How often do you see customers rebuild/refresh models?

I am interested in how frequently you see customers rebuilding/refreshing models they have deployed in production? Are they using our C&DS automation to schedule these, and do they do any refreshing of their models automatically, or do they have analysts perform these manually?

This is what I see customers wanting:

-Champion challenger

-Self improving models, models learns as new data comes in (ala our naive Bayes, 'self learning' model).  

This is what I see customers doing:

‎-use CADS to store models.  

-manually score

-sometime schedule score

-real time deployment.  

-Never: champion challenger. Reason: a model needs thorough checking when re-created.  Interface in CADS is not on par.  

-Never: refresh: R‎eason: a model needs thorough checking.  Refresh works well, but the storing and replacing the model is too complex because it involves scripting and Modeler/CADS interplay.  

This is what I customers want to do:

Analytical reporting:

-being able to set up an experiment in CADS to keep track of model performance over the lifetime of the model. 

-having a comprehensive (=prebuilt) and configurable model evaluation dashboard.  

Operational reporting:

-being able to see what ‎the model predicts (without knowing the outcomes yet, hence the operational reporting).  

-having a comprehensive and configurable model scoring dashboard.  

In addition: having both abilities working if one has many models in production in a convenient way.  On top of this massive model deployment, having a way to quickly get insight in the model trends and being able to alert the worse performing models.