I recently ran onto a short paper (speakers notes, really) by Joshua M. Epstein titled "Why Model?" I spend a lot of my life answering that question and I am excited by Epstein's concise, reasoned explanation. He boils it right down to the basics:
- We're all modelers, but most of our models are implicit, not explicit.
- Sometimes we model to predict.
- Sometimes we model to explain.
- And there are at least 15 other good reasons to build explicit models . . .
In some sense Epstein's position on modeling is a presentation of the scientific worldview and its moral advantages. So, mixed in with some really concrete reasons (eg: #2 -- Guide data collection) are some seemingly more esoteric objectives (eg: #6 -- Promote a scientific habit of mind).
Alas, business, financial, and other organizational leaders are mostly not swayed by a "scientific approach". I find that business and organizational clients generally need an additional level of motivation to justify an investment in explicit modeling. Usually, for the business person it is not enough to believe that an investment in explicit modeling will accomplish any of Epstein's 16 reasons. The business person wants to know What Then? Often phrased as a somewhat derisive "So What?"
For most business leaders explicit modeling has to be linked to some decision making or problem solving process. And, unfortunately, this often boils down to a focus on prediction at the expense of the other 16 reasons that are also part of excellent decision making and problem solving.
If you like this paper by Epstein try his book Generative Social Science: Studies in Agent-Based Computational Modeling. It's one of my favorites.