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Human Resources Analytics: Exploring Employee Data in R

Manipulate, visualize, and perform statistical tests on HR data.

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5 Hours16 Videos60 Exercises8,575 Learners4750 XP

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Course Description

HR analytics, people analytics, workforce analytics -- whatever you call it, businesses are increasingly counting on their human resources departments to answer questions, provide insights, and make recommendations using data about their employees. In this course, you'll learn how to manipulate, visualize, and perform statistical tests on HR data through a series of HR analytics case studies.

  1. 1

    Identifying the best recruiting source


    In this chapter, you will get an introduction to how data science is used in a human resources context. Then you will dive into a case study where you'll analyze and visualize recruiting data to determine which source of new candidates ultimately produces the best new hires. The dataset you'll use in this and the other chapters in this course is synthetic, to maintain the privacy of actual employees.

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    Welcome to the course!
    50 xp
    Applications of human resources (HR) analytics
    50 xp
    Looking at the recruiting data
    100 xp
    Recruiting and quality of hire
    50 xp
    Identifying groups in data
    100 xp
    Sales numbers by recruiting source
    100 xp
    Attrition rates by recruiting source
    100 xp
    Visualizing the recruiting data
    50 xp
    Visualizing the sales performance differences
    100 xp
    Visualizing the attrition differences
    100 xp
    Drawing conclusions
    50 xp
  2. 2

    What is driving low employee engagement?

    Gallup defines engaged employees as those who are involved in, enthusiastic about and committed to their work and workplace. There is disagreement about the strength of the connection between employee engagement and business outcomes, but the idea is that employees that are more engaged will be more productive and stay with the organization longer. In this chapter, you'll look into potential reasons that one department's engagement scores are lower than the rest.

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  3. 3

    Are new hires getting paid too much?

    When employers make a new hire, they must determine what the new employee will be paid. If the employer is not careful, the new hires can come in with a higher salary than the employees that currently work at the same job, which can cause employee turnover and dissatisfaction. In this chapter, you will check whether new hires are really getting paid more than current employees, and how to double-check your initial observations.

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  4. 4

    Are performance ratings being given consistently?

    Performance management helps an organization keep track of which employees are providing extra value, or below-average value, and compensating them accordingly. Whether performance is a rating or the result of a questionnaire, whether employees are rated each year or more often than that, the process is somewhat subjective. An organization should check that ratings are being given with regard to performance, and not individual managers' preferences, or even biases (conscious or subconscious).

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  5. 5

    Improving employee safety with data

    In many industries, workplace safety is a critical consideration. Maintaining a safe workplace provides employees with confidence and reduces costs for workers' compensation and legal liabilities. In this chapter, you'll look for explanations for an increase in workplace accidents.

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Recruitment dataSurvey dataFair pay dataPerformance dataHR dataAccident dataHR data (2)Survey data (2)


sumedhpanchadharSumedh PanchadharrichieRichie Cotton
Ben Teusch Headshot

Ben Teusch

People Analytics Partner at Facebook

Ben is an HR Analytics Consultant at Capital Group. His passion is using data science to improve the way people experience work, manage others at work, and get work done. Ben holds degrees in mathematics, economics, & industrial and labor relations.
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