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Английский

Субтитры: Английский, Китайский (упрощенное письмо)

Приобретаемые навыки

Talent ManagementAnalyticsPerformance ManagementCollaboration

Курс 3 из 5 в программе

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Английский

Субтитры: Английский, Китайский (упрощенное письмо)

Программа курса: что вы изучите

Неделя
1
2 ч. на завершение

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.

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11 видео ((всего 83 мин.)), 2 материалов для самостоятельного изучения, 1 тест
11 видео
Goals for the Course1мин
Course Outline and Overview3мин
People Analytics in Practice4мин
Performance Evaluation: the Challenge of Noisy Data6мин
Chance vs. Skill: the NFL Draft22мин
Finding Persistence: Regression to the Mean11мин
Extrapolating from Small Samples5мин
The Wisdom of Crowds: Signal Independence5мин
Process vs. Outcome7мин
Summary of Performance Evaluation3мин
2 материала для самостоятельного изучения
Performance Analytics Slides PDF10мин
People Analytics in Action: Additional Reading10мин
1 практическое упражнение
Performance Evaluation Quiz20мин
Неделя
2
2 ч. на завершение

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 видео ((всего 73 мин.)), 2 материалов для самостоятельного изучения, 1 тест
12 видео
Staffing Analytics Overview2мин
Hiring 1: Predicting Performance8мин
Hiring 2: Fine-tuning Predictors9мин
Hiring 3: Using Data Analysis to Predict Performance7мин
Internal Mobility 1: Analyzing Promotibility4мин
Internal Mobility 2: Optimizing Movement within the Organization8мин
Causality 15мин
Causality 26мин
Attrition: Understanding and Reducing Turnover10мин
Turnover: Predicting Attrition7мин
Staffing Analytics Conclusion49
2 материала для самостоятельного изучения
Staffing Analytics Slides PDF10мин
Staffing Analytics in Action: Additional Reading10мин
1 практическое упражнение
Staffing Quiz20мин
Неделя
3
2 ч. на завершение

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.

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7 видео ((всего 75 мин.)), 2 материалов для самостоятельного изучения, 1 тест
7 видео
Basics of Collaboration5мин
Describing Collaboration Networks14мин
Mapping Collaboration Networks16мин
Evaluating Collaboration Networks10мин
Measuring Outcomes9мин
Intervening in Collaboration Networks18мин
2 материала для самостоятельного изучения
Collaboration Slides PDF10мин
Collaboration Research in Action: Additional Readings10мин
1 практическое упражнение
Collaboration Quiz20мин
Неделя
4
2 ч. на завершение

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 видео ((всего 85 мин.)), 2 материалов для самостоятельного изучения, 1 тест
9 видео
Interdependence6мин
Self-fulfilling Prophecies9мин
Reverse Causality4мин
Special Topics: Tests and Algorithms5мин
Prescriptions: Navigating the Challenges of Talent Analytics15мин
Course Conclusion: Organizational Challenges 110мин
Course Conclusion: Organizational Challenges 2 and Future Directions19мин
Goodbye and Good Luck!32
2 материала для самостоятельного изучения
Talent Analytics and Conclusion Slides PDF10мин
Talent Management in Action: Additional Readings10мин
1 практическое упражнение
Talent Management Quiz20мин
4.5
Рецензии: 500Chevron Right

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15%

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Лучшие отзывы о курсе People Analytics

автор: AADec 22nd 2018

Thank you so much for this very helpful module! I hope you continue to inspire HR professionals around the world to use HR Analytics as an important means to drive organizational-related decisions.

автор: 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.

Преподаватели

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Cade Massey

Practice Professor
The Wharton School
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Martine Haas

Associate Professor of Management
The Wharton School
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Matthew Bidwell

Associate Professor of Management
The Wharton School

О Пенсильванский университет

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. ...

О специализации ''Бизнес-аналитика'

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....
Бизнес-аналитика

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