Outline

Overview

The biggest challenge facing most businesses today is that they don't anticipate the changes in their market environment that fundamentally threaten the way they do what they do. This applies to the government sector and not-for-profits as much as it does to for-profit businesses. While some organisations struggle to respond to new uses of new digital technologies (including data), others have re-designed themselves to use those same digital technologies to address continuously evolving customer and employee needs in new profitable ways. How do businesses ensure that they renew themselves before they become obsolete? This unit of study is the culmination of the previous four Executive MBA units of study, combining entering new markets, incorporating cutting-edge technology and using leadership and strategy to challenge existing business models. We look at existing businesses that have managed this transformation well and examine those that haven't. This unit will include examples of companies that figured out how to minimise the risks of digital while leveraging their distinct benefits. Students obtain an understanding of how organisations can adapt to disruption. We examine how organisations are drawing on digital technologies (most notably data and AI) for growth and resilience. How are organisations redesigning themselves to realise significantly more impact faster with a variety of digital technologies amidst a global landscape increasingly marked by technological, geopolitical, economic, and environmental changes? We also examine the impact of technology on the workforce, and the future of work. A major project on a progressive organisation enables students to apply what they have learned to this organisation's transformation.

Unit details and rules

Academic unit	Management Education
Credit points	12
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	EMBA6000
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Massimo Garbuio, massimo.garbuio@sydney.edu.au

Assessment

The census date for this unit availability is 1 May 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Written work	Reflective Report Report	50%	Formal exam period Due date: 13 Jun 2026 at 23:59 Closing date: 23 Jun 2026	4000 words	AI allowed
Outcomes assessed:
Presentation	Interim team project presentation Oral presentation	10%	Week 04 Due date: 16 May 2026 at 23:59 Closing date: 16 May 2026	15 Minutes	AI allowed
Outcomes assessed:
Presentation	Final team project presentation Oral presentation	40%	Week 05 Due date: 22 May 2026 at 23:59 Closing date: 22 May 2026	25 Minutes	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Interim team project presentation: Each team will present project analyses and conclusions to date, previewing the presentation they are planning for the final day of the module. The focus at this stage will be on explaining:

1.    the underlying business problem(s) and opportunities identified
2.    the process the team has followed thus far, the information gathered, and next steps.

Final team project presentation: The project will involve pre-departure deskwork, research on the topic prior to the unit, on-the-ground analyses during the two-week module, and preparation of a presentation. Presentations should overview the project and indicate its scope, summarize the analyses completed, and suggest key conclusions and insights gained.
A 'Presentation Pack' summarising the team's research, analysis and recommendations should be included in the submission in the form of an Appendix/Data Pack.
Reflective report: In this report you are asked to reflect on the key leadership habits that emerged from the module and assess their relevance and implications to the way in which you currently lead and face leadership challenges. Use explicit examples to explain a few leadership challenges and how the experience of this module has influenced the way that you will approach these and similar challenges.

Detailed information for each assessment can be found 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)

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.

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:

According to University and Business School policies.

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	Pre-departure orientation and briefing	Lecture (3 hr)
Week 04	Monday 11 May: Day 1	Lecture (9 hr)
	Tuesday 12 May: Day 2	Lecture (9 hr)
	Wednesday 13 May: Day 3	Lecture (9 hr)
	Thursday 14 May: Day 4	Lecture (9 hr)
	Friday 15 May: Day 5	Lecture (9 hr)
	Saturday 16 May: Day 6	Lecture (9 hr)
Week 05	Monday 18 May: Day 7	Lecture (9 hr)
	Tuesday 19 May: Day 8	Lecture (9 hr)
	Wednesday 20 May: Day 9	Lecture (9 hr)
	Thursday 21 May: Day 10	Lecture (9 hr)
	Friday 22 May: Day 11 Final Presentations and Debrief	Lecture (9 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 12 credit point unit, this equates to roughly 240-300 hours of student effort in total.

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. Apply a series of frameworks to engage organisational leaders in meaningful discussions around the management of digital business models
LO2. Identify some of the ways in which leaders can effectively manage the change required to create value in a digital world
LO3. Develop customer-centric approach to digital innovation that increases business impact and minimises resource waste
LO4. Design and implement strategies for a future-ready workforce
LO5. Examine your leadership capabilities required for success in a digital business model
LO6. Examine a company using digital business model frameworks to develop a relevant strategy for success in the organisational context

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.

No changes have been made since this unit was last offered.

Additional information

Business School Policies

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

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

EMBA6006: Challenging Business Models

Intensive April - May, 2026 [Block mode] - Castlereagh St, 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

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