2017/18 Undergraduate Module Catalogue

LUBS3185 People Analytics: Strategy and Practice

20 creditsClass Size: 26

Module manager: Xanthe Whittaker
Email: X.Whittaker@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

This module is mutually exclusive with

LUBS1525	Analytical Methods
LUBS2920	Advanced Analytical Methods

This module is approved as a discovery module

Module summary

The world of business, management and human resources becomes increasingly dependent on data. Data comes from different sources, capturing a variety of performance outcomes and determinants of human behaviour. It is indeed true that success in the contemporary HR profession hinges upon our ability to process and analyse data, and being able to translate quantitative outcomes into viable solutions to organisational problems.The module will introduce you to the fundamental principles of analytics in the context of human resource management, drawing on strategic human capital theory and other relevant perspectives. You will gain proficiency in pertinent quantitative techniques and software packages essential for developing analytical literacy. Using practical examples from the NHS and other large organisations, the module will help you to understand how HR analytics can be used to address organisational challenges.The module thus aims to ensure that every student is capable of analysing HR data and critically assessing outcomes of data analysis in light of practical HR problems. The module is supported by Q-Step at the University of Leeds. Q-Step is a £19.5 million programme designed to promote a step-change in quantitative social science training in the UK. Funded by the Nuffield Foundation, ESRC and HEFCE, Q-Step was developed as a strategic response to the shortage of quantitatively-skilled social science graduates.Q-Step is funding fifteen universities (including the University of Leeds) across the UK to establish Q-Step Centres that will support the development and delivery of specialist undergraduate programmes, including new courses, work placements and pathways to postgraduate study.

Objectives

A prime objective of this module is to develop basic analytic skills with regard to datasets, quantitative techniques and the type of measurements used in human resource management. It is imperative to contemporary HR specialists to be able to navigate through data, rapidly growing in volume and variety, and to understand the rationale for appropriate modelling, with its merits and limitations. The module will nurture a critical outlook on actual HR problems and the ways by which they can be solved with the help of analytic skills.

Learning outcomes
Upon completion of this module, students will be able to:
- understand and communicate the principles of data analytics in the context of human resource management;
- navigate through the complexity of HR data architecture;
- use quantitative methods to model HR outcomes;
- use R statistical environment to programme and analyse HR data;
- identify evidence-based solutions to practical HR problems.

Skills outcomes
Transferable skills:
- work with organisation-level and representative HR data;
- apply relevant quantitative techniques;
- IT and programming skills - gain proficiency in statistical software packages
- communication skills – effectively communicate practical solutions based on quantitative evidence.

Subject specific:
- use data literacy skills and statistical software packages to analyse HR data
- provide quantitative base for HR decision-making.

Syllabus

Indicative content:
- Analytics in the context of HRM: what is analytics and how can analytics be applied to HR and human capital?
- Strategy and analytics involving strategic human capital theory, strategic management, resourced based view of the firm and critical evaluation of these concepts
- Understanding HR data: data generation and administration; classes of data involving attitudinal data, soft performance data and hard performance outcomes
- Logic driven people analytics: theory building, solving commercial problems and developing models to understand the people dimensions of business challenges
- Understanding the potential and barriers to HR analytics in practice: balancing safe staffing and financial data, modelling safe staffing
- From analysis to action: visualising results and storytelling
- The future of people analytics: analytics as craft; analytics as software and products; machine learning and automation

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	1.00	10.00
Practical	4	1.00	4.00
Seminar	6	1.00	6.00
Private study hours			180.00
Total Contact hours			20.00
Total hours (100hr per 10 credits)			200.00

Private study

Students are expected to spend significant time outside of lectures checking their learning of techniques introduced in lectures, reading suggested materials and practicing software packages used to read, visualise HR data and conduct relevant analytical procedures.

Opportunities for Formative Feedback

Tutorial exercises.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	2,000 word Project Report	100.00
Total percentage (Assessment Coursework)		100.00

The resit for this module will be 100% by coursework.

Reading list

The reading list is available from the Library website

Last updated: 06/03/2018

Disclaimer

Browse Other Catalogues

• Undergraduate module catalogue
• Taught Postgraduate module catalogue
• Undergraduate programme catalogue
• Taught Postgraduate programme catalogue

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD