Overview
In today's dynamic business landscape, organisations strive for operational excellence and data-driven decision-making. Operations management and business analytics offer a comprehensive exploration of the synergies between efficient operations and the strategic use of data analytics. The unit explores the contemporary principles and practices involved in the management of both service and manufacturing operations. Taking a strategic approach to operations, you will examine fundamental concepts such as process planning, design, control and Six Sigma continuous improvement; quality management and lean thinking; the role of the supply chain in modern operations; capacity and location principles as well as the use of project-based activities in an operational environment. You will utilise business data from a variety of organisational sources including financial, economic and market information and develop mathematical models for more effective operational decisions. The unit also provides you with the opportunity to engage in independent research using evidence-based approaches to identify workplace issues and recommend viable solutions that enhance organisational effectiveness.
Details
Pre-requisites or Co-requisites
There are no requisites for this unit.
Important note: Students enrolled in a subsequent unit who failed their pre-requisite unit, should drop the subsequent unit before the census date or within 10 working days of Fail grade notification. Students who do not drop the unit in this timeframe cannot later drop the unit without academic and financial liability. See details in the Assessment Policy and Procedure (Higher Education Coursework).
Offerings For Term 1 - 2026
Attendance Requirements
All on-campus students are expected to attend scheduled classes - in some units, these classes are identified as a mandatory (pass/fail) component and attendance is compulsory. International students, on a student visa, must maintain a full time study load and meet both attendance and academic progress requirements in each study period (satisfactory attendance for International students is defined as maintaining at least an 80% attendance record).
Recommended Student Time Commitment
Each 6-credit Postgraduate unit at CQUniversity requires an overall time commitment of an average of 12.5 hours of study per week, making a total of 150 hours for the unit.
Class Timetable
Assessment Overview
Assessment Grading
This is a graded unit: your overall grade will be calculated from the marks or grades for each assessment task, based on the relative weightings shown in the table above. You must obtain an overall mark for the unit of at least 50%, or an overall grade of 'pass' in order to pass the unit. If any 'pass/fail' tasks are shown in the table above they must also be completed successfully ('pass' grade). You must also meet any minimum mark requirements specified for a particular assessment task, as detailed in the 'assessment task' section (note that in some instances, the minimum mark for a task may be greater than 50%). Consult the University's Grades and Results Policy for more details of interim results and final grades.
All University policies are available on the CQUniversity Policy site.
You may wish to view these policies:
- Grades and Results Policy
- Assessment Policy and Procedure (Higher Education Coursework)
- Review of Grade Procedure
- Student Academic Integrity Policy and Procedure
- Monitoring Academic Progress (MAP) Policy and Procedure - Domestic Students
- Monitoring Academic Progress (MAP) Policy and Procedure - International Students
- Student Refund and Credit Balance Policy and Procedure
- Student Feedback - Compliments and Complaints Policy and Procedure
- Information and Communications Technology Acceptable Use Policy and Procedure
This list is not an exhaustive list of all University policies. The full list of University policies are available on the CQUniversity Policy site.
Feedback, Recommendations and Responses
Every unit is reviewed for enhancement each year. At the most recent review, the following staff and student feedback items were identified and recommendations were made.
Feedback from SUTE
This is just a comment. I was pleased that the assessment was an assignment and not an exam. I noticed that there was varied Excel competence amongst the student group in this subject, and I certainly am no expert. By having the analytics as an assignment, I could take my time to work it out and practice the required tasks without feeling under pressure. So, I would say keep the assessment as an assignment. The lecturer was terrific! Professional & very supportive - I really enjoyed this subject.
Continue providing staggered assessment support and materials that build confidence in analytical (including Excel) skills relevant to the assessment.
Feedback from SUTE
Please provide more examples and details for the spreadsheets and case analysis. The A2 is useful but a bit difficult.
Develop more templated example case analysis spreadsheet activities for in-class use.
- Develop an advanced and integrated understanding of operations managements and business analytics
- Critically analyse and reflect on key principles of operations analytics
- Critically apply a complex systems approach to analytically identify, analyse and investigate the management of operational functions
- Synthesise complex data from a variety of sources and develop mathematical models as part of the analytical process to identify and propose solutions to contentious workplace business problems
- Interpret and successfully apply knowledge related to recent development of operations management in service and manufacturing industries.
