MSc Business Analytics: Operational Research and Risk Analysis / Course details

Year of entry: 2024

Course unit details:
Simulation & Risk Analysis

Course unit fact file
Unit code BMAN73942
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Available as a free choice unit? No


The unit provides an overview of simulation techniques and, in particular, their use in supporting risk analysis and flow management in systems that are sufficiently complex to limit the applicability of other modelling approaches. In particular, the unit covers and contrasts three of the main Operational Research simulation concepts and approaches: Monte Carlo Simulation, Discrete Event Simulation and System Dynamics. The unit also introduces Markov Chain Analysis and basic Queuing Theory models, and discusses the use of these mathematical approaches as a means of complementing and / or informing simulation. There is a focus on practical modelling work and students are introduced to a range of suitable software packages.



BMAN73942 Programme Req: BMAN73942 is only available as an elective to students on MSc Business Analytics and MSc Data Science (Business and Mgmt pathway)


Analysing systems dominated by randomness and/or interactions between their constituent elements is particularly challenging. Problems of this type include operational risk analysis, revenue management and improving operational process flow in service or manufacturing. This unit will focus on application of approaches developed to model such systems, including the basics of queuing theory, Markov processes and (in particular) computer-based simulation.


Learning outcomes

• Familiarity with the concepts and types of tools and techniques commonly used in analysing the performance of and risk in complex operational systems.
• Experience in considering different approaches and their assumptions, advantages and disadvantages.
• Ability to formulate, use and understand models of problem situations including, where appropriate, state-of-the-art software tools.


Teaching and learning methods

Formal Contact Methods

Minimum Contact hours: 20 

Delivery format: Lecture and Workshops 

Assessment methods

Group coursework project (50%)
Examination (50%)


Feedback methods

• Informal advice and discussion in contact sessions.
• Online discussion board.
• Written and/or verbal comments on assessed or non-assessed work

Recommended reading

Core texts:

Pidd, M. (2009), Tools for thinking (3rd ed), John Wiley & Sons, Chichester. (ebook available via library)
Robinson S (2014). Simulation: The practice of model development and use 2nd ed. Palgrave Macmillan: Basingstoke, UK
Hillier, F. and Lieberman, G.J. (2009), Introduction to operations research (9th ed), McGraw-Hill Education.

Supplementary reading:

Pidd, M. (1998). Computer simulation in Management Science (4th ed), Wiley. Savage, S.L. (2009), The Flaw of Averages, John Wiley & Sons. (ebook available via library (ebook available via library)
Holweg M, Davies J, de Mayer A, Lawson B and Schmenner RW (2018). Process theory: The principles of operations management. Oxford University Press: Oxford.
Slack N and Brandon-Jones A (2019). Operations management (8th ed.) Pearson Education: Harlow. (ebook available via library)
Additional background references may be listed with the material for the sessions - these are for interest and to provide more depth for interested students.

Study hours

Scheduled activity hours
Assessment written exam 2
Lectures 20
Seminars 10
Independent study hours
Independent study 118

Teaching staff

Staff member Role
Nathan Proudlove Unit coordinator

Additional notes

Informal Contact Methods

•    Office Hours
•    Online Discussion Board

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