Big Data Reduction 3: From Descriptive to Prescriptive

Hello Larry,

Thank you for commenting.

First of all, predictive analytics can go way beyond geo-location. Have you read the previous installment in this data reduction mini-series? There are a lot of very interesting emergent predictive analytics. In my previous post, the 2 non-trivial examples I gave was influence scoring and sentiment analysis. But there are many more. If it is of interest, maybe I will write a post summarizing some of the more interesting predictive analytics I've seen. Let me know...

Second, prescriptive analytics does is not the same as automation. Remember the function of prescriptive analytics is to guide decision making. Not to make the decision for us. Ultimately, human judgment is required. Moreover, what recommendation you get will depend a lot on how well you can specify the desired outcome.

But you are right in that individual behaviors are very difficult to predict. But collective behaviors are still very predictable. And for business, we rarely rely on single user behavior to monetize, especially for consumer brands. After all, prescriptive analytics is not new to business intelligence systems. They've been around quite a bit.

Back to the individual vs. collective behavior. Even if we predict barely above chance (say only 50.1% of the population correct and 49.9% wrong), if the population is large enough, that small differential predictability can still result in a huge gain for the business. That is in fact what people do in Wall Street, even though some of them are not doing such a great job now.

Moreover, the feedback loop allow you to adapt with new data as people change. Again, if 1 person change, that is not a concern for the prescriptive system. Until a large enough population change, and change in the same way that it affects the outcome, then the data would have inform the decision maker that something has change. Then it is the decision maker's choice whether s/he like to change his course of action.

Alright, I hope this address some of your concern. If you still have question, I'm happy to discuss and dig deeper. That is how we learn and improve.

See you next time.