Complex Problem Structuring for Socio-Technical Systems
A systematic approach to analyzing complex problems by integrating social, technical, and systemic factors for comprehensive solutions.
A systematic approach to analyzing complex problems by integrating social, technical, and systemic factors for comprehensive solutions.
This course teaches advanced techniques for analyzing and structuring complex socio-technical problems. Participants will learn to transform 'poor' problem descriptions into 'rich' ones, using tools and approaches designed for policy, regulatory, and governance decisions. The curriculum covers problem demarcation, multi-actor analysis, system analysis, and methods for identifying and managing deep uncertainty. Students will focus on socio-technical systems, where social and technical complexities are interdependent, such as energy transition, climate change, and sustainable cities. The course emphasizes the importance of considering multiple actors with conflicting interests, fast technical developments, institutional fragmentation, and uncertainties. By the end, students will be able to embrace complexity and apply structured approaches to various real-world complex problems.
Instructors:
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What you'll learn
Identify characteristics of complex problems and socio-technical systems
Structure problems iteratively using various instruments and approaches
Conduct problem demarcation, actor analysis, and means-end analysis
Create and interpret systems diagrams for complex situations
Analyze and incorporate uncertainty in the problem structuring process
Apply complex problem structuring techniques to diverse case studies
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 5 modules in this course
This course provides a comprehensive introduction to complex problem structuring with a focus on socio-technical systems. The curriculum is divided into five modules, each addressing key aspects of problem structuring. Module 1 introduces the characteristics of complex socio-technical problems and their implications for problem structuring. Module 2 covers problem structuring techniques and means-end analysis. Module 3 focuses on multi-actor analysis, considering various stakeholders and their interests. Module 4 delves into systems diagrams and boundary setting. The final module addresses future uncertainties and how to manage them in the problem structuring process. Throughout the course, students will apply these concepts to various case studies, developing practical skills in analyzing and structuring complex problems in fields such as energy transition, climate change, public health, and urban planning.
Understanding complex socio-technical problems and the implications for problem structuring
Module 1
Problem structuring and means-end analysis
Module 2
Multi-actor analysis
Module 3
Systems diagrams and boundaries
Module 4
Unlocking the future: identifying and managing uncertainty
Module 5
Fee Structure
Instructors
1 Course
Expert in AI-Based Decision Support and Environmental Policy Analysis
Jazmin Zatarain Salazar serves as an Assistant Professor in Policy Analysis at TU Delft's Faculty of Technology, Policy and Management, where she also co-directs the Hippo AI Lab. Her academic journey includes a Ph.D. in Civil and Environmental Engineering from Cornell University and postdoctoral research at Politecnico di Milano's Environmental Intelligence lab. Her research integrates hydrologic sciences, artificial intelligence, and multi-objective optimization to address complex water and environmental challenges. She specializes in uncertainty analysis, transboundary river basin management, and model-based decision support, focusing particularly on integrating distributional outcomes in environmental policy decisions. Through her work at the Hippo AI Lab, she develops AI-based decision support systems for water and climate-economy systems, emphasizing the importance of understanding uncertainty in problem structuring and modeling for environmental policy making.
1 Course
Expert in Telemedicine and Frugal Healthcare Innovation
Christopher Adlung serves as a Ph.D. candidate in the Policy Analysis section at TU Delft, focusing on telemedicine and frugal innovation in healthcare. His research investigates how telemedicine can support the adoption of frugal innovations in low-income countries like Togo, Uganda, Nigeria, and Kenya. His multidisciplinary background includes a BA in Business Administration & Accounting from Ludwigshafen University, an MSc in Service Management & Engineering from Karlsruhe Institute of Technology, and a Master's in Organizational Psychology & Leadership from Pennsylvania State University. With over twelve years of professional experience in telecommunications and consulting across Europe, Africa, USA, and Indonesia, he brings practical insights to his academic work. As a research theme leader at TU Delft, he supervises Master's theses and teaches scientific thinking, writing, and qualitative research methodologies while serving as an ambassador for health initiatives. His polymath mindset combines systemic, scientific, creative, and philosophical approaches to address complex socio-technical challenges in healthcare accessibility.
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