Outline

Overview

This unit provides an in-depth understanding of the role of business processes in effectively and efficiently managing business operations. Students gain essential skills of the entire Business Process Management (BPM) lifecycle, from process identification and design to process monitoring, including process modelling, analysis, redesign, and automation required to achieve high performance and deliver the strategy in a service-oriented environment. Students also gain highly sought after practical skills of using BPM tools to recommend improvements by documenting and simulating current and new processes.

Unit details and rules

Academic unit	Business Information Systems
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	INFS2020
Assumed knowledge ?	INFS1000 or INFO1000 or INFO1003 or INFO1903
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Corina Raduescu, corina.raduescu@sydney.edu.au
Lecturer(s)	Corina Raduescu, corina.raduescu@sydney.edu.au
Lecturer(s)	Jeffrey Lo, jeffrey.lo@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Supervised exam ?	Final Exam Written exam	40%	Formal exam period	2 hours
Outcomes assessed:
Assignment	Individual Assignment Written submission	25%	Week 06 Due date: 04 Apr 2025 at 23:59 Closing date: 11 Apr 2025	Up to 1750 Words
Outcomes assessed:
Assignment	Group Plan Pitch (5 min) Presentation & Submission	10%	Week 09 Due date: 28 Apr 2025 at 09:00 Closing date: 30 Apr 2025	Up to 500 words (6 PPT slides)
Outcomes assessed:
Assignment	Group Project Group Report Submission	25%	Week 13 Due date: 30 May 2025 at 23:59 Closing date: 31 May 2025	Up to 2750 words
Outcomes assessed:
= group assignment ? = AI allowed ?

Assessment summary

Individual assignment: In this assignment students will take the role of the process analyst and engage in process discovery and analysis within a given business case context.
Group Plan assignment: In this assignment students will analyse the market and identify new services to be executed via new and modified business processes. Students will also develop a project plan to guide the project execution. Students will present and make a written submission.
Group Report assignment: In this assignment students will design new processes following the services proposed in the Group Plan assignment. Students will assess the feasibility of the new processes, the resources required, and the challenges encountered during process implementation. Students will use Signavio (BPM tool) to document, simulate and analyse the new business processes. Students will present a summary of the findings and recommendations.
Final exam: A supervised exam that will test students theoretical understanding, critical thinking, and ability to apply and evaluate BPM concepts and principles in practice.

Detailed information for each assessment will be released as appropiate on Canvas.

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) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

As per policy.

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.

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 the Unit and Business Process Management (BPM)	Workshop (3 hr)
Week 02	Process identification	Workshop (3 hr)
Week 03	Process discovery	Workshop (3 hr)
Week 04	Process modelling (1) - BPMN Notation	Workshop (3 hr)
Week 05	Process modelling (2) - As-Is Modelling using BPMN and Signavio	Workshop (3 hr)
Week 06	Process analysis (1) (qualitative)	Workshop (3 hr)
Week 07	Process analysis (2) (quantitative): As-Is Simulation using Signavio	Workshop (3 hr)
Week 08	Process improvement (1) - Redesign heuristics	Workshop (3 hr)
Week 09	Group plan presentations - Feedback collection	Workshop (3 hr)
Week 10	Process improvement (2) - To-Be Simulation using Signavio	Workshop (3 hr)
Week 11	Process implementation, monitoring and mining	Workshop (3 hr)
Week 12	Process automation and Group project consultation	Workshop (3 hr)
Week 13	Unit Review and Final Exam Practice	Workshop (3 hr)

Attendance and class requirements

Each week session is a combination of live lecture and hands-on exercises. All lecture topics are broken down in specific topics, followed by hands-on exercises.
The materials will be available the week before and students are expected to review the lecture notes, the exercises, and the additional materials, e.g., textbook chapters, videos. This will enhance students' ability to apply the BPM concepts and fully engage during the class.
Students should attend and participate in all classes if they want to be able to fully understand and apply the concepts, thus maximise their learning as solutions to in-class exercises are not provided.
Students can use Generative AI in all assessments, to help them understand the complexities of the industry landscape, to source relevant information, however the work must be fully contextualised to the business case in order to attract marks. Generic answers will not be rewarded.

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

Marlon D., Marcello L. R., Jan M., Hajo A. R. (2018). Fundamentals of Business Process Management, (2nd ed), Springer Berlin Heidelberg. [ISBN: 978-3-662-56509-4 (ebook) and 978-3-662-56508-7 (hardcover) and 978-3-662-58585-6 (softcover)]
The eBook is available for purchase: https://www.springer.com/gp/book/9783662565087 ; and free access via the University Library.

All further readings for this unit can be accessed through the Reading List, available via Canvas.

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. Discuss the role of Business Process Management (BPM) in a business environment and how BPM initiatives contribute to improving the overall business performance
LO2. Apply the BPM principles, concepts, and frameworks to business problems and practice as captured in the BPM lifecycle
LO3. Address the issues and challenges associated with process improvement initiatives in organisations
LO4. Evaluate the impact of process design and redesign decisions on stakeholders and the role of change management in addressing the risks associated with such changes in organisations
LO5. Use BPM tools to model, document, and analyse processes during the BPM lifecycle stages
LO6. Work independently, collaborate, and communicate in a professional manner with people from diverse backgrounds within a team work environment

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 unit is continually updated in response to student feedback, including a greater emphasis on case studies, revised assessments, and updated learning materials.

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) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

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

INFS3120: Business Process Analysis and Design

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

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

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

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