Outline

Overview

Digital innovation is transforming markets, organisations and management itself. It is an important means for businesses in creating value for customers, and a necessary aspect of a modern manager's mindset. On the one hand, managers have to be able to critically examine the nature and promises of digital technology to make sense of unfolding trends and to avoid the trappings of technological fashions. On the other hand, the field of digital innovation offers new managerial techniques and tools for effective organizational management in changing environments. In this unit, students learn to re-imagine the way in which business is done through digital technology and to employ managerial innovations such as agile methods and insight generation and design thinking for creative problem framing and solving. Learning is based on hands-on in-class activities, case study analysis, and classroom discussions.

Unit details and rules

Academic unit	Management Education
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	MMGT6011
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	Carlos Vazquez Hernandez, carlos.vazquezhernandez@sydney.edu.au

Assessment

The census date for this unit availability is 3 October 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Portfolio or journal	Impact Journal Reflective learning journal. Each entry opens the content for next module/session.	0%	Multiple weeks	50-100 words	AI allowed
Outcomes assessed:
Written work	Problem Framing & Hills Statement Written report	30%	Week 02 Due date: 14 Oct 2025 at 23:59 Closing date: 24 Oct 2025	1000 words	AI allowed
Outcomes assessed:
Written work	Behavioural Solution Proposal Written report	30%	Week 03 Due date: 21 Oct 2025 at 23:59 Closing date: 31 Oct 2025	1000 words	AI allowed
Outcomes assessed:
Creative work	Group Video and Report Group Video and Written Report (e.g., White Paper)	20%	Week 05 Due date: 05 Nov 2025 at 23:59 Closing date: 15 Nov 2025	1000 words report and 3-mins group video	AI allowed
Outcomes assessed:
Creative work	Digital Proof of Concept A functional Proof of Concept using digital tools	20%	Week 05 Due date: 05 Nov 2025 at 23:59 Closing date: 15 Nov 2025	Proof of Concept	AI allowed
Outcomes assessed:
= group assignment ?

Assessment summary

Problem Framing and Hills Statement (Individual, 30%): Students identify a pre-scoped behavioural challenge aligned with the SDGs and develop a problem framing brief. This includes a contextual analysis of the issue in the region of interest (e.g., SEA), and the development of a Hills Statement outlining the key user, their need, and the significance of addressing it.
Behavioural Solution Proposal (Individual, 30%): Students propose a behavioural science-based intervention to address their chosen challenge. The proposal must articulate the behavioural mechanisms involved and integrate relevant technologies to support the solution.
Digital Proof of Concept (Group, 20%): Students collaborate in teams formed around promising individual proposals to develop a functional proof of concept (POC), where digital technologies are used to demonstrate the feasibility of the behavioural solution.
Final Group Video and Report (Group, 20%): Each team presents their final behavioural innovation through a professional video and report. These summarise the problem, behavioural insight, industry-enabled solution, and impact pathway.
Impact Journal: Students maintain a personal journal across the unit to reflect on complexity, behavioural framing, and their evolving role as changemakers. Each entry is guided by four lenses: system, technology, user, and producer. Entries also unlock access to subsequent module content.

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:

Late penalties will be applied per University policy.

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	Framing Complexity in a Digital World	Lecture and tutorial (8 hr)
Week 02	Behavioural Insight to Digital Solutioning (Part A)	Lecture and tutorial (8 hr)
Week 03	Behavioural Insight to Digital Solutioning (Part B)	Lecture and tutorial (8 hr)
Week 04	Digital Innovation & Development (Part A)	Lecture and tutorial (8 hr)
Week 05	Digital Innovation & Development (Part B)	Lecture and tutorial (8 hr)

Attendance and class requirements

All sessions are in-person only. No online options are possible. Students are required to complete pre-readings and other activities ahead of class and to participate in class discussions. Students are expected to arrive on time for class and to attend all sessions. Aspects of assessment require students to always be present throughout the 5 days of teaching.

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

All information necessary for the unit, including guidelines readings and other materials will be published on 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. Critically discuss and evaluate the key issues, debates, principles, concepts, and of behavioural theories that enable digital transformation for sustainable business futures
LO2. Apply appropriate methods for behaviourally informed digital transformation interventions in differentiated Environmental, Social, and Governance (ESG) contexts, and provide evidence-based arguments to support related analysis
LO3. Reflect upon individual and/or group performance in identifying behaviour change, solving complex digital transformation, and sustainability problems
LO4. Communicate behaviourally informed digital transformation for sustainable business futures and outcomes—and related analysis—convincingly, and professionally through written reports, video summaries/pitches, and oral discussions

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.

Updated for 2025 Nov/Dec delivery - assessment changes and updated weekly schedule to reflect updated content design and delivery.

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

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

MMGT6015: Digital Transformation

Semester 2b, 2025 [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

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