This module is designed for students who have completed Year 1 and Year 2 of the Management Science BSc/MSci programme. In particular, it assumes that students have completed the modules in the Mathematics/Quantitative Thinking strand (MSIN103P, MSIN107P, MSIN203P) and the modules in the Data Analytics strand (MSIN102P, MSIN204P, MSIN206P).
Important business decisions cannot be left to intuition alone. We need to communicate the structure of our reasoning, defend it to adversarial challenges and make presentations that show we have done a thorough analysis. We also need to make sense out of various sources of data, organise the inputs of experts and colleagues, and use state-of-the-art tools to provide analytical support for our reasoning.
The objective of this course is to equip you to be more effective in these tasks. You will develop skills in data analysis, structuring decisions, building decision models, risk assessment, decision making under uncertainty, recognising areas where business analysis can add value, selecting appropriate types of analyses and learn to apply them in a small scale, quick-turnaround fashion.
The aims of this module are:
- To provide students with an understanding of how to structure business decisions, build decision models and assess risk.
- To introduce students to the challenges of decision-making under uncertainty and to help them understand where structured approaches to decision and risk analysis can add value.
- To provide students with practical experience of working with state-of-the-art decision support software.
Upon successful completion of the module, students will be able to:
- Understand what makes a good decision and the role of intuition and analysis in decision making.
- Understand how to structure managerial decision problems.
- Understand risk and how it can be measured and assessed.
- Understand the value of flexibility and optionality in decision-making.
- Understand the value of mitigating risk and obtaining additional information.
- Use selected decision support software, such as @Risk, PrecisionTree and Solver.
40% individual coursework comprising of 4 workshop reports; 60% 2-hour examination
Current students should refer to Moodle for specific details of the current year’s assessment.