MIS40540 Project Management and Decision Analytics

Academic Year 2017/2018

Students undertaking the Master of Science in Business Analytics Degree (Analytics) come with a strong mathematical background, an affinity of developing computer software, practice with doing projects, and a desire to work in management. Many have engineering degrees. Some have business, mathematics, science or computer science backgrounds.Most of the Analytics courses are strongly technical. This course makes the bridge into management.The first Project Management part takes well-known management methodologies and typologies and breaks them down to reveal their underlying dimensions and variables. We alos look at the behavioural aspects of Project Management. The second part -Decision Analytics applies decision science to real problems of making choices using Multiple Criteria Decision-Making. It applies an analytical approach to real decision applications in an environment where management objectives can be conflicting. The focus is on providing immediately applicable techniques that are currently used by management and we also look at the behavioural aspects of these decisions. Students learn the latest methods for structuring problems, weighting criteria, scoring alternatives, and forming preferences.

Show/hide contentOpenClose All

Curricular information is subject to change

Learning Outcomes:

Students learn about project management and management methodologies and typologies from an analytical point of view, and how to quickly critique management systems.Students get experience of working in groups with people of different backgrounds on an academic research project to analyse some method or methodology in the light of the ideas presented in the course. They get experience as decision consultants with some such practical decision, such as helping other students that wish to make a decision during the period of the course about what they should do next year. Students also learn to understand how, by appreciating the cognitive biases to which they are prone, they can become better decision-makers

Student Effort Hours: 
Student Effort Type Hours
Lectures

24

Practical

12

Specified Learning Activities

100

Autonomous Student Learning

36

Total

172

 
Requirements, Exclusions and Recommendations

Not applicable to this module.



 
Description % of Final Grade Timing
Practical Examination: In Class Test

30

Week 12
Multiple Choice Questionnaire: In Class Test

25

Throughout the Trimester
Group Project: Group decision analytics project

25

Varies over the Trimester
Group Project: Group project management project

20

Varies over the Trimester

Compensation

This module is not passable by compensation

Resit Opportunities

End of Semester Exam

Remediation

If you fail this module you may repeat, resit or substitute where permissible