Alignment of Assessment Tasks to Learning Outcomes
| Assessment Tasks | Learning Outcomes | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1 - Critical Review - 40% | |||||
| 2 - Report - 60% | |||||
Alignment of Graduate Attributes to Learning Outcomes
| Graduate Attributes | Learning Outcomes | ||||
|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | |
| 1 - Knowledge | |||||
| 2 - Communication | |||||
| 3 - Cognitive, technical and creative skills | |||||
| 4 - Research | |||||
| 5 - Self-management | |||||
| 6 - Ethical and Professional Responsibility | |||||
| 7 - Leadership | |||||
| 8 - First Nations Knowledges | |||||
| 9 - Aboriginal and Torres Strait Islander Cultures | |||||
Textbooks
Business Analytics
- Latest Edition
- Authors: Camm, Jeffrey D ; Cochran, James J ; Fry, Michael, J.
- Mason, OH : Cengage
- ISBN: 9780357131909
Operations and Supply Chain Management for MBAs
- Latest Edition
- Authors: Authors: Jack R. Meredith and Scott M. Shafer
- John Wiley & Sons Inc
- ISBN: 9781119898672
Operations Management: An Integrated Approach
- Edition: 8
- Authors: R. Dan Reid and Nada R. Sanders
- John Wiley & Sons, Inc.
- ISBN: 9781119905509
IT Resources
- CQUniversity Student Email
- Internet
- Unit Website (Moodle)
- computer lab
- Excel 2016 with Add-in Solver
All submissions for this unit must use the referencing style: American Psychological Association 7th Edition (APA 7th edition)
For further information, see the Assessment Tasks.
i.ali@cqu.edu.au
d.turnbull@cqu.edu.au
Week 1
Begin Date: 09 Mar 2026Module/Topic
Introduction to Operations Management
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 2
Begin Date: 16 Mar 2026Module/Topic
Process Planning and Design
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 3
Begin Date: 23 Mar 2026Module/Topic
Process Monitoring and Control
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 4
Begin Date: 30 Mar 2026Module/Topic
Managing the Supply Chain and Inventory
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 5
Begin Date: 06 Apr 2026Module/Topic
Forecasting, Capacity Planning and Facility Location
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 6
Begin Date: 13 Apr 2026Module/Topic
Introduction to Business Analytics
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Vacation Week
Begin Date: 20 Apr 2026Module/Topic
Chapter
Events and Submissions/Topic
Week 7
Begin Date: 27 Apr 2026Module/Topic
Optimisation Modelling
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 8
Begin Date: 04 May 2026Module/Topic
Modelling and Sensitivity Analysis
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 9
Begin Date: 11 May 2026Module/Topic
Network Models and Decision Analytics
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 10
Begin Date: 18 May 2026Module/Topic
Quality Management
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 11
Begin Date: 25 May 2026Module/Topic
Just-in-time and Lean Systems
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Week 12
Begin Date: 01 Jun 2026Module/Topic
Project Management
Chapter
Lecture notes and materials are available in Moodle.
Events and Submissions/Topic
Exam Week
Begin Date: 08 Jun 2026Module/Topic
Chapter
Events and Submissions/Topic
Vacation/Exam Week
Begin Date: 15 Jun 2026Module/Topic
Chapter
Events and Submissions/Topic
1 Critical Review
This is an individual assessment. In this assessment, the students are required to perform a critical analysis of the literature on the intersections of digital technologies and supply chain resilience and devise a model or framework for resilient supply chain operations. The literature should not be more than three years old and should be sourced from the recommended list of academic journals in the field of operations and supply chain management (the list of journals has been provided in Moodle).
Students are advised to submit their 2500-word (+/- 10%) critical review through Turnitin in Moodle, with a cover sheet showing the unit name and number, assessment number, student name, and ID. Assessment details and guidelines will be provided on the unit website.
This assessment requires students to adhere to the guidelines on the use of artificial intelligence tools as specified in the Artificial Intelligence Assessment Scale (AIAS) Level-1. Any misuse or lack of disclosure regarding the use of AI tools will be considered a breach of academic integrity. AIAS Level-1 states: The assessment is completed entirely without AI assistance in a controlled environment, ensuring that students rely solely on their existing knowledge, understanding, and skills. You must not use AI at any point during the assessment. You must demonstrate your core skills and knowledge.
Week 6 Thursday (16 Apr 2026) 11:45 pm AEST
A late penality @ 5% per day applies
Week 8 Friday (8 May 2026)
See your marks in Moodle and grade book
The assessment will be marked based on the following criteria:
Developed a succinct introduction of the review: 10%
Performed descriptive statistics: 20%
Critically discuss how different technologies support three main elements (readiness, response, and recovery) of supply chain resilience: 25%
Devised a robust framework linking digital technologies and supply chain resilience: 20%
Evaluated and articulated the viability and limitations of implementing a resilient supply chain framework for the organisation: 10%
Conclusion and recommendations: 10%
Cited at least 20 articles following APA style: 5%
- Develop an advanced and integrated understanding of operations managements and business analytics
- Critically analyse and reflect on key principles of operations analytics
- Critically apply a complex systems approach to analytically identify, analyse and investigate the management of operational functions
- Synthesise complex data from a variety of sources and develop mathematical models as part of the analytical process to identify and propose solutions to contentious workplace business problems
- Interpret and successfully apply knowledge related to recent development of operations management in service and manufacturing industries.
2 Report
This is an individual assessment. The assessment is designed for students to apply operations management principles and business analytics. It involves writing about factors influencing location decisions, identifying optimal facility locations, and scenario-based mathematical modelling of business problems to devise optimal solutions for operational efficiency and productivity.
Students need to submit a 2500-word (+/- 10%) Business Report and their quantitative outcomes based on the developed Optimisation Models using Excel Spreadsheets through Turnitin, and Moodle, with a cover sheet showing unit name and number, assessment number, your name, and student ID. Submissions must be in Business Report format using Word with 1.5 line spacing and Times Roman 12-point font. Further details and guidelines on assessment have been provided on the unit website.
This assessment requires students to adhere to the guidelines on the use of artificial intelligence tools as specified in the Artificial Intelligence Assessment Scale (AIAS) Level-1. Any misuse or lack of disclosure regarding the use of AI tools will be considered a breach of academic integrity. AIAS Level-1 states: The assessment is completed entirely without AI assistance in a controlled environment, ensuring that students rely solely on their existing knowledge, understanding, and skills. You must not use AI at any point during the assessment. You must demonstrate your core skills and knowledge.
Week 12 Friday (5 June 2026) 11:45 pm AEST
A late penality @ 5% per day applies
The result will be released after grade certification
The assessment will be marked following these criteria:
Developed a concise executive summary and introduction for the report: 10%
Demonstrated a comprehensive understanding of the factors influencing facility location decisions: 20%
Conducted thorough analysis and accurately identified the optimal facility location: 20%
Developed and evaluated a mathematical model, proposing solutions to the problems/questions: 25%
Interpreted the outcomes of the model's analytics: 10%
Integrated a minimum of 12 academic journal articles, adhering to APA reference format: 10%
Ensured clarity of written expression, grammar, and spelling: 5%
- Develop an advanced and integrated understanding of operations managements and business analytics
- Critically analyse and reflect on key principles of operations analytics
- Critically apply a complex systems approach to analytically identify, analyse and investigate the management of operational functions
- Synthesise complex data from a variety of sources and develop mathematical models as part of the analytical process to identify and propose solutions to contentious workplace business problems
- Interpret and successfully apply knowledge related to recent development of operations management in service and manufacturing industries.
As a CQUniversity student you are expected to act honestly in all aspects of your academic work.
Any assessable work undertaken or submitted for review or assessment must be your own work. Assessable work is any type of work you do to meet the assessment requirements in the unit, including draft work submitted for review and feedback and final work to be assessed.
When you use the ideas, words or data of others in your assessment, you must thoroughly and clearly acknowledge the source of this information by using the correct referencing style for your unit. Using others’ work without proper acknowledgement may be considered a form of intellectual dishonesty.
Participating honestly, respectfully, responsibly, and fairly in your university study ensures the CQUniversity qualification you earn will be valued as a true indication of your individual academic achievement and will continue to receive the respect and recognition it deserves.
As a student, you are responsible for reading and following CQUniversity’s policies, including the Student Academic Integrity Policy and Procedure. This policy sets out CQUniversity’s expectations of you to act with integrity, examples of academic integrity breaches to avoid, the processes used to address alleged breaches of academic integrity, and potential penalties.
What is a breach of academic integrity?
A breach of academic integrity includes but is not limited to plagiarism, self-plagiarism, collusion, cheating, contract cheating, and academic misconduct. The Student Academic Integrity Policy and Procedure defines what these terms mean and gives examples.
Why is academic integrity important?
A breach of academic integrity may result in one or more penalties, including suspension or even expulsion from the University. It can also have negative implications for student visas and future enrolment at CQUniversity or elsewhere. Students who engage in contract cheating also risk being blackmailed by contract cheating services.
Where can I get assistance?
For academic advice and guidance, the Academic Learning Centre (ALC) can support you in becoming confident in completing assessments with integrity and of high standard.
What can you do to act with integrity?
