Solving Complex Problems addresses complex multi actor systems; so called ‘spaghetti situations’ in which everything is connected to everything, and everything influences everything. Situations, for instance, in which innovative new energy technologies emerge into the existing energy system. Or new health technology, medicine, treatments or screening technologies are being developed and society has to decide about whether they should be allowed and what they may cost.

This course has been awarded with the Award for Open Education Excellence in 2015 and has been shortlisted for the Wharton Awards in the category of Hybrid Learning in 2014.

What to do about expanding international airports that have the habit of developing closely to densely populated areas? These airports are believed to contribute substantially to the economy and industrial activity in a country but also generate substantial hindrance when it comes to noise and local air quality. What to do about the multi-facetted and multi-subsystem linkages of the ICT based emergency response system in a country, where at different places decisions have to be made that may influence the safety of people substantially.

In situations such as the above, it is by far not obvious what the best solution is. All people involved have a different idea about what the solution should be. And if you ask them, all these people have different ideas about what the problem exactly is either. If you, as engineer, consultant, manager, policy maker, politician or analyst are in a situation like this, then what to do?

There are multiple ways, but one option that has proven to be very useful is the analytical, engineering like approach of analysing the problem, a methodology for making the problem explicit and rationalising the different potential solutions. In short: analytically based support of decision making, design and implementation of solutions.

  • Analytically based support of decision-making, design and implementation of solutions.
  • How to apply tools like actor analysis, causal modeling, goal trees and means-end diagrams, problem diagrams, uncertainty, decision support and score cards.

The course materials used in this MOOC are available on TU Delft OpenCourseWare and can be viewed and downloaded for free. If you enrol for the MOOC, you will be introduced to up to date techniques in web lectures and webinars. Also you will apply each technique to a case with fellow learners. Ultimately, the combination of these techniques provides a coherent analysis of the problem. If you want to enrol, go to to learn when the next run will start

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Solving Complex Problems by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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