A natural language processing (NLP) strategy is part of the triumvirate of strategies critical to managing a modern enterprise. First and most critical is the corporate strategy. A great corporate strategy instantiates a value vector of action for the company. Next comes the marketing strategy, how the company communicates the value vector internally and to the world. The best marketing strategies elicit highly motivating stories. And then comes the NLP strategy, how the company will ascertain the success of the first two strategies.

Why Use Natural Language Processing?

But why use natural language processing, why not some other metric? Modern business is made of ideas. Very few things are tangible in modern workplaces. Many times, we think our processes are tangible and we measure them as if they were. But process is almost always an abstracted simulation of some system. Usually, the process assumes that the system is simple. Typically, this is not the case, as many systems in a modern enterprise are complex. Also, we don’t have any idea how abstracted our measures are from what is going on in the enterprise. If your process can make predictions about data, information or processes tangential to the process’s vector, then your process is probably not abstracted. Can any metric in your customer relationship management process make a high confidence prediction about some aspect of your Agile process? Shouldn’t it? A sales leads to work doesn’t it? More than likely, none of your processes can make predictions about anything outside of their own makeup.

If modern business is made of ideas, and ideas are communicated via conversations, then the least abstracted data is language based. Coupled with the notion that the real value of the enterprise is created by the shepherding of ideas, everything else in an enterprise is metadata. Ideas in movement provide ground truth. In a powerful natural language processing strategy, ideas in some organized form are the base taxonomy for every data element in the enterprise. In this way, you know the abstraction levels of every process. You know how systems are related by the network of your ideas. You can make predictions based on the same information that creates value – ideas.

You need an natural language processing strategy.

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