What steps can be used to work on a QA if a predictive...

Here is a way to handle the QA process efficiently:

Firstly, partition the data into three different sets Training, Testing and Validation.
Secondly, show the results of the validation set to the business owner by eliminating biases from the first two sets. The input from the business owner or the client will give an idea of whether the model predicts customer churn with accuracy and provides desired results or not.
Data analysts require inputs from the business owners and a collaborative environment to operationalize analytics. To create and deploy predictive models in production there should be an effective, efficient and repeatable process. Without taking feedback from the business owner, the model will be a one-and-done model.

What steps can be used to work on a QA if a predictive model is developed for forecasting?