À propos de ce cours
4.5
2,515 notes
442 avis
Spécialisation
100 % en ligne

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Heures pour terminer

Approx. 10 heures pour terminer

Recommandé : 4 weeks of study, 1-2 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais, Chinois (simplifié)

Compétences que vous acquerrez

Talent ManagementAnalyticsPerformance ManagementCollaboration
Spécialisation
100 % en ligne

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.
Heures pour terminer

Approx. 10 heures pour terminer

Recommandé : 4 weeks of study, 1-2 hours/week...
Langues disponibles

Anglais

Sous-titres : Anglais, Chinois (simplifié)

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
Heures pour terminer
2 heures pour terminer

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....
Reading
11 videos (Total 83 min), 2 lectures, 1 quiz
Video11 vidéos
Goals for the Course1 min
Course Outline and Overview3 min
People Analytics in Practice4 min
Performance Evaluation: the Challenge of Noisy Data6 min
Chance vs. Skill: the NFL Draft22 min
Finding Persistence: Regression to the Mean11 min
Extrapolating from Small Samples5 min
The Wisdom of Crowds: Signal Independence5 min
Process vs. Outcome7 min
Summary of Performance Evaluation3 min
Reading2 lectures
Performance Analytics Slides PDF10 min
People Analytics in Action: Additional Reading10 min
Quiz1 exercice pour s'entraîner
Performance Evaluation Quiz20 min
Semaine
2
Heures pour terminer
2 heures pour terminer

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. ...
Reading
12 videos (Total 73 min), 2 lectures, 1 quiz
Video12 vidéos
Staffing Analytics Overview2 min
Hiring 1: Predicting Performance8 min
Hiring 2: Fine-tuning Predictors9 min
Hiring 3: Using Data Analysis to Predict Performance7 min
Internal Mobility 1: Analyzing Promotibility4 min
Internal Mobility 2: Optimizing Movement within the Organization8 min
Causality 15 min
Causality 26 min
Attrition: Understanding and Reducing Turnover10 min
Turnover: Predicting Attrition7 min
Staffing Analytics Conclusion min
Reading2 lectures
Staffing Analytics Slides PDF10 min
Staffing Analytics in Action: Additional Reading10 min
Quiz1 exercice pour s'entraîner
Staffing Quiz20 min
Semaine
3
Heures pour terminer
2 heures pour terminer

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. ...
Reading
7 videos (Total 75 min), 2 lectures, 1 quiz
Video7 vidéos
Basics of Collaboration5 min
Describing Collaboration Networks14 min
Mapping Collaboration Networks16 min
Evaluating Collaboration Networks10 min
Measuring Outcomes9 min
Intervening in Collaboration Networks18 min
Reading2 lectures
Collaboration Slides PDF10 min
Collaboration Research in Action: Additional Readings10 min
Quiz1 exercice pour s'entraîner
Collaboration Quiz20 min
Semaine
4
Heures pour terminer
2 heures pour terminer

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....
Reading
9 videos (Total 85 min), 2 lectures, 1 quiz
Video9 vidéos
Interdependence6 min
Self-fulfilling Prophecies9 min
Reverse Causality4 min
Special Topics: Tests and Algorithms5 min
Prescriptions: Navigating the Challenges of Talent Analytics15 min
Course Conclusion: Organizational Challenges 110 min
Course Conclusion: Organizational Challenges 2 and Future Directions19 min
Goodbye and Good Luck! min
Reading2 lectures
Talent Analytics and Conclusion Slides PDF10 min
Talent Management in Action: Additional Readings10 min
Quiz1 exercice pour s'entraîner
Talent Management Quiz20 min
4.5
442 avisChevron Right
Orientation de carrière

33%

a commencé une nouvelle carrière après avoir terminé ces cours
Avantage de carrière

83%

a bénéficié d'un avantage concret dans sa carrière grâce à ce cours
Promotion de carrière

13%

a obtenu une augmentation de salaire ou une promotion

Meilleurs avis

par PNJul 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.

par STMar 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!

Enseignants

Avatar

Cade Massey

Practice Professor
The Wharton School
Avatar

Martine Haas

Associate Professor of Management
The Wharton School
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Matthew Bidwell

Associate Professor of Management
The Wharton School

À propos de 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. ...

À propos de la Spécialisation Business Analytics

This Specialization provides an introduction to big data analytics for all business professionals, including those with no prior analytics experience. You’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, and you’ll develop basic data literacy and an analytic mindset that will help you make strategic decisions based on data. In the final Capstone Project, you’ll apply your skills to interpret a real-world data set and make appropriate business strategy recommendations....
Business Analytics

Foire Aux Questions

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