Outline

Overview

Modern supply chain tools such as the internet of things and sensors linked with Enterprise Resource Planning and Warehouse Management Systems are strengthening Information Technology systems as the backbone of supply chains. This is facilitating communication between systems and organisations throughout the length of the supply chain. However, many companies are struggling to manage the large and growing flow of data which is needed to generate meaningful insights. This requires enterprises to develop consistent data standards that allow integration of systems within and between organisations. A unified treatment of supply chain systems helps achieve sustainable profitability for both enterprises and the entire supply chain. It also facilitates compliance and drives strategy for Corporate Social Responsibility, environmental sustainability and resilient supply chains. The improved supply chain visibility enables the optimisation of all functions simultaneously, including sourcing, manufacturing, warehousing, distribution, retail and reverse logistics, and allows the tracking of key performance indicators in supply chain operations. This unit develops highly marketable skills in managing and analysing data to generate meaningful key performance indicators and insights for nimble and agile decision making. Students gain experience with enterprise resource planning systems and tools needed for system integration.

Unit details and rules

Academic unit	Transport and Logistics Studies
Credit points	6
Prerequisites ?	(ITLS5020 or ITLS5000 or TPTM5001) and (ITLS5050 or ITLS5200 or TPTM6495) and (ITLS6201 or ITLS6101) and (ITLS6202 or ITLS6003)
Corequisites ?	ITLS6002
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Jyotirmoyee Bhattacharjya, jyotirmoyee.bhattacharjya@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written work	Final assignment Individual assignment	30%	Formal exam period Due date: 20 Nov 2025 at 23:59 Closing date: 21 Nov 2025	24 hours	AI allowed
Outcomes assessed:
Presentation	Group presentation Group activities	30%	Multiple weeks	2 weeks	AI allowed
Outcomes assessed:
Written work	In-semester assignment Individual assignment	40%	Week 12 Due date: 01 Nov 2025 at 23:59 Closing date: 11 Nov 2025	2500 words	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Group presentation: The presentations in Weeks 9 and 10 will focus on your managerial understanding of traceability standards. Students will need to sign up for groups by Week 8. Detailed instructions will be available via Canvas.

In-semester assignment: The in-semester individual assignment covers WMS design content delivered during the first half of the semester. Detailed instructions for the assessment will be provided via Canvas. Students are strongly advised to submit drafts for feedback as advised in the instructions

Final assignment: The final individual assignment is comprehensive in scope, i.e., it covers all key topics covered during semester. Detailed instructions will be provided via Canvas. Students will be expected to submit the completed work during exam week.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction to Systems in Logistics and Supply Chain Operations	Block teaching (3 hr)
Week 02	Database Design for WMS - 1	Block teaching (3 hr)
Week 03	Database Design for WMS - 2	Block teaching (3 hr)
Week 04	Querying Operational Data - 1	Block teaching (3 hr)
Week 05	Querying Operational Data - 2	Block teaching (3 hr)
Week 06	Traceability in Supply Chains - 1	Block teaching (3 hr)
Week 07	Traceability in Supply Chains - 2	Block teaching (3 hr)
Week 09	Assessed Presentations on Traceability in Supply Chains - 1	Presentation (3 hr)
Week 10	Assessed Presentations on Traceability in Supply Chains	Presentation (3 hr)
Week 11	Managing L & SC Operations with an ERP System - 1	Block teaching (3 hr)
Week 12	Managing L & SC Operations with an ERP System - 2	Block teaching (3 hr)
Week 13	Wrap-up	Block teaching (3 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Readings will be provided via Canvas as required

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. Integrate and synthesise understanding of key system design and application concepts in a variety of logistics and supply chain contexts
LO2. Apply a range of research skills to diagnose complex logistics and supply chain management problems.
LO3. Integrate disciplinary and interdisciplinary perspectives to identify creative system based solutions for logistics and supply chain problems
LO4. Identify and use appropriate technological tools for the development of effective solutions to LSCM problems.
LO5. Use effective communications strategies to reach agreement with others about appropriate systems and standards-based solutions to complex logistics and supply chain management problems
LO6. Prepare for working in real business environments by working collaboratively with diverse teams, integrating different cultural perspectives in the development of a presentation for an industry audience

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

Students enjoy developing practical skills that are necessary for today's supply chain professionals. No changes have been made since this unit was last offered.

Additional information

Business School Policies

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links

ITLS6010: Logistics and Supply Chain Management Systems

Semester 2, 2025 [Normal evening] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links