To address point 3, the answer, obviously, is no. Just about every human enterprise is based on a simplified model at some point: cooking, building, interpersonal relationships all involve humans acting on some kind of data + assumptions. No one has ever constructed a model that they did not intend to make use of. To assert otherwise is idle pedantry.
It is much more interesting and enlightening, and useful to ask when inexact models are not useful, why they fail in their usefulness, and what happens when we rely on models that turn out not to be useful. Any researcher, whether in academia or industry, has to ask that question shrewdly and often.
I don't think the question can be answered in general, but the principles of error propagation will inform the answer. Inexact models break down when the behavior they predict fails to reflect behavior in the real world. Understanding how errors propagate through a system can help one understand how much precision is necessary in modeling the system.
For example, a rigid sphere is not usually a bad model for a baseball. But when you are designing catcher's mitt, this model will fail you and lead you to design the wrong thing. Your simplifying assumptions about baseball physics propagate through your baseball-mitt system, and lead you to draw the wrong conclusions.