Why should we develop simulation models in pairs?

The conventional approach to model construction for simulation is to focus on a single model and follow a more or less structured development cycle. Why we put in twice the time and effort to develop two models rather than one? The answer lies in the fact that like most greedy heuristics, short-sightedness at the beginning may be much more costly in the end. This talk will champion the cause of the pairs-of-models (perhaps families of models) with discussion of multiresolution modeling. We show how the pair-of-models approach leads to be better results overall than construction of a complex model followed by a simpler model developed subsequently by necessity under stress when complexity overwhelms. Benefits include the ability to perform mutual cross-calibration, avoiding the usual difficulties in harmonization of the underlying ontologies as well as ability to better reconcile and correlate predictions of referent system outcomes.