Big Data Reduction 3: From Descriptive to Prescriptive

hi Michael,

Now that is the kind of big thinking I like.  And, I fully understand your point about audience.

Next, we must discuss, unexpected, and unpredictable events, They will always exist, and have an effect on outcome.  In your example, planning out living in the south of France, if the subject were to be belessed with a child, or experience an accident, for example, things could change the outcome.  Or, one could serendipitously change their mind.

Predicting nature's course is something we can approximate, but I do believe we're a good bit away connecting the human genome, neuroscience, and ultimate final behavior. 

Two individuals could plan out that they will win the Olympic 400m relay. But this depends on others team members, and individual human performance, weather, and other environmental factors - and thus can't fully be prescribed analytically.  And, of course, there is the case where there is one outcome (winning a foot race at the Olympics) that is shared by two individuals. The computations will happen, but only one will win.

I like the big examples of prescriptive, with respect to decision making, social, marketing as strategy (a la Kumar), and business. The distribution curve continues to live and thrive there, and prove  we can create value through prescriptive analytics.

All the best - 

Andrew Stein