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Regular version of the site

Staffing Analytics Overview

2019/2020
Academic Year
ENG
Instruction in English
3
ECTS credits
Course type:
Elective course
When:
2 year, 2 module

Instructors

Программа дисциплины

Аннотация

The course is a part of the people analytics’ track. The main point of this discipline is to understand the basics of the staffing process including hiring the right persons, placing them in the right position and developing the strategies to keep the key employees. It also provides a strong framework to put into practice HRM statistical tools and methods. The course includes online learning over the Coursera platform in which 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. In class students will practice in using analytics to improve efficiency at hiring, placing and retaining the great people (12 academic hours)
Цель освоения дисциплины

Цель освоения дисциплины

  • Identify what to do for being efficient at hiring.
  • Use analytics to improve efficiency at hiring, placing and retaining the best people.
  • Manage techniques to hire, place and retain the right employees.
  • Recognize the relationship between HRM and organizational performance, business strategy as well as organizational behavior.
  • Analyze the relationship between HR practices and their outcomes for the individual and the organization.
Результаты освоения дисциплины

Результаты освоения дисциплины

  • Apply received knowledge and understanding of data and tools to real business situations
  • Study and apply people science methods adjusting to working environment
  • Demonstrate the ability to make managerial decisions and evaluate their consequences
  • Demonstrate the ability to catch new knowledge and skills in the fields beyond his/her majoring
  • Create and defend a customized suggestions based on data and analytics given
  • Demonstrate the ability to collect, process, and analyze data necessary for solving tasks
  • Create and defend a customized consulting project based on data and analytics given
Содержание учебной дисциплины

Содержание учебной дисциплины

  • Topic 1. Introduction to Staffing Analytics, and Performance Evaluation
    What is analytics? Data type. Three levels of staffing analytics. Two values. Analytic capabilities. Analytic value chain. Analytic model. Performance Evaluation: the Challenge of Noisy Data. Chance vs. Skill: the NFL Draft. Finding Persistence: Regression to the Mean. Extrapolating from Small Samples. The Wisdom of Crowds: Signal Independence. Process vs. Outcome. Learning objectives for the seminar:  Talk about preparing for an analytics unit of a particular company.  Identify ten steps taken to reorganize the analytics unit within an HR department to make its output more useful to business leaders.
  • Topic 2. Staffing Analytics in Human Capital Management Systems
    Turning data into information. Force analysis. Metrics and statistical applications.Three value paths. Efficiency measures. Effectiveness measures. Business outcome measures. People analytics trends. Barriers andkey enablers to success.Hiring: Predicting Performance: Fine-tuning Predictors;Using Data Analysis to Predict Performance. Internal Mobility: Analyzing Promotibility& Optimizing Movement within the Organization.
  • Topic 3. Collaboration Environment of Human Capital Management System
    Basics of Collaboration. Describing Collaboration Networks. Mapping Collaboration Networks. Evaluating Collaboration Networks. Measuring Outcomes. Intervening in Collaboration Networks.
  • Topic 4. Talent Analytics and Future Directions
    Self-fulfilling Prophecies. Reverse Causality. Tests and Algorithms. Prescriptions: Navigating the Challenges of Talent Analytics. Organizational Challenges and Future Directions.
  • Topic 5. Performance Evaluation: the Formation of the Squad
    The continuum of staffing analytics. Data set for predictive analytics. Relationships, optimizations, and predictive analytics. Prior performance. The peculiarities of the squad formation. Learning objectives for seminars:  Practice to determine the key performance indicators (KPIs) in order to segment the data into three types of measures: efficiency, effectiveness and outcomes  Discuss how to analyze and report the obtained data.
  • Topic 6. Performance Evaluation within an Academic Contract.
    Placing the employees: internal mobility and promotion or career perspectiveswithin an Academic Contract. Learning objectives for the seminar:Written test
Элементы контроля

Элементы контроля

  • Class activities (неблокирующий)
    (1) Kahoot game. At the beginning or at the end of some lectures a 15-minute Kahoot game is conducted. If the student missed the class, there is no option to participate in this activity. (2) Individual assignment during seminars. At the beginning or at the end of some seminars students will get a written task for 10-15 min based on their home reading or materials discussed during the previous classes. If the student missed the class, there is no option to rewrite this task, except for sickness absence. In this case, the student should notify the instructor about his/her sick leave.
  • Written Test in the LMS (неблокирующий)
    The quiz consists of 30 test questions (1 mark for each positive answer), 2 open questions with an explanation of your ideas (up to 3 marks for each positive answer), and one practical exercise (up to 4 marks)
  • Exam in the LMS (неблокирующий)
    The exam consists of 40 test questions and covers all topics including the Blended course details. Total time: 60 min. No negative marks for wrong answers.
Промежуточная аттестация

Промежуточная аттестация

  • Промежуточная аттестация (2 модуль)
    0.25 * Class activities + 0.4 * Exam in the LMS + 0.35 * Written Test in the LMS
Список литературы

Список литературы

Рекомендуемая основная литература

  • Fitz-enz, J., & Mattox, J. (2014). Predictive Analytics for Human Resources. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=812792

Рекомендуемая дополнительная литература

  • Pease, G. (2015). Optimize Your Greatest Asset —— Your People : How to Apply Analytics to Big Data to Improve Your Human Capital Investments. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1046506