Good decision-making rests on robust analysis, and robust analysis must use specific methods. It does not matter whether the purpose is purely academic or applied, such as for public policy guidance or in a business context.

I started my career as a researcher at the University of Heidelberg while doing my Ph.D. in political science. Although I subsequently decided to leave academia to pursue an international career, the importance of research methodology stuck with me. No matter what project I was responsible for, I have always striven to apply rigorous analytical standards.

At International IDEA and the World Economic Forum, I led initiatives that produced insight into global challenges. At Frankfurt School, I’m responsible for a large business unit that I manage using clear performance indicators. We always base strategic decisions on thorough analysis.

I’ve also taught research methodology in courses and workshops to students at Frankfurt School.

I’m generally agnostic as to which method to use. I believe that methods are like tools. The objective and the purpose determine which one is suited best, not vice versa. My doctoral thesis was a comparative study with a limited number of cases (Small-N). More recently, I have relied more on quantitative analysis. For statistical analysis, I like to draw on the powerful capabilities of Python.

Analyze