Perfect Data and Perfect Predictions

An obvious conclusion: you never get perfect answers.  Analytics depends upon the correctness if the data in context, AND the power of the model being used.  Bill Franks covers some of the landscape:  

" ... Many organizations attempt to achieve “data nirvana” by having 100% complete information for any given business decision. In the customer analytics space, this is sometimes referred to as a “360 degree view of the customer.” However, we really never know everything about our customers. What we call a 360 degree view is really just the most complete view we have at any given time. All of the information we are missing must be inferred or assumed through analytics. The more complete our picture, the less we have to infer, but realistically we are usually inferring far more information than what we have in our possession. ... " 


I further suggest that your success from the value of the results you get is dependent on what you do with the always somewhat incorrect results that you get from the model.   This often depends on how the results are integrated with the decision model. I point again to my simple decision circle model.  Its
not a 360 degree view, its how it all fits together.