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

Type	Description	Weight	Due	Length
Final exam (Take-home short release)	Final exam Written exam	40%	Formal exam period	3 hours
Outcomes assessed:
Presentation	Group presentation n/a	30%	Multiple weeks	50 minutes
Outcomes assessed:
Assignment	Inidividual assignment n/a	30%	Week 11	2000 words
Outcomes assessed:
= group assignment ? = Type D final exam ?

Assessment summary

Individual assignment: The individual assignment covers content delivered during the first half of the semester. The assessment task will be provided via Canvas. Students will be expected to submit the completed work via Canvas in Week 11.

Group presentation: The presentation and assessment of your managerial understanding of standards will be the focus of workshops in Weeks 8 and 9. Students will need to sign up for groups by Week 7. Cases will be made available at the beginning of each workshop.

Final exam: The final exam will covers all content delivered this semester and take place. The exam paper will be provided via Canvas. Students will be expected to submit their work via Canvas during final 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.

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 Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction; Material handling systems and automation	Block teaching (3 hr)
Week 02	System and database design for warehouse management systems - 1	Block teaching (3 hr)
Week 03	System and database design for warehouse management systems - 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	Overview of master data and traceability standards	Block teaching (3 hr)
Week 07	Standards adoption strategies for managing data quality and traceability in supply chains (practice workshops)	Block teaching (3 hr)
Week 08	Standards adoption strategies for managing data quality and traceability in supply chains (assessment workshops)	Block teaching (3 hr)
Week 09	Standards adoption strategies for managing data quality and traceability in supply chains (assessment workshops)	Block teaching (3 hr)
Week 10	TBD	Block teaching (3 hr)
Week 11	Managing logistics operations with ERP systems - 1	Block teaching (3 hr)
Week 12	Managing logistics operations with ERP systems - 2	Block teaching (3 hr)
Week 13	Perspectives from industry; 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.

This is the first time this unit has been 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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect

Current students

ITLS6010: Logistics and Supply Chain Management Systems

Semester 1, 2021 [Normal evening] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

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

Media

Student links

About us

Connect