People Analytics - BUSN6007

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2021 to 2022
Autumn Term 6 15 (7.5) Carola Leicht checkmark-circle


Employee performance, retention, recruitment/selection, development, engagement

The module will focus on practical applications of analytical methods in the context of HR processes. Participants will acquire an understanding of quantitative methods important for prediction and evaluation. Statistical techniques will be applied to analyse a range of employee characteristics and HR processes in view of their optimisation and contribution to employee well-being and firm performance.

Indicative topics of study are:
• Introduction to People Analytics
• HR Systems, Data Databases and their usage
• Statistical methods for prediction and evaluation
• Analytics for diversity management
• Analytics for employee attitudes and perceptions
• Analytics for managing employee turnover and performance
• Analytics for managing recruitment and selection
• Analytics for training, learning and development
• Critical People Analytics – data privacy, transparency, security and ethics


Contact hours

Total contact hours: 22
Private study hours: 128

Total study hours: 150

Method of assessment

Main assessment methods:

Group presentation – 15-20 minutes (20%)
2000 word individual report (80%)

Reassessment methods:

100% coursework

Indicative reading

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

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:

- Demonstrate a systematic 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.
- Develop an accurate understanding of methods of statistical inference required to analyse people data.
- Critically identify links between HR analytics and drivers of sustainable organisational performance.
- Critically apply relevant knowledge, skills and creativity in analysing HR data to improve the efficiency and effectiveness of HR processes.
- 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:

- Demonstrate enhanced analytical skills by linking quantitative techniques to people management processes/data
- Work effectively in groups in order to solve complex problems
- Analyse as well as synthesize complex data to facilitate decision-making
- Critically evaluate current practices using big data and artificial intelligence in the context of company management
- Demonstrate an ability to communicate effectively to a variety of audiences and/or using a variety of methods


  1. Credit level 6. Higher level module usually taken in Stage 3 of an undergraduate degree.
  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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