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October 1, 2013

ReLearning Strategy with Big Data

Cycle times of processing the typical events for generating new scenarios are accelerated by many orders of magnitude when using the tools now affordably available for data and information analysis.

However, the main objective remains the same -- to arrive at a model that will provide the argument for what positions to take with regard to obtaining targeted beneficial impacts.

The gap between where we think we will need to be and where we think we will probably be is the starting point of strategy.

At that starting point, there are the current potentials (based on logical relationships), and there are the current expectations (based on plausible models).

When an accepted set of potentials are organized into an argument supporting an expectation, a strategy can result as a prescription based on that argument.

In the end, models provide an explanation of why certain combinations of patterns are a useful representation of the experience of reality. The technique for creating the representation can be adopted as a way to “simulate” or “predict” speculative alternatives that are either concurrent or not yet present. This now can be done more frequently than ever before, in a comprehensive way

Re-Learning Strategy with Big Data.jpg

The full discussion of the transformation of strategy brought on by Big Data is provided in this following notebook:

Re-Learning Strategy with Big Data.pdf

Posted by Malcolm Ryder at October 1, 2013 10:15 PM