The amount of data available to analyse and understand how people contribute to the success of organisations has grown exponentially over the last decade due to the widespread use of HR information systems and enterprise resource planning software. A growing wave of start-ups are offering new machine learning and AI tools and techniques for understanding the role and people factors in organisational performance.
In this context, most large organisations have developed HR/people analytics/insight teams in the last five years, following in the wake of large global technology and financial services institutions who have pioneered the development of this new business function. The UK professional body for HR has also recently launched new professional standards that place evidence based management and analytics at the heart of the professional competencies expected of the HR professional.
Despite these developments, it is widely perceived that HR lags behind other areas of business in the adoption of analytics. This programme will equip students with the skills and knowledge to work in the HR analytics field or to become an HR generalist who is competent in the use of data and analytics.
The programme of study is informed by the latest research and developments in the fields of HR analytics and HRM more generally, drawing on strong links with employers to provide students with an academically rigorous but practice informed learning experience.
The programme aims to foster in graduates the capacity for reflective practice, and professional and personal development so that they are able to contribute effectively to the leadership and management of business, organisations and society.
It also provides graduates with advanced understanding of the social science theory and evidence that underpins HR and people analytics and HR management more generally, allowing students to meet the knowledge requirements for chartered membership of the Chartered Institute for Personnel and Development.
[Learning Outcomes, Transferable (Key) Skills, Assessment]
View Timetable
Students are eligible for the award if they pass the 150 credits of modules (including any pass for progression modules) and achieve an overall average mark of 50 or above, calculated across the 180 credits of modules.
Students will be required to study the following 150 credits of compulsory modules:
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| LUBS5322M | Strategic Human Resource Management | 30 | Semester 1 (Sep to Jan) | PFP |
| LUBS5342M | People Analytics: Strategy and Practice | 30 | Semester 2 (Jan to Jun) | PFP |
| LUBS5346M | Data Analytics for Human Resources | 30 | Semesters 1 & 2 (Sep to Jun) | |
| LUBS5348M | Human Resources Analytics Research Methods and Dissertation Project | 60 | 1 Feb to 30 Sep |
Students will be required to study 30 credits from the following optional modules:
| Code | Title | Credits | Semester | Pass for Progression |
|---|---|---|---|---|
| LUBS5303M | Sustainable Futures: Climate Change, the Environment and Business | 30 | Semester 2 (Jan to Jun) | |
| LUBS5325M | Employment Law | 30 | Semesters 1 & 2 (Sep to Jun) | |
| LUBS5332M | Migration and Labour Mobility Management | 30 | Not running in 202526 | |
| LUBS5338M | Global Perspectives on Work | 30 | Semester 2 (Jan to Jun) | |
| LUBS5365M | Diversity Management | 30 | Semester 2 (Jan to Jun) | |
| LUBS5443M | Change Management and Communication | 15 | Semester 2 (Jan to Jun) | |
| LUBS5991M | Creating Effective Data Visualisations | 15 | Semester 2 (Jan to Jun) | |
| LUBS5995M | Digital Technologies for a Sustainable Future | 15 | Semester 2 (Jan to Jun) |
Last updated: 30/04/2025 16:07:50
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