About this Course
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다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

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완료하는 데 약 11시간 필요

권장: 4 weeks of study, 1-2 hours/week...

영어

자막: 영어, 중국어 (간체자)

귀하가 습득할 기술

Talent ManagementAnalyticsPerformance ManagementCollaboration

다음 전문 분야의 1개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

완료하는 데 약 11시간 필요

권장: 4 weeks of study, 1-2 hours/week...

영어

자막: 영어, 중국어 (간체자)

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 2시간 필요

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
11개의 동영상
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
2개의 읽기 자료
Performance Analytics Slides PDF10m
People Analytics in Action: Additional Reading10m
1개 연습문제
Performance Evaluation Quiz20m
2
완료하는 데 2시간 필요

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
12개의 동영상
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 Conclusion49
2개의 읽기 자료
Staffing Analytics Slides PDF10m
Staffing Analytics in Action: Additional Reading10m
1개 연습문제
Staffing Quiz20m
3
완료하는 데 2시간 필요

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
7개의 동영상
Mapping Collaboration Networks16m
Evaluating Collaboration Networks10m
Measuring Outcomes9m
Intervening in Collaboration Networks18m
2개의 읽기 자료
Collaboration Slides PDF10m
Collaboration Research in Action: Additional Readings10m
1개 연습문제
Collaboration Quiz20m
4
완료하는 데 2시간 필요

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
9개의 동영상
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!32
2개의 읽기 자료
Talent Analytics and Conclusion Slides PDF10m
Talent Management in Action: Additional Readings10m
1개 연습문제
Talent Management Quiz20m
4.5
520개의 리뷰Chevron Right

26%

이 강좌를 수료한 후 새로운 경력 시작하기

29%

이 강좌를 통해 확실한 경력상 이점 얻기

14%

급여 인상 또는 승진하기

People Analytics의 최상위 리뷰

대학: 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.

대학: 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.

강사

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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

펜실베이니아 대학교 정보

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. ...

비즈니스 분석 전문 분야 정보

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....
비즈니스 분석

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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