специализация Business Analytics
Make Data-Driven Business Decisions. Achieve fluency in business data strategies in four discipline-specific courses.
специализация Business Analytics
5 coursesUniversity of Pennsylvania
People analytics is a data-driven approach to managing people at work. For the first time in history, business leaders can make decisions about their people based on deep analysis of data rather than the traditional methods of personal relationships, decision making based on experience, and risk avoidance. In this brand new course, three of Wharton’s top professors, all pioneers in the field of people analytics, will explore the state-of-the-art techniques used to recruit and retain great people, and demonstrate how these techniques are used at cutting-edge companies. They’ll explain how data and sophisticated analysis is brought to bear on people-related issues, such as recruiting, performance evaluation, leadership, hiring and promotion, job design, compensation, and collaboration. This course is an introduction to the theory of people analytics, and is not intended to prepare learners to perform complex talent management data analysis. By the end of this course, you’ll understand how and when hard data is used to make soft-skill decisions about hiring and talent development, so that you can position yourself as a strategic partner in your company’s talent management decisions. This course is intended to introduced you to Organizations flourish when the people who work in them flourish. Analytics can help make both happen. This course in People Analytics is designed to help you flourish in your career, too.
Приобретаемые навыки
Performance ManagementTalent ManagementData AnalysisHuman Resources
Syllabus - What you will learn from this course
1
Section
Introduction to People Analytics, and Performance Evaluation
In this module, you'll meet Professors Massey, Bidwell, and Haas, cover the structore and scope of the course, and dive into the first topic: Performance Evaluation. Performance evaluation plays an influential role in our work lives, whether it is used to reward or punish and/or to gather feedback. Yet its fundamental challenge is that the measures we used to evaluate performance are imperfect: we can't infer how hard or smart an employee is working based solely on outcomes. In this module, you’ll learn the four key issues in measuring performance: regression to the mean, sample size, signal independence, and process vs. outcome, and see them at work in current companies, including an extended example from the NFL. By the end of this module, you’ll understand how to separate skill from luck and learn to read noisy performance measures, so that you can go into your next performance evaluation sensitive to the role of chance, knowing your environment, and aware of the four most common biases, so that you can make more informed data-driven decisions about your company's most valuable asset: its employees.
11 videos (Total 83 min), 2 readings, 1 quiz
11 videos
Goals for the Course1m
Course Outline and Overview3m
People Analytics in Practice4m
Performance Evaluation: the Challenge of Noisy Data6m
Chance vs. Skill: the NFL Draft22m
Finding Persistence: Regression to the Mean11m
Extrapolating from Small Samples5m
The Wisdom of Crowds: Signal Independence5m
Process vs. Outcome7m
Summary of Performance Evaluation3m
2 readings
Performance Analytics Slides PDF10m
People Analytics in Action: Additional Reading10m
1 practice exercises
Performance Evaluation Quiz20m
2
Section
Staffing
In this module, you'll learn how to use data to better analyze the key components of the staffing cycle: hiring, internal mobility and career development, and attrition. You'll explore different analytic approaches to predicting performance for hiring and for optimizing internal mobility, to understanding and reducing turnover, and to predicting attrition. You'll also learn the critical skill of understanding causality so that you can avoid using data incorrectly. By the end of this module, you'll be able to use data to improve the quality of the decisions you make in getting the right people into the right jobs and helping them stay there, to benefit not only your organization but also employee's individual careers.
12 videos (Total 73 min), 2 readings, 1 quiz
12 videos
Staffing Analytics Overview2m
Hiring 1: Predicting Performance8m
Hiring 2: Fine-tuning Predictors9m
Hiring 3: Using Data Analysis to Predict Performance7m
Internal Mobility 1: Analyzing Promotibility4m
Internal Mobility 2: Optimizing Movement within the Organization8m
Causality 15m
Causality 26m
Attrition: Understanding and Reducing Turnover10m
Turnover: Predicting Attrition7m
Staffing Analytics Conclusion0m
2 readings
Staffing Analytics Slides PDF10m
Staffing Analytics in Action: Additional Reading10m
1 practice exercises
Staffing Quiz20m
3
Section
Collaboration
In this module, you'll learn the basic principles behind using people analytics to improve collaboration between employees inside an organization so they can work together more successfully. You'll explore how data is used to describe, map, and evaluate collaboration networks, as well as how to intervene in collaboration networks to improve collaboration using examples from real-world companies. By the end of this module, you'll know how to deploy the tools and techniques of organizational network analysis to understand and improve collaboration patterns inside your organization to make your organization, and the people working within in it, more productive, effective, and successful.
7 videos (Total 75 min), 2 readings, 1 quiz
7 videos
Basics of Collaboration5m
Describing Collaboration Networks14m
Mapping Collaboration Networks16m
Evaluating Collaboration Networks10m
Measuring Outcomes9m
Intervening in Collaboration Networks18m
2 readings
Collaboration Slides PDF10m
Collaboration Research in Action: Additional Readings10m
1 practice exercises
Collaboration Quiz20m
4
Section
Talent Management and Future Directions
In this module, you explore talent analytics: how data may be used in talent assessment and development to maximize employee ability. You'll learn how to use data to move from performance evaluation to a more deeper analysis of employee evaluation so that you may be able to improve the both the effectiveness and the equitability of the promotion process at your firm. By the end of this module, you'll will understand the four major challenges of talent analytics: context, interdependence, self-fulfilling prophecies, and reverse causality, the challenges of working with algorithms, and some practical tips for incorporating data sensitively, fairly, and effectively into your own talent assessment and development processes to make your employees and your organization more successful. In the course conclusion, you'll also learn the current challenges and future directions of the field of people analytics, so that you may begin putting employee data to work in a ways that are smarter, practical and more powerful.
9 videos (Total 85 min), 2 readings, 1 quiz
9 videos
Interdependence6m
Self-fulfilling Prophecies9m
Reverse Causality4m
Special Topics: Tests and Algorithms5m
Prescriptions: Navigating the Challenges of Talent Analytics15m
Course Conclusion: Organizational Challenges 110m
Course Conclusion: Organizational Challenges 2 and Future Directions19m
Goodbye and Good Luck!0m
2 readings
Talent Analytics and Conclusion Slides PDF10m
Talent Management in Action: Additional Readings10m
1 practice exercises
Talent Management Quiz20m
4.5
33%
83%
13%
Top Reviews
By PN•Jul 28th 2017
This is a very well defined course to give a very good start to the knowledge of People Analytics. The professors have brought in numerous examples to make the understanding of analytics better.
By ST•Mar 18th 2017
Real helpful course especially for individuals who are in HR field or interested in becoming a better leaders, team players. Professors incorporated data analytics into human talent management!
Instructors
Cade Massey
Practice Professor
Martine Haas
Associate Professor of Management
Matthew Bidwell
Associate Professor of ManagementAbout University of Pennsylvania
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
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