After employees are hired, a key activity that an HR analytics wants to conduct is to explore what factors predict post-hire employee performance the best. One reason to do this is to test how valid the interview processes are; a second reason is to identify the factors that will predict who is likely to turn out to be a high performer. Continue reading
When it comes to recruitment and selection of new employees, one of the key focuses at the forefront of an HR analyst’s priorities is to minimize bias as much as possible. In this post, we will examine diversity-related analysis on recruitment and selection activities. For example, what are the gender – male and female ratios of people who are shortlisted, interviewed, and ultimately offered a job? Also, the analyst may wish to conduct a similar analysis linked to ethnicity and other important demographic categorizations other than gender. Continue reading
In this post we will predict the factors that affect the individual employee turnover. Because our response variable is the turnover status, and its value in the dataset is binary type (1=leave, 0=stay), we will apply logistic regression to investigate the data. Continue reading
Employee turnover usually refers to all “leavers” of an organization – those who leave voluntarily or involuntarily. It includes those who resign, are made redundant, take retirement, or exit for any other reason. In this article we are only concerned with voluntary turnover and its possible causes. Continue reading
Last week we analyzed the survey question validity and construction provided by an external survey provider, now we are ready to test if the team engagement level is influenced by the work location and the group function. Continue reading
While Principal Component Analysis (PCA) and reliability test should be conducted on individual-level responses, this information is usually not available if the survey is conducted by an external survey provider. What we can do first is to apply PCA and reliability test to validate how the survey questions are constructed. Continue reading
Employee engagement is not a tangible thing and can’t be measured easily. However, based on the definition we choose, we then can ask a range of questions that will indicate how engaged the person is. Continue reading
In the previous post, we learned from a financial institution that the type of the team – sales or professional service has an impact on the prevalence of the minority groups. The conclusion was that the proportion of the staff with different ethnic backgrounds is significantly lower in sales than in the professional service. In this post, we want to know if we can come up with a model to predict employee diversity across the teams. Continue reading
In this example, we have team-level data from a UK-based financial company. The company has 29,976 employees in 928 teams which are divided in two main functions – sales and professional service. In short, sales staff are customer-facing employees; whereas professional service staff are non customer-facing employees such as product development, finance, marketing. Continue reading
Besides descriptive data, HR can use other methods to interrogate data in more detail. For example, HR might explore a dataset of gender and job role, and find that as job role status increases, the number of female employees decreases. See the figures below. To ensure that the finding is not just a coincidence, Continue reading
