How to Apply
Learn about the admissions process and requirements to apply.
Learn how to optimize overall workplace success using data to interpret trends and predict outcomes related to people management. As part of the Rutgers Stackable Business Innovation Program (rSBI), the Human Capital Analytics Concentration is stackable with the following master's programs: Master of Information Technology and Analytics, MBA, and Master's in Human Resources.
Organizational success is largely driven by human capital. The Human Capital Analytics concentration equips students with data-driven decision-making skills to develop and evaluate high-impact people management interventions and practices. After completing the certificate, students will be skilled in analyzing data to interpret trends and predict outcomes related to people management, which facilitates change initiatives and enables the development of effective human resources practices, ultimately contributing to overall workforce success and organizational competitive advantage. Data analytics skills will be applied within the human resources context, optimizing practices and addressing challenges such as employee turnover, employee engagement, talent acquisition and management, legal compliance and discrimination, and performance management.
You can take the course listed below as individual classes or as stackable courses toward the completion of a concentration. This concentration requires four courses to be completed. Students have the option to choose between Business Data Management (22:198:603) OR Data Analytics and Visualization (22:544:646).
This course introduces students to the concepts of Human Resource Management metrics, analytics, and evidence-based management. Students learn to reexamine the scope of human resource management through a quantitative lens. Topics include costing and predicting turnover, ensuring diversity, equity and inclusion, valuing engagement and performance, and designing more effective selection and compensation systems.
This course introduces statistics as applied to managerial problems. Emphasis is placed on conceptual understanding as well as conducting statistical analyses. Students learn the limitations and potential of statistics, gain hands-on experience using Excel, as well as various statistical techniques such as sampling, inference, and regression.
This course provides students with an understanding of database technology and its application in managing data resources. The conceptual, logical, and physical design of databases will be analyzed. A database management system will be used as a vehicle for illustrating some of the concepts discussed in the course.
The course aims to develop critical business data presentation skills to ensure that visualizations add to the effective interpretation and explanation of the underlying data without undue strain to the consumer of the information. Students will learn how visualizations enable effective detection of trends that can be easily connected to real world events to help explain relationships and interrelationships, and how to use appropriate and minimal use of color to maximize its impact. The course will present a variety of data visualization methods, focusing on business data visualizations similar to those that appear in business publications. Finally, students will learn advanced techniques that will help them analyze big data including hundreds of variables. Software tools such as R and Tableau will be used for experiential learning.
This course focuses on identifying strategic Human Resource Management problems and creating data-driven approaches to find solutions. Students focus on designing and using surveys, collecting HR metrics and data, as well as developing skills necessary to inform a broad audience about evidence-based solutions. Topics include problem identification, data acquisition, data analysis, identifying best practices, project management, research ethics, and communicating research findings to a managerial audience.
The concentration and courses are offered by the Management Science & Information Systems Department
Sample Relevant Careers: Human Resources Professional, Human Resources Manager, Human Resources Generalist, Executives, Supervisors, Managers, Compensation Analysts, Recruiters, Data Scientist, Data Analyst, Data Engineer, Business Analyst, Business Intelligence Specialist, Quantitative Researcher, Statistician