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Unit of study_
CEMS6015: Business Transformation Management
2022 unit information
This unit is designed for students interested in understanding how to create a successful strategic roadmap in order to lead, seize opportunities, and transform organizational thinking in a digital age. For many years, state-of-the-art strategic thinking has promoted business models and leadership strategy based on competition analysis of close sector rivals, market analytics, as well as traditional human resources processes and talent development. At the present time, the impacts of digital transformation are so broad that the most disruptive competition is likely to be external, and come from businesses about which executives may have an incomplete understanding. For example, in Finance many traditional organizations (banks) are challenged by small fintech start-ups. Furthermore, businesses at the moment are facing many external uncertainties such as the COVID-19 outbreak crisis. This unit delivers an in-depth understanding of how current business needs can be supported by analytics and AI at the cutting-edge of thinking about the transformative potential of digital technology for tackling contemporary challenges. Students learn how digital transformation (through analytics and AI) could be championed in organisations facing risk and uncertainty. No previous experience in analytics or data science is necessary.
Unit details and rules
Managing faculty or University school:
Business (Business School)
| Study level | Postgraduate |
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| Academic unit | Management Education |
| Credit points | 6 |
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Prerequisites:
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None |
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Corequisites:
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None |
| Prohibitions:
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None |
| Assumed knowledge:
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None |
At the completion of this unit, you should be able to:
- LO1. Students will develop an ability to approach and define real-world problems in leading digital transformation as well as understand limitations, which responsible thinking brings to data-driven business models
- LO2. Students will develop an ability to identify appropriate measures, variables and datasets as well as to understand how to collect suitable data to minimize algorithmic bias and maximize business and customer value
- LO3. Students will develop an ability to select and apply the most appropriate methods and techniques to analyse the data and solve the problem
- LO4. Students will develop an ability to critically evaluate existing data science methodology against business needs
- LO5. Students will develop an ability to communicate AI and analytics findings for business-level understanding
- LO6. Students will develop an ability to approach all stages of the business problem-solving process in responsible and ethical manner
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
There are no availabilities for this year.
| Session | MoA ? | Location | Outline ? |
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Semester 1 2022
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Normal day | Castlereagh St, Sydney |
Outline unavailable
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Semester 1 2022
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Normal day | Remote |
Outline unavailable
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Semester 2 2022
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Normal day | Castlereagh St, Sydney |
Outline unavailable
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Semester 2 2022
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Normal day | Remote |
Outline unavailable
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Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
