Chunking as a NLP strategy can be useful in many occasions. Have you ever been caught in a negotiation situation where both parties refused to give concessions? This is a common case in diplomacy where politicians try to outwit one another for a better deal.

More often than not, this sort of situation arises because opposing parties are debating and arguing at a level of thought that is similar in its nature. For example, when you choose to decide whether to eat out of not, an agreement might not be so easily reached if you and your children look specifically at the pros and cons of eating out only. Both sides will probably present good points for each case. When such situation occurs, chunking as a NLP strategy can be used to resolve it.

What is Chunking as a NLP Strategy?

Chunking as a NLP strategy simply refers to raising or lowering the level of thought on a particular subject. When we ‘chunk up’ we are basically bring a bigger perspective or view to the subject under discussion. For example, let’s pretend that the subject of discussion is about cars. When we ‘chunk up’ we view cars as a type of vehicle. That is a higher classification of cars or a bigger perspective. If we ‘chunk up’ further, we can consider vehicle as a form of land transport.

When we ‘chunk down’ using chunking as a NLP strategy, we are zooming into greater and more specific details of the subject. In the case of the cars, when we ‘chunk down’ from cars, we could be looking at a specific brand of car like Honda. Chunking down further can lead us to discuss about the type of Honda cars and so on.

Chunking as a NLP strategy can also be used laterally at any level of discussion. What are the alternatives when we ‘chunk laterally’ about cars? Some answers could be looking to an alternative to cars like vans, trucks and so on.

How can Chunking as a NLP Strategy be Used?

With this understanding of chunking as a NLP strategy, how can we use this tool of NLP? There are four main ways to use chunking as a NLP strategy in general;

1.      Coaching Situation

When using chunking as a NLP strategy in coaching, we commonly refer to the Meta-Milton Model. Meta is the chunking down aspect whilst Milton is the chunking up aspect. Whenever your clients in coaching enter problems, chunking can often solve the problem by reframing the problem in a higher or lower perspective. For example, if your client cannot stay in a relationship long enough, perhaps examining a larger cause of what does she want in a relationship can offer more insight into the problem.

2.      Negotiation or Mediation Situation

Chunking as a NLP strategy is also very useful here. In our earlier example on whether to eat out or not, instead of just looking at the pros and cons of eating out, perhaps if the negotiation comes down to a specific eatery or restaurant, the problems become easier to resolve. So if dad suggests a dirty and oily hawker centre for eating out, the kids might get turn off immediately. Problem solved!

3.      Thinking Situation

When we come to thinking of ideas and brainstorming for innovative solutions to problems, it will be of great help to adopt some form of lateral chunking as a NLP strategy. Thinking laterally allows us to generate alternatives along the same thought level that could lead to unique and revolutionary solutions. Once you have done enough lateral chunking, focusing on each new solution by chunking up and down becomes the next step to really crystallize detailed solutions.

4.      Motivation Situation

Sometimes we get into a motivation trap whereby we are unable to find solutions to the problems we face. When such situations occur, making the problem simpler by chunking down can help simplify the problem. Easier problems become more solvable and this sort of progress will ensure that motivation does not fail.

Your Experience Using Chunking as a NLP Strategy

Chunking as a NLP strategy is a reasonably simple tool and method to apply. Once again, it is probably a process we often undertake but do not notice. Making chunking as a NLP strategy conscious in our thinking will equip us properly to overcome our challenges.

What are some of your experiences with chunking? Have you used chunking as a NLP strategy in daily and practical applications before? What do you think of chunking as a NLP strategy?

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