Data-driven Decision Making 5 credits

In an increasingly data-saturated world, the ability to make sound decisions based on evidence is essential. Organisations across industries rely on professionals who can interpret data, manage uncertainty, and translate analysis into meaningful action. This course addresses the growing demand for decision-makers who combine analytical precision with strategic thinking. You will explore how data can inform choices in complex, real-world business environments, where stakes are high and information is often incomplete. You will examine core principles of decision theory and learn how individuals and organisations make choices under uncertainty. The course introduces frameworks for structuring decision problems and selecting appropriate analytical approaches. You will work with both structured and unstructured data, gaining practical skills in data cleaning, organisation, and visualisation. Key methods include descriptive statistics and predictive modelling, guided by a responsible use of AI and applied through real-world examples from marketing, sales, supply chain management, and customer relationship management. By the end of the course, you will be able to evaluate analytical outcomes, draw well-supported conclusions, and communicate recommendations with clarity and confidence. You will develop the ability to assess the quality of data and models, defend your decisions, and contribute to evidence-based strategies in professional settings. Whether you pursue a role in analytics, consulting, or management, this course will prepare you to engage critically with data and make informed decisions that create value. <br> **Connection to Research ** This course is closely connected to contemporary research in data analytics and decision science. It introduces you to key research methods used in data-driven decision-making, including statistical analysis, predictive modelling, and data interpretation. You will critically assess the assumptions, applicability, and ethical implications of analytical methods and tools in order to develop the ability to evaluate research-based evidence. Practical exercises and case analyses offer opportunities to apply research findings to complex business problems and reflect on the limitations of data and models. JIBS research on entrepreneurship, renewal, and ownership increasingly draws on data-driven approaches and advanced analytics. The course specifically offers insight into how these approaches support evidence-based decision-making in entrepreneurial and organisational contexts. **Connection to Practice ** The course emphasises practical skills and application of data-driven decision making in organisational contexts. By working with examples and case material you gain relevant experience of how organisations use data and analytical tools. The course focuses on real-world situations where information may be incomplete, uncertain, or ambiguous. By working with such cases and datasets, you will develop the ability to evaluate analytical results, assess their limitations, and use data responsibly to support decision-making in professional settings. **Connection to Ethics, Responsibility, Sustainability (ERS) ** Ethical and responsible use of data is an important dimension of data-driven decision-making. The course addresses ethical considerations related to the collection, analysis, and use of data, including issues such as data quality, bias in algorithms and models, transparency of analytical methods, and the responsible use of artificial intelligence in organisational decision processes. Throughout the course, you will examine how analytical choices can influence decisions and outcomes, and how limitations in data or models may create ethical risks or unintended consequences. ERS perspectives are integrated through discussions, analytical tasks, and case-based exercises in which you assess the ethical implications and broader societal impacts of data-driven decisions. This helps you develop the ability to use data and analytical tools in ways that are not only effective, but also responsible and mindful of their potential impact on organisations, individuals, and society.