MEEN40360 Decision Analysis

Academic Year 2023/2024

This is an option module on the Master of Engineering Management programme. It is designed for participants based in industry and who have at least five years professional engineering work experience.

This module is designed to provide engineering management students with a detailed understanding of the principles and practices of decision analysis, with particular emphasis on the application of analytical tools and techniques to assist decision making in engineering operations and supply chains environments.
Decision analysis provides the engineering manager with an approach and set of tools to construct and analyse a model of a decision situation. The objective is to help the engineering manager examine a decision in detail, including the structure, data and preferences in order to gain understanding, insight and ultimately to improve decision making. It is expected that students are familiar with basic statistical concepts, probability distributions and regression

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Curricular information is subject to change

Learning Outcomes:

1. Relate the theory of decision analysis to decision making in engineering operations.
2. Demonstrate the application of quantitative tools and techniques to enable decision making in engineering operations environments.
3. Critique the results of decisions made with a view to improving engineering management decision making competency.
4. Apply both oral and written communication through continuous in-class discussions and written reports.
5. Assess published academic and practitioner research related to decision analysis to support in-class discussions and written reports.

Indicative Module Content:

Topics include:-
Introduction to quantitative decision making, modelling, simulation, underlying theory and concepts.

Problem identification, solution formulation, verification and validation.

Decision analysis, decision making with probabilities, decision trees. Spreadsheet computational tools, Linear and Non Linear Programming, Solver, Software packages for simulation.

Development of discrete event simulation models using manual techniques, Excel spreadsheets, Excel Monte Carlo methods and also the Extend simulation software package.

Use of probability distributions including empirical, normal, exponential, beta, triangular, etc.. Analysis of expected values and model outcomes. Queuing Theory, Reliability Theory.

Applications from sectors including service, industrial, manufacturing and financial.

Student Effort Hours: 
Student Effort Type Hours


Specified Learning Activities


Autonomous Student Learning




Approaches to Teaching and Learning:
active/task-based learning;
peer and group work; lectures;
reflective learning;
case-based learning;
student presentations, 
Requirements, Exclusions and Recommendations
Learning Recommendations:

This is a core module on the Master of Engineering Management and the Professional Diploma in Operations Excellence programmes. It is designed for postgraduate students based in industry and who have at least two to five years professional engineering work experience.

Module Requisites and Incompatibles

Additional Information:
This module is designed for postgraduate students based in industry and who have at least two to five years professional engineering experience.

Decision Analysis (EEME40170)

Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Project: Industry Based Decision Analysis Application Week 10 n/a Graded No


Journal: Group Simulation Journal Coursework (End of Trimester) n/a Graded No


Presentation: Industry Based Application Week 10 n/a Graded No


Carry forward of passed components
Resit In Terminal Exam
Spring No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

The module will use the following two texts:
"Decision Analysis for Management Judgment”, Paul Goodwin and George Wright, 5th Edition, publisher Wiley.
"Practical Management Science", Wayne Winston & S. Christian Albright, 6th edition, publisher Cengage Learning.

As an alternative to the "Practical Management Science" text , students are referred to the following 3 texts:
“Business Analytics – Data Analysis and Decision Making”, S. Christian Albright & Wayne Winston, 6th edition, publisher Cengage Learning.
“Management Science – The Art of Modeling with Spreadsheets”, Stephen Powell & Kenneth Baker, 1st – 4th editions, publisher Wiley.
“Analytics for Managers with Excel”, Peter C. Bell & Gregory S. Zaric, publisher Routledge (Taylor & Francis).

Other Decision Analysis reference texts are:
“Decision Making Under Uncertainty with RISKOptimizer – A Step by Step Guide Using Palisade’s RISKOptimizer for Excel”, by Wayne Winston, 2nd edition, publisher Palisade Corporation.
"Introduction to Management Science – A Modeling and Case Studies Approach with Spreadsheets", Frederick Hillier & Mark Hillier, 5th edition, publisher McGraw Hill International.
“Making Hard Decisions”, Robert Clemen & Terence Reilly, 1st/2nd/3rd editions, publisher Cengage Learning.
“Decision Making Under Uncertainty”, David E Bell & Arthur Schleifer, publisher Cengage Learning
“Handbook of Decision Analysis”, Gregory Parnell, Terry Bresnick, Steven Tani, Eric Johnson, publisher Wiley.
Name Role
Dr Pezhman Ghadimi Lecturer / Co-Lecturer
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Lecture Offering 1 Week(s) - 1, 4, 8, 12 Fri 12:00 - 13:50
Lecture Offering 1 Week(s) - 2, 3, 5, 6, 9, 10, 11 Fri 15:00 - 16:50