UnitLevel 5Postgraduate

MGO5220 Workforce and employment analytics

Faculty of Business and Economics

MGO5220 Workforce and employment analytics is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics. It isn't offered in 2025. It has no prerequisites.

Credit points
6
Offered in 2025
Other periods
Monash Online
Assessment
No exam
3 tasks
Workload
144 hours
per semester

This is the 2025 handbook entry. See the 2027 entry.

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Requisites

Before MGO5220

No prerequisites or corequisites besides the enrolment rules below.

After MGO5220

No unit lists MGO5220 as a prerequisite in the 2025 handbook.

Enrolment rules

You must be enrolled in a Monash Online course to undertake this unit.

Overview

Synopsis: Contemporary human resource management (HRM) practice is increasingly relying on data to inform an organisation’s HR strategy. Digitalisation and existing business systems in organisations can hold an abundance of people related data sets which can be used to generate insights and evidence for effectively managing a workforce. This unit introduces data analytics concepts in the context of HRM and people management. You will learn how modern analytical tools can be used to visualise and meaningfully communicate insights from HR-centric data and how predictive analytics can be applied to various areas HRM (e.g. predicting employee attrition).

Offerings in 2025

Teaching periodCampusMode
Teaching period 2Monash OnlineMo
Teaching period 6Monash OnlineMo

Assessment

  • Within semester assessment
    100%
  • Written
    40%
  • Written
    60%

Learning outcomes

When you finish this unit, you should be able to:

  1. 1

    demonstrate an understanding of the role and value of data in improving workforce processes and informing people management decisions

  2. 2

    understand what key components are involved for delivering effective workforce analytical solutions

  3. 3

    develop an awareness of modern analytical tools used to analyse workforce-related data to address HR problems and identify HR opportunities

  4. 4

    recognise and identify the ethical considerations with using workforce and employment data for HRM.

  5. 5

    demonstrate knowledge or skills for crafting sustainable futures for people, organisations, communities, and/or the environment.

Workload and teaching

  • Teaching approachProblem-based learning
  • Teaching approachActive learning

Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. You are expected to complete all pre-class activities prior to your scheduled class, and post-class activities should be completed after your scheduled class. Learning activities may include a combination of teacher directed, peer directed and online engagement activities.

This unit includes problem-based learning approaches, where you engage in research, integrate theory and practice and apply knowledge and skills to develop viable solutions in response to a problem or set of problems.   

This unit engages you in actively applying your knowledge, skills and attributes in interactive, collaborative and reflective activities.

Contacts

Chief Examiners
Dr Danielle Ramirez

Common questions

What are the prerequisites for MGO5220?

MGO5220 has no prerequisites, but enrolment rules apply.

When is MGO5220 offered?

MGO5220 has no offerings listed in the 2025 handbook.

How much work is MGO5220?

The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.

Does MGO5220 have an exam?

No. MGO5220 has 3 assessment tasks and no exam.

More details

Credit points
6
Level
5
Study level
Postgraduate
Faculty
Faculty of Business and Economics
Organisational unit
Department of Management
Type
Coursework
EFTSL
0.125
Student contribution
SCA Band 4
Study abroad
Not available
Handbook years
20232024202520262027