module, we will address a variety of people-related business problems, such as performance management and employee engagement, in a range of company situations. Students will learn how companies are rapidly experimenting with new technologies and practices for engaging employees, organizing their work, and measuring their activities. This module will give students exposure to principles of data visualization, machine learning, and related tools for using data to drive organizational change.
  • Module 3: Team and Collaboration Analytics. As the traditional organization chart becomes less representative of the way work actually gets done, organizations are turning to a variety of tools and practices to collaborate through networks and teams. Include a module focusing on collaboration and team analytics. We will use network analyses to study organizational collaboration patterns (including the common problem of collaborative overload), and test new technologies to gain insight into group dynamics and communication effectiveness.
  • Module 4: The Quantified Self: Using Your Own Data for Self-Improvement. What data are you automatically generating as you go about your work (and your life)? What additional data could you purposefully gather about yourself that might be helpful? We will discuss and debate different ways to use feedback from your own data to become more effective.
  • Module 5: Privacy, Control, and the Future of Work. How are others, including your employer, using the data you generate to accomplish their goals, either with or without your knowledge or consent? We will discuss case examples of these issues with the goal of becoming more knowledgeable and effective in managing and using the data we generate. As leaders, this module will help you think clearly about the tradeoffs and dilemmas involved in using various sources of employee data to help individuals develop while driving organizational performance.

Please email Professor Jeff Polzer directly with any questions: jpolzer@hbs.edu