Postgraduate Course: Managing Strategic Risk in Major Projects (MSc) (PGEE11203)
Course Outline
School | School of Engineering |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | The course deep dives into the sources of strategic risk in the delivery of major projects and how to overcome, and even profit from, such risks.
This course seeks to equip the student with an understanding of how to map and manage strategic risks in the designing, building, and running of major projects. Drawing on behavioural psychology and theories of risk management, this course will review the challenges of risk facing major projects, the causes why major projects typically encounter risks; and examine the cures how these common pitfalls may be avoided and potentially even turned to one's advantage. The course will introduce a variety of analytical tools such as Reference Class Forecasting, Real-Option Valuing, or Systems Thinking to holistically assess and manage risks. The course will conclude with a primer on radical technologies such as modularity, automation, digitisation (including machine learning & artificial intelligence) to harness risk. The course draws on a wide array of cases and empirical evidence.
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Course description |
The course will be organised in three successive stages, one per day: Challenges, Causes and Cures.
Each day will include lectures and presentations on topics within those themes and be completed with groupwork. In the last day, the groups will also present they work.
The themes and topics covered during each day include:
Day 1 - Challenges
- What are the Sources & Impacts of Risk?
- Big is Fragile: Scale vs Scalability
- Cumulative & Inherited Fragility: System-Level Consequences of Risky Decisions
Day 2 - Causes
- What are the Causes of Risk?
- Perverse Incentives
- Myopia of Learning
Day 3 - Cures
- How to Succeed under Uncertainty
- Embracing Risk with Real Options
- Learning Like A Machine: Collective Artificial Intelligence
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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Academic year 2022/23, Not available to visiting students (SS1)
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Quota: None |
Course Start |
Semester 1 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 13,
Seminar/Tutorial Hours 5,
Online Activities 2,
Feedback/Feedforward Hours 2,
Summative Assessment Hours 25,
Revision Session Hours 51,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
0 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Written Exam 0%
Practical Exam 0%
Coursework 100%
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Feedback |
Feedback will be provided in three ways:
- On the online forum before and after the on-campus block.
- The course will be delivered in short block mode with lectures intertwined with tutorials/workshops. This will allow for a two-way dialogue between students and course tutors to allow judgement on course material understanding.
- Formal written feedback will be provided after the submission of the coursework exercise
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No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Describe the types, causes, and impacts of risk in delivering major projects.
- Analyse and explain strategic risk.
- Critically evaluate theories and practices of strategic risk management.
- Develop analytical tools to overcome, and even profit from, strategic risk.
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Reading List
Completion of this course will require extensive reading and each of the six half-day engagements will have their own digest of pre-reading. Overarching texts include:
- Flyvbjerg, Bent, Nils Bruzelius, and Werner Rothengatter, 2003, Megaprojects and Risk: An Anatomy of Ambition (Cambridge: Cambridge University Press).
- Kahneman, Daniel, 2011. Thinking, Fast and Slow, New York: Farrar, Straus and Giroux
- Powell, T. C. (2017). Strategy as Diligence: Putting Behavioral Strategy into Practice. California Management Review, 59(3), 162¿190. https://doi.org/10.1177/0008125617707975
- Taleb, Nassim Nicholas, 2010. The Black Swan: The Impact of the Highly Improbable, Second Edition, London and New York: Penguin.
Reading will also be complemented with multimedia sources
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Additional Information
Graduate Attributes and Skills |
Not entered |
Keywords | Strategic Risk,Major Projects |
Contacts
Course organiser | Dr Simon Smith
Tel: (0131 6)50 7159
Email: |
Course secretary | Miss Margaret Robertson
Tel: (0131 6)50 5565
Email: |
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