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.

Automated summary

This paper investigates wrong Discrete Event Simulation (DES) models based on empirical evidence by interviewing 22 modellers. It analyzes the factors that define a wrong model and the potential uses of wrong models. The study suggests that even wrong models can still be useful and provide valuable insights. Practical suggestions are provided for users and modellers dealing with wrong models.