There are different types of data mining models, so definition of good quality model will depend of type of the model.
Another angle of what constitute good model comes purely from a business perspective. Near perfect models from a statistical perspective are of no use they cannot be implemented for whatever reason. On the other hand - we may have models that fall short of statistically sound model – but who can still help us do things better than what we are able to do in absence of such model.
And lastly – main question remains – how does benefits generated by the model compare with its cost of production and implementation? Benefits of the good model always outweigh its cost.