Steve Andreas > Articles > Modeling Modeling

Introduction

In a recent article, Robert Dilts introduced a statement by Carmen Bostic St. Clair and John Grinder proposing a distinction between “NLP modeling” and “Analytic Modeling.” Every field progresses by making new distinctions, so it is always interesting to examine them to find out what they can offer us, and how they fit in with existing knowledge. St. Clair and Grinder write:

NLP Modeling, in the creation of the initial models that founded the field of NLP, at present and in the future of NLP, references an appreciation of and respect for two criteria that apply to modeling in NLP:

1. The suspension of any taxonomic and/or analytic attempt (all f2 transforms as described in Whispering in the Wind, see www.nlpwhisperinginthewind.com) to understand consciously the patterning of the genius or model of excellence during the acquisition stage of patterning and until the following criterion is met.
2. The modeler must demonstrate the ability to reproduce the patterning of the model in parallel contexts and in such contexts elicit roughly the same responses from client with roughly the same quality and time commitment as the original genius or model of excellence prior to beginning the challenging and rewarding activity of codification of the patterning demonstrated by the modeler.

We further note that all modeling work products failing to meet these criteria are to be classified as some other logical type of model—we suggest Analytic Modeling as a general term for such work products; employing the patterning and the distinctions available in the technology of NLP applications but failing to respect the definition of NLP modeling. (6, p. 2)

What St. Clair and Grinder call “NLP modeling” is something that every normal child does when they play “dress up,” learn language or acquire any other behavior unconsciously through observation and imitation. With the discovery of “mirror neurons,” we are learning more about the neurological basis of how we learn new behavior in this way. Because this process is not unique to NLP, and because I believe that other kinds of modeling deserve to be included in the category “modeling,” in this article I will use the term “unconscious acquisition” for this process.

I am not sure that the term “analytic modeling” adequately describes the wide variety of different modeling processes that have been used in the field by means other than unconscious acquisition. The term “analytic” sounds very “mental,” as if there was no utilization of observation, and behavioral testing, or unconscious participation, etc. in the process. As long as it is clearly understood that this term encompasses a broad spectrum of modeling processes, I am willing to use that term until someone suggests a better one.

Paragraph 1 above requires that acquisition is done unconsciously, prior to explicit and conscious codification. Paragraph 2 specifies the results: that the modeler can duplicate the pattern of excellence demonstrated by the expert model.

The first criterion specifies the process of creating a model, while the second criterion specifies the outcome: the modeler can duplicate the pattern of excellence.

The field of NLP has always been focused on outcomes, and it has always valued having as wide a range of choices as possible in reaching those outcomes. The test of a good model should be the outcome that it enables, not how the model was derived.

The outcome of a modeling process can be evaluated irrespective of how the modeling was done. Whether someone models consciously or unconsciously, receives a model in a vision, or reads it on the side of a dill pickle, