Purpose and description of the course
In the current competitive business environment, decision makers need to make decisions quickly and effectively based on abundant data. Making decisions includes many considerations such as weighing risk, understanding the specific situation encountered, identifying available options as well as considering long-range implications for the organization.
This course is about understanding and applying data-driven decision making while taking into consideration the decision maker’s experience and expertise. By knowing how data-driven decisions are actually made we can learn how various decision techniques and strategies improve the quality of decisions. Some of these techniques and strategies are founded on mathematical models or computer software like algorithmic decision making; others build on theories about awareness and mindfulness. The course presents a wide range of such techniques covering the different theoretical approaches to decision making.T
he goal of this course is to relate our knowledge of how decisions are made to a number of techniques and strategies for improving decision making. This will enable participants to support and improve their own decision making as well as to understand the decision making of others. We view the decision maker as a socially, economically, historically, and materially situated human – who increasingly uses algorithms for decision making and struggles with unrealistic demands and therefore has developed (individually and socially) heuristics, habits, routines, practices, and conventions which sometimes lead to algorithm aversion.
By the end of the course, students will be able to reflect on the complexities of decision making in organizations, their own decision styles and personal dispositions. They will be able to make decisions more deliberately and systematically and will be able to use decision analysis techniques, intuition and group processes, integrate their values into their decisions.
- Understand and apply models and mechanisms for decision making in strategic decisions
- Identify unconscious biases when making decisions and solving problems and reflect on common decision making traps that lead to fallacious reasoning and unfavorable outcomes
- Identify criteria for when to trust intuition and when to push for analysis and evidence-based decisions
- Reflect on how to make strategic decisions involving multiple (and changing) goals and stakeholders
Key themes in the course
- Foundations of rational, data-driven and behavioural decision making.
- Expertise based Intuition
- Group decision making
Your learning outcome
In this course, you will learn to:
- How data-driven decisions happen in organizations
- How complexity and uncertainty impact data-driven decision making
- How to analyze problems and issues in preparation for decisions
- When to be data-driven and when to trust your intuition
- How to account for multiple goals and stakeholders in data-driven decision making
Who should attend this course
The course targets different levels of managers, specialists, and analysts who are involved in organizational decision making. The course is also relevant for professionals who would like to understand the challenges and opportunities of data driven decision making in organizational settings.
