Are "wrong" models useful? A qualitative study of discrete event simulation modeller stories

Little is known about models deemed "wrong" by their modellers or clients in Operational Research (OR). This paper aims to improve our understanding of "wrong" Discrete Event Simulation (DES) models based on empirical evidence. We interview 22 modellers who describe projects where modelling did not go as expected and explain how they dealt with those situations. This resulted in 54 stories reporting that a model was identified "wrong" either by the modeller, the client or both. We perform a qualitative text analysis of the stories to identify the factors that define a "wrong" model as well as potential uses of "wrong" models. The results show that some models even though considered "wrong" may still be useful in practice and provide valuable insights to users and modellers. This study offers practical suggestions for users and modellers to consider when dealing with a model that is considered "wrong".