I have very strong opinions about this. We have been implementing predictive models for forecasting and pipeline management for over 10 years. Things have not changed that much.
Success comes from:
a) Using it as a carrot, not a stick
b) Change management
c) Process
What's less important: How good the model's predictive score is. Our models have had >90% precision, but that's not what have made them successful