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Continued model-based decision support is associated with particularchallenges, especially in long-term projects. Due to the regularly changingquestions and the often changing understanding of the underlying system, themodels used must be regularly re-evaluated, -modelled and -implemented withrespect to changing modelling purpose, system boundaries and mappedcausalities. Usually, this leads to models with continuously growing complexityand volume. In this work we aim to reevaluate the idea of the model family,dating back to the 1990s, and use it to promote this as a mindset in thecreation of decision support frameworks in large research projects. The idea isto generally not develop and enhance a single standalone model, but to dividethe research tasks into interacting smaller models which specificallycorrespond to the research question. This strategy comes with many advantages,which we explain using the example of a family of models for decision supportin the COVID-19 crisis and corresponding success stories. We describe theindividual models, explain their role within the family, and how they are used- individually and with each other.

Model Families for Multi-Criteria Decision Support: A COVID-19 Case Study