The principle of parsimony refers to the methodological principle that a model should be kept simple, or in general that simpler models should be preferred to models that include more variables. This principle is advocated in virtually every textbook on methodology and is evidenced in daily practice in (urban) modelling. For example, there is a constant quest to find simple concepts and models for complex phenomena that explain them well. There is a tendency to include only those variables that are statistically significant in models. Models that are elegant (in many cases seen as representations in simple mathematical equations) seem to be preferred implicitly or explicitly.In addition to these arguments in academic research, the overriding argument in the literature on decision and planning support systems seems to favour less complex models that are easier to understand by practitioners and hence are more likely to be applied.In this paper I will argue why, in contrast to physics, the principle of parsimony may be less appropriate in spatial sciences, with a focus on simulating human behaviour. Moreover, I will argue that it should not be a key consideration in developing planning support systems.