Module Title:People Analytics
Language of Instruction:English
Credits: 5
NFQ Level:8
Module Delivered In No Programmes
Teaching & Learning Strategies: Lectures - communication of knowledge and ideas from the lecturer to the student. Problem Solving Exercises - student will work as part of a team and will work together to resolve various HRM scenarios. Class Discussion/Debate - Students will be encouraged to actively participate in the class sessions which will develop their analytical and communication skills. E-Learning - It is envisaged that the module will be supported with on-line learning materials. Self-Direct Independent Learning - the emphasis on independent learning will develop a strong and autonomous work and learning practices.
Module Aim: This module aims to provide an understanding of the importance of people analytics in practice. In doing so, the objective is to develop the knowledge, skills and abilities to use people-data in analytical processes to solve business problems. From this process, students will contribute to improved performance in many of the HRM functions, from recruitment and selection, to turnover and retention. This module will enable students to make realistic connections between strategic, business and operational plans. The module will promote the value added strategic role of people analytics, as opposed to the narrow view of meeting reporting and compliance based requirements. Students will also develop a pragmatic approach to people analytics projects and find opportunities from data and vice versa. In summary, the objective is to inform students of how people-data can contribute to HRM’s ultimate objective of improved organisational performance.
Learning Outcomes
On successful completion of this module the learner should be able to:
LO1 Connect HR and business data in ways that aid the alignment and improved success between strategic and operational business plans
LO2 Analyse and use HR data and analytics to demonstrate the impact that HR policies, practices and processes may have on workforce and organisational performance.
LO3 Identify, gather, diagnose and communicate the links between HR analytics and sustainable organisational performance by aligning people data with business intelligence data.
Pre-requisite learning
Module Recommendations

This is prior learning (or a practical skill) that is recommended before enrolment in this module.

No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.
No requirements listed
 

Module Content & Assessment

Indicative Content
Introduction to HR analytics
What is HR/People analytics; Contextual awareness; aligning strategic, business and operational plans;
Developing the Process
Developing a process for analysis; Levels of analysis: descriptive, predictive and prescriptive; trend analysis; diagnosing; scenario planning; risks
Knowledge Sources
Internal and external sources; quantitative and qualitative; hard and soft data; Databases - HR Systems, Data Databases and their usage
Data analysis of the HRM functions
1. Resourcing – forecasting, position surveys  Recruitment and selection – internal and external  Workforce planning – and flexibility  Staff turnover and retention 2. HRD – learning, training and development interventions 3. Performance management and appraisal 4. Employee engagement 5. Rewards 6. Contemporary issues - diversity management
Responsibilities
Ethical and moral responsibilities; Sustainability; CSR, GDPR
Assessment Breakdown%
Continuous Assessment100.00%
Continuous Assessment
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Other Examination/Essay/Group Project/Presentation/Case studies Example - case study analysis and problem solving, developing descriptive research questions and sources of relevant data. 1,2,3 40.00 Week 24
Other Examination/Essay/Group Project/Presentation/Case studies Example - Case study analysis - using predictive and prescriptive analysis of data to solve problems. 1,2,3 60.00 Sem 2 End
No Project
No Practical
No End of Module Formal Examination

SETU Carlow Campus reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Frequency Average Weekly Learner Workload
Lecture Every Week 3.00
Independent Learning Every Week 6.00
Total Hours 9.00
Workload: Part Time
Workload Type Frequency Average Weekly Learner Workload
Lecture Every Week 1.50
Independent Learning Every Week 7.50
Total Hours 9.00