• Identify and explain a relevant decision-making challenge related to the integration of data and intuition within your own organization or another chosen empirical context
• Demonstrate how the course’s concepts and theories on data-driven decision-making, intuition, bias, and stakeholder integration can be applied to analyse the chosen challenge
• Evaluate and reflect on the theoretical and practical implications of combining data and judgment in decision-making, including limitations, trade-offs, and alternative approaches

In today’s fast-paced business environment, the ability to make informed, data-driven decisions is essential for executives. This course equips participants with the skills to effectively combine data analytics with intuitive judgment, enhancing their decision-making capabilities in complex, dynamic situations. By enrolling in this course, executives will gain a competitive edge by learning how to balance evidence-based strategies with their professional expertise, ultimately leading to better outcomes for their organizations.

In particular, participants will explore the theoretical foundations of decision-making, from rational and evidence-based approaches to the role of intuition and expertise. The course emphasizes practical application through case studies and interactive exercises, enabling participants to apply these concepts directly to their own organizational contexts. A particularly interesting aspect of the course is the exploration of how machine learning and AI are reshaping decision-making structures, and how executives can leverage these technologies while maintaining their unique human judgment.

After the course you will be able to:

• Make well-grounded decisions in complex and uncertain situations by combining data insights with professional judgment.
• Assess when to rely on data-driven analysis and when to draw on experience-based intuition in real organizational contexts.
• Translate analytical outputs into actionable decisions that align with organizational goals and constraints.
• Identify and mitigate biases and blind spots in both data-driven and intuitive decision processes.
• Communicate and defend decisions effectively by articulating the interplay between data, assumptions, and judgment.

Key themes in the course

• Foundations of rational, data-driven, and behavioural decision-making.
• Evidence-based decision-making: opportunities and limitations.
• The role of intuition in executive decision-making.
• Combining data and intuitive judgments in complex decisions.
• The impact of AI and machine learning on organisational decision-making structures.

• Classic and basic theory
• Teacher’s own research
• Models

• Development of research questions
• Data collection
• Analysis
• Discussion, critical reflection, modelling