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Unit outline_

ITLS5050: Introductory Supply Chain Analysis

Semester 1, 2023 [Normal evening] - Camperdown/Darlington, Sydney

The amount of data generated within organisations is growing rapidly and the ability of supply chains to harness emerging opportunities and respond to issues of sustainability and resilience relies on the ability of managers to make effective decisions based on the information provided by careful analysis of data. Through this unit students develop a strong understanding of the basic techniques underpinning quantitative analysis for logistics and supply chain management and develop highly marketable skills in spreadsheet modelling and the communication and presentation of data to support management decision making. This unit emphasises the practical aspects of quantitative analysis and students are guided through the basic theories used in decision making. This unit emphasises how the theories are applied in practice, drawing on real world experience in quantitative analysis for logistics and supply chain management. The unit covers demand forecasting, spreadsheet modelling, optimisation of production and distribution using linear programming, simulation and quantitative performance management. The unit also introduces basic statistics and linear regression techniques.

Unit details and rules

Academic unit Transport and Logistics Studies
Credit points 6
Prerequisites
? 
None
Corequisites
? 
ITLS5020 or ITLS5000 or TPTM5001
Prohibitions
? 
TPTM6495 or ITLS5200 or ITLS6203 or MMGT6012
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Geoffrey Clifton, geoffrey.clifton@sydney.edu.au
Type Description Weight Due Length
Assignment Final report
Written report
40% Formal exam period
Due date: 17 Jun 2023 at 23:59

Closing date: 27 Jun 2023
1000 words
Outcomes assessed: LO3 LO4
Supervised test
? 
Computer exam
The date is subject to confirmation.
30% Week 08
Due date: 22 Apr 2023 at 15:00
2 hours
Outcomes assessed: LO1 LO2 LO3
Assignment Individual report
The individual report topic will be available on Canvas
30% Week 10
Due date: 04 May 2023 at 23:59

Closing date: 14 May 2023
1000 words
Outcomes assessed: LO2 LO3 LO4

Assessment summary

Individual report: Write a report to a business manager on how quantitative analysis can address an issue in LSCM. The exact topic will be provided on Canvas. The report should include reference to academic and professional literature, evidence of your own data analysis, as well as tables and charts of your own creation.

Computer exam: The computer exam will test your ability to apply the techniques covered in class and to interpret your results.

Final report: Two essay topics will be assigned one week prior to the due date. One essay will cover the application of the material covered in class during the Semester. The other essay will reflect on your learning during the Semester.

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.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

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.

WK Topic Learning activity Learning outcomes
Week 01 Introduction to supply chain modelling Workshop (3 hr) LO1 LO2 LO4
Week 02 Spreadsheet modelling Workshop (3 hr) LO1 LO2 LO3
Week 03 Linear programming Workshop (3 hr) LO1
Week 04 Linear programming applications Workshop (3 hr) LO1 LO2 LO3 LO4
Week 05 Aggregate planning Workshop (3 hr) LO1 LO2
Week 06 Forecasting with regression Workshop (3 hr) LO1 LO2 LO3
Week 07 Computer exam review Workshop (3 hr) LO1 LO2 LO3
Week 10 Demand modelling Workshop (3 hr) LO1
Week 11 Demand modelling applications Workshop (3 hr) LO1 LO2 LO3 LO4
Week 12 Simulation modelling Workshop (3 hr) LO1 LO2 LO3
Week 13 Simulation modelling applications and course review Workshop (3 hr) LO1 LO2 LO3 LO4

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

Camm J. D., Cochran J. J., Fry M. J., Ohlmann J. W. (2021). Business Analytics, (4th ed), Cengage Learning US, Boston. ISBN: 9780357131787

https://cengage.com.au/product/title/business-analytics/isbn/9780357131787 

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.

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

  • LO1. Select the appropriate model to use in unfamiliar contexts and implement the core set of quantitative logistics and supply chain management models in an efficient manner
  • LO2. Clean, chart and present data and the outputs of quantitative logistics and supply chain analysis and interpret and discuss outputs, identifying limitations and creating recommendations
  • LO3. Explain analytic logistics and supply chain methods in your own words and how the techniques are implemented in practice and contribute to better management decision making
  • LO4. Recognize and address issues relating to the ethics and limitations of quantitative logistics and supply chain analysis

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

Improvements to feedback and changes to the topic mix are being implemented this year.

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.