HR Analytics - BUSN9167

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2021 to 2022
Canterbury
Spring Term 7 15 (7.5) N Clarke checkmark-circle

Overview

This module aims to provide an understanding of the importance of HR analytics in practice. It will also ensure that students have hand-on experience to apply current quantitative techniques and tools to a variety of problems encountered in HR. Special emphasis will be given to the analysis of diversity within companies and how HR analytics can contribute to a better understanding on how this relates to performance, retention and the wider organisational climate.
Topics are:
• Introduction to HR Analytics
• HR Systems, Data Databases and their usage
• Diversity Analytics
• Engagement and Workforce Perceptions
• Predicting Employee turnover and performance
• HR analytics – recruitment and selection
• HR Analytics to mentor training and interventions
• Critical HR Analytics – ethical and moral implications for Organisations and Employees

Details

Contact hours

Total contact hours: 24
Private study hours: 126
Total study hours: 150

Method of assessment

Main assessment methods
VLE Test (20%)
Individual presentation – 15-20 minutes (20%)
3000 word individual report (60%)

Reassessment method:
100% coursework

Indicative reading

Bhattacharyya, D. K. (2017). HR Analytics: Understanding Theories and Applications. London: Sage.

Edwards, M. R., & Edwards, K. (2018). Predictive HR Analytics: Mastering the HR Metric. London: Kogan Page Publishers

Marr, B., (2018). Data-Driven HR: How to Use Analytics and Metrics to Drive Performance. London: Kogan Page Publishers

Students are strongly recommended to read as widely as possible, using a mixture of textbooks and journal articles. Support and encouragement of journal article reading is provided through seminar activities.

Students are advised to read from the following journals:
Journal of Applied Psychology; Employee Relations; Human Resource Management Journal; International Journal of Human Resource Management; Personnel Psychology; Psychometrika

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to
- Demonstrate an advanced knowledge and understanding of core concepts and analytical frameworks in HR analytics with the aim to influence and shape people and business strategy by aiding strategic decision making.
- Critically identify links between HR analytics and sustainable organisational performance by aligning people data with business intelligence data.
- Critically apply relevant knowledge, skills and creativity in analysing HR data using advanced quantitative techniques.
- Evaluate opportunity costs and/or propositions to build capability within an organisation using evidence based practice
- Demonstrate a practical understanding of model building and problem-solving techniques to support ethical and responsible HR policies using specialised software.

The intended generic learning outcomes.
On successfully completing the module students will be able to:
- Select and critically apply a variety of problem solving techniques, both autonomously and collaboratively.
- Aiding strategic decision making through applying HR people and business analytics
- Effectively communicate information, arguments and analysis in a variety of forms (e.g. storytelling)
- Work effectively as part of a group, and use self-direction, initiative and planning in the context of independent learning and the management of assignments

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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