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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/wharton-people-analytics
课程评论：没有评论
课程名称：人员分析 课程概述：人员分析是一种基于数据的工作管理方法。历史上首次，商业领袖可以基于深度的数据分析而不是传统的个人关系、经验决策和风险规避的方法来做出关于员工的决策。在这门全新的课程中，三位沃顿商学院的顶尖教授，将探讨用于招聘和留住优秀员工的先进技术，并展示这些技术在前沿公司的应用。他们将阐释如何将数据和复杂的分析方法应用于与员工相关的问题，如招聘、绩效评估、领导力、招聘与晋升、岗位设计、薪酬和协作等。本课程旨在介绍人员分析理论，而不是为学习者准备进行复杂的人才管理数据分析。课程结束时，您将理解何时使用硬数据来做出关于雇佣和人才发展的软技能决策，从而使您能够在公司的人才管理决策中担任战略合作伙伴。课程还旨在帮助您在职业生涯中蓬勃发展，因为一个组织的成功与内部员工的成功密切相关，而分析可以帮助实现这一目标。 课程大纲： 1. **引言与绩效评估**：介绍课程的结构与范围，探讨绩效评估的基本问题，包括如何衡量员工的表现及其挑战。 2. **人员配备**：学习如何运用数据分析招聘、内部流动和职业发展及人员流失的关键环节，以此提高决策质量。 3. **协作**：了解如何利用人员分析改善组织内部的员工协作，包括绘制协作网络图及干预措施。 4. **人才管理与未来发展**：探索人才分析的使用，着重于员工评估和发展，处理在这一领域的主要挑战，并讨论未来发展方向以更好地利用员工数据。 通过这门课程，您将掌握如何运用分析技术，帮助组织和员工更有效地成长与成功。
Name:Introduction to People Analytics, and Performance Evaluation
Description: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.
Name:Staffing
Description: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.
Name:Collaboration
Description: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.
Name:Talent Management and Future Directions
Description: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.
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.
