Program structure and content
Data Driven Decision Making
In 6 weeks, move from separate analyses to robust, data-driven decision-making processes in your organization.
In this master's module, you will explore how to structurally link data to the way your organization makes decisions. You will explore the full spectrum of analytics and see how data quality, governance, and visualization lay the foundation for reliable insights. You will then look at the practice of decision-making: how to make choices under uncertainty, how to limit bias and noise, and how to ensure that analyses actually influence strategy and operations.
You will learn to make decision-making processes explicit: which decisions are strategic, which are operational or tactical, which criteria are important, and what alternatives are available? You will also examine where automation, decision rules, or decision agents can add value—and where human judgment must remain central.
Finally, you will translate the insights into your own organization. You will work on a concrete case in which you will refine an existing decision-making process or develop an initial concept for a data-driven decision support system. In this way, data-driven working will grow from separate analyses into a recognizable and repeatable decision-making process.
In six weeks, you will complete an online kick-off, three intensive on-campus days, and an in-depth phase. You will conclude with an assessed assignment based on your own organization or customer case. By combining theory, frameworks, practical cases, and reflection on your own context, you will develop the insight and skills to structurally strengthen data-driven decision-making.
Online kick-off
During the online kick-off, you will meet the instructors and fellow participants and explore your own issues surrounding data and decision-making. You will receive an overview of the module structure and identify which decisions in your organization are already (partly) data-driven—and where opportunities still exist.
Day 1 – Fundamentals of data-driven decision-making
The first day lays the conceptual and practical foundation. You will explore the entire analytics spectrum, the role of data quality and governance, and the psychology of decision-making under uncertainty. Using recognizable examples, you will examine why dashboards and reports sometimes have little effect on real choices and how you can break through that.
Day 2 – Impact of AI on business and the business of AI
The second day focuses on the bridge between analysis and action. You will learn how to systematically map out decision moments, criteria, and alternatives, and how different forms of analytics can support or (partially) automate this process. You will discuss ethical and organizational questions surrounding automated decisions and reflect on the balance between speed, transparency, and control.
Day 3 – Costs and benefits of AI and implications for organizations and the environment
On the third day, you will work specifically on your own practical case. You will design an improved decision-making process or an initial concept for a decision agent for your organization, and explore what data, roles, and governance are required for this. In peer sessions, you will refine each other's designs and translate the insights into a realistic roadmap for further data maturity.
Deepening after the lecture days
After the lecture days, you will delve deeper into the subject matter with literature, (micro) lectures, and assignments. You will apply models and frameworks to your own organizational context and work step by step toward a consistent design for a data-driven decision-making process or support system.
Assessment of your own practice
You will complete the master's module with an assignment that is directly linked to your work environment and role. In this assignment, you will demonstrate that you can translate the most important insights from the module into a concrete improvement design or roadmap for data-driven decision-making. This means that you will not only leave the module with new knowledge, but also with a substantiated proposal that can be further developed in your organization.
