“We learn from history that we do not learn from history.” said Hegel, implying we humans keep repeating the same mistakes over and over again, due to our inability, or unwillingness, to learn from the past.
Predictive and prescriptive analytics (defined here) comes with a great promise. It is all about learning from history, and to do the smartest thing based on these learnings. Your statistical models can find patterns in the data that the human brain is incapable of. Add Prescriptive analytics and you will also have substantiated suggestions for your next best action based on these learnings. Hegel would be content; we reduce the risk of repeating past failures, and we use our historical observations as a means to do better.
But the dependency on historical events also reveals the weakness in using an algorithmic approach to foresee and shape the future. The data and the methods can be improved over time, but the data itself will never come from the future (obviously…). You will get as close as real time (what is happening right here and now), but that´s it.
Models applied on historical data can predict irregular or exponential future development, but they will never foresee a disruptive change. Just as we need the human brain to interpret and evaluate the results of our statistical analysis, we also need the human creativity and genius to come up with the brand new ideas. Those ideas are disruptive in the sense that nothing in the historical data can anticipate them. Leave disruptive innovation to a statistical model and what you really get is random guesses performed by a machine.