Data-Driven Decision-Making

On completion of the course, students will be able to:

1. describe and analyse the role of intuition in decision-making in complex environments
2. explain and critically analyse how asymmetric information affects collective decisions and actions
3. explain and critically reflect on the role of cultural factors in the design of institutions and incentives, and analyse alternative strategies to formal decision models
4. formulate and implement formal, data-driven models for decision-making situations, including underlying assumptions, limitations, and computational strategies
5. analyse and evaluate investment and action alternatives in situations characterised by uncertainty, incomplete data, and a combination of monetary and non-monetary values
6. analyse and assess trade-offs between exploration and exploitation in data strategies for decision-making, with attention to efficiency, risk, and reliability
7. apply and reflect on their own decision-making and their ability to communicate and work in a group. This includes independently deepening their knowledge in a relevant field, communicating complex concepts in decision-making, and giving and receiving constructive feedback in academic discussions
8. apply and reflect on their decision-making methods and their ability to communicate and work in a group in decision-making processes
9. identify and reflect on the challenges of research ethics when making decisions, including integrity, accountability, responsibility, and potential impact on individuals, organisations, and society.