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Strategy chunking

When working with strategies in NLP it's important to break the strategy down into appropriately sized and organised chunks.

If you chunk too small when detecting / eliciting strategies you'll get bogged down in detail and complexity.

If you chunk too big the level of detail will be insufficient to successfully elicit and replicate the strategy.

How then do you know when you've chunked at the right level? That's a very good question!

As a rule of thumb most strategies can be described elegantly in about four or five steps. So if you have more than five steps/chunks the chances are that you chunked too small.

Say, for example, that you had been in the company of a person whom you considered particularly skillful in the art of public speaking and that you wished to elicit their strategy for doing this. Would the starting point of your strategy elicitation be to find out how this person uses their breath, lips, teeth and tongue to form the individual sounds which combine to form the words they speak, as discussed earlier in the Early Strategies section?

If it were you'd be chunking too small because:-

As we come at this from the opposite perspective things will become clearer.

If a strategy that you've elicited fails to produce the expected outcome when you run it, and that strategy has fewer than four steps, it's entirely possible that you chunked too big and thus missed details or steps vital to the effective operation of that strategy.

Using the example above let's say that you'd asked this person the very important question - 'How do you do that?' and that their response was something like:-

Given these three pieces of information could you successfully utilise this person's strategy to replicate the same results that they produce? You could try. You could be very lucky and produce the same results which would suggest that the chunk size (3 chunks) in this instance was just right.

On the other hand the results that you get could differ greatly from what you expected which would suggest that the chunk size is too large and more detail (in smaller chunks) is needed. In cases such as these Meta Model questions are a great tool for recovering the required level of detailed information.

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