Career Focus

This course will help you become a more effective general manager by using data to improve employee-related decisions and practices.

Educational Objectives

The goal is for you improve your ability to manage people, whatever your formal role, by analyzing data and using the process and results to help solve organizational challenges. To accomplish this goal, we will do hands-on data analysis throughout the course.
The two-hour weekly format of the course will allow us to mix different activities, including traditional case discussions, analyses of case data, lab workshops, fireside chats with industry guests, and experiential simulations.

• We will use the statistical program R as our primary data tool, with starter code to help people move up the learning curve (or build your skills from a more advanced starting point). See below for details.
• You are not required to have a background related to data analyses or statistics to take this course (though if you have experience it will help). The first module will provide a foundation in analyzing data that we will then build on throughout the semester.
• We will try out tools and techniques to reveal the opportunities, limits, and tensions of using data to manage people more effectively, while increasing your data fluency in the process.

Course Content

Think about the digital tools you use to do your work (and live your life), and the trail of data you leave behind as you do so. Just as digital data revolutionized consumer analytics and other domains, it is now transforming how companies use employee data. Many companies now analyze data in new ways to inform decisions throughout the employee life cycle, such as using predictive algorithms to guide hiring, promotion, and compensation decisions. Leading companies are starting to use day-to-day streams of digital trace data to try to improve productivity, collaboration, and employee well-being, among other outcomes.
Given these trends, 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 rise of remote and hybrid work has only fueled the collection of employee data to guide these arrangements.
The course is organized around four modules:

• Foundations of Analytics. We will introduce key statistical concepts and techniques to build the skills necessary to turn data into actionable insights. 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.

• Managing with Analytics. Using the foundational skills developed in the first module, we will address a variety of people-related business challenges, such as performance management, promotion decisions, and employee engagement, in a range of company situations. Students will learn how companies are 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, analytic techniques, and related tools for using data to drive organizational change.

• Team and Network Analytics. As the traditional organization chart becomes less representative of the way work actually gets done, especially with the challenges of remote work amplified by the pandemic, organizations are turning to a variety of tools and practices to collaborate through networks and teams. We will use network analyses to reveal and improve collaboration patterns, and test new technologies to gain insight into group dynamics and communication effectiveness.

• New Frontiers in People Analytics. What data are you automatically generating as you go about your work? What additional data could you purposefully gather about yourself that might be helpful? We will discuss and debate different ways to use new tools and data to become more effective. How are others, including your employer, using the data you generate to accomplish their goals, either with or without your knowledge or consent? As leaders, this module will help you think clearly about the tradeoffs and dilemmas involved in using employee data to help individuals develop while driving organizational performance. Issues of privacy, control, and ethics will be front and center.

A note on statistics and code: We will use the statistical program R as our primary tool in the course (though we will also gain exposure to other programs and tools along the way). No previous experience with code is required; the beginning of the course is designed to give students a foundation for using R and statistics to inform specific organizational decisions and problems. Each case that includes a dataset will also include R "starter code", which provides scaffolding to help you learn how to analyze data and apply the results.

If you have experience with R and statistics, you will have ample opportunity to continue to develop your skills, as most datasets lend themselves to a variety of analytic techniques. For everyone, it will be imperative to come to class with a learning orientation so we can all improve together, and enjoy doing so. We will focus on learning -- and applying -- practical analytic techniques that organizations use most frequently.

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

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