Undergraduate Course: People Analytics (BUST10173)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course bridges human resource management and data analytics, providing students practical skills to interpret and apply workforce data in real-world scenarios. Through interactive case studies, hands-on data analysis, and industry insights, students will explore how HR professionals, managers, and organisation consultants use analytics to improve hiring, performance management, and employee engagement.
Integrating AI, predictive analytics, and workforce trends makes the course highly relevant in todays digital workplace. Students will also examine ethical dilemmas such as AI bias and data privacy, making the course technically engaging and critically thought-provoking.
By the end, students will be equipped with data-driven decision-making skills, preparing them for careers in HRM, business analytics, and organisational strategy consultancy where people analytics is becoming a key competitive advantage. |
| Course description |
People Analytics is transforming how organisations manage talent, optimise workforce performance, and align human resource strategies with business objectives. This undergraduate course introduces students to the principles, techniques, and applications of data-driven decision-making as it relates to decisions about the workforce. The course will help equip students with fundamental analytical skills to interpret and apply data analysis effectively. Students interested in human resource analytics and human capital consultancy will benefit from this course.
Students will explore key HR metrics and analytics frameworks. The course will examine how organisations use analytics to enhance recruitment, performance management, employee engagement, and workforce planning. Students will learn how to collect, analyse, and visualise people management data while considering ethical implications such as data privacy and algorithmic bias.
By the end of the course, students will have developed a foundational understanding of how to use people analytics to support evidence-based HR decision-making, preparing them for roles in management, human resource management, organisational transformation, and business analytics.
Outline content
Introduction to People Analytics (Week 1)
Workforce Metrics & Data-Driven HR Decisions (Week 2)
Data Management in HR (Week 3)
Statistical Analysis for Human Resources (Weeks 4-5)
AI, Machine Learning, and Qualitative Data Processing (Weeks 6-7)
Strategic Workforce Planning (Weeks 8-9)
Advanced Topics in HR Data Science (Week 10)
Capstone Project Presentations (Week 11)
Student learning experience
The students use class exercises and case study examples to facilitate interactive student discussions applying analytic frameworks.
Analytics reports and case assessments provide opportunities for students to analyse people management issues and topics by summarising multiple viewpoints and making related recommendations for policy and practice.
|
Course Delivery Information
|
| Academic year 2025/26, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 20,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
166 )
|
| Assessment (Further Info) |
Written Exam
65 %,
Coursework
35 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
15% Video assignment (Group) - Assesses all course Learning Outcomes
20% Case study analysis (Individual) - 1,000 words - Assesses all course Learning Outcomes
65% Exam (Computer-based) (Individual) - 1,500 words - Assesses all course Learning Outcomes |
| Feedback |
Formative: Students will be encouraged to email the course organiser/lecturer for some formative feedback ahead of their first assessment (summative work), based on their topic choice. Students will also be given formative feedback on their first assignment alongside their summative Assignment-1 mark, in time for it to be of potential use for them in successfully completing their examination (summative work).
Feedback on formative assessed work will be in time to be of use in subsequent assessments within the course.
Students will gain feedback on their understanding of the material when they discuss their answers in class concerning cases, debates and other types of exercise. Students may also ask questions directly before, during, and after Lectures to assess their own individual levels of knowledge and understanding in a timely fashion.
Summative: Summative marks will be returned on a published timetable, which has been made clear to students at the start of the academic year. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Apply analytical skills to improve management practices using data analytic techniques.
- Make data-driven decision-making in workforce planning, performance management, and employee engagement.
- Explain how AI, machine learning, and digital tools reshape HR functions and change management.
- Integrate strategic insights with HR data to align human capital strategies with business goals.
- Identify ethical considerations in the practice of people analytics.
|
Reading List
Indicative Text: Workforce Analytics: A Global Perspective. Edited By Martin R. Edwards, Dana Minbaeva, Alec Levenson, Mark Huselid (2025)
Indicative Text: Predictive HR Analytics: Mastering the HR Metric 3rd Edition by Dr Martin Edwards, Kirsten Edwards, Daisung Jang
|
Additional Information
| Graduate Attributes and Skills |
Practice: Applied Knowledge, Skills and Understanding
After completing this course, students should be able to:
Work with a variety of organisations, their stakeholders, and the communities they serve - learning from them, and aiding them to achieve responsible, sustainable and enterprising solutions to complex problems.
Knowledge and Understanding
After completing this course, students should be able to:
Demonstrate a thorough knowledge and understanding of contemporary organisational disciplines; comprehend the role of business within the contemporary world; and critically evaluate and synthesise primary and secondary research and sources of evidence in order to make, and present, well informed and transparent organisation-related decisions, which have a positive global impact.
Identify, define and analyse theoretical and applied business and management problems, and develop approaches, informed by an understanding of appropriate quantitative and/or qualitative techniques, to explore and solve them responsibly. |
| Keywords | People Analytics |
Contacts
| Course organiser | Prof Susan Murphy
Tel: (01316)51 5548
Email: Susan.Murphy@ed.ac.uk |
Course secretary | |
|
|
University Homepage