Course Information Undergraduate prospectus

Human Resources Metrics

Course summary

Course code: BUSI1629
Level: 4
Credits: 15
School: Business Faculty
Department: Human Res and Organisational Beh
Course Coordinator(s): Leroi Henry

Specification

Aims

This course introduces students to the fundamental logic underlying HR metrics. It focuses on evaluating HR tools and practices; understanding the types of data that are available in organisations; computing descriptive statistics; communicating data straightforwardly; while ensuring that ethical risks are mitigated and employees’ data is secure. In doing so, students will develop subject specific and key transferable skills that are necessary for future course/dissertation work in university settings, and also in employment in human resources roles.

Learning outcomes

On successful completion of this course a student will be able to:

1. Understand the role of HR metrics in supporting organisational success
2. Evaluate HR tools and practices for reliability and validity
3. Understand the types of data held by organisations and how variables are typically measured
4. Understand how employee surveys are designed and used by HR practitioners and HR researchers, including the components of effective survey design
5. Identify ethical issues and understand how to mitigate ethical risks in collecting, analysing, and storing employee data
6. Compute descriptive statistics and effectively report data, using both written words and visuals, so that it is straightforwardly understood

Indicative content

HR metrics and evidence-based management; forms of reliability and validity and an understanding of when each type is relevant to HR practitioners; understand where data is held in organisations (e.g. recruitment, pay, employee survey, KPIs, etc) and the form that those variables take (e.g. continuous, categorical, binary, etc.); understand survey design and how scales are developed and used in research and practice, including how to find high-quality scales in academic research; identify the main ethical issues involved in collecting, analysing, and storing data; use Excel to enter data, compute descriptive statistics (mean, standard deviation, etc), and effectively communicate the results in both words and graphical form.

Teaching and learning activity

The course will use readings, in-class discussion and exercises, applied work on computers, and an exam to accomplish the course objectives. The readings will provide the backdrop to the lectures and discussions. The in-class discussions and exercises will allow students to learn from one another and clarify understanding of course materials. The students will be provided with an opportunity, in groups, to complete a series of exercises to receive formative feedback. The exercises will mirror some of those found on the exam. The students will participate in 12, 2-hour sessions; 2-3 of those sessions will be held in a computer lab.

Assessment

Exam - 100% weighting, 40% pass mark.
Outline Details - two hours written exam.

Formative Assessment - Group Assignment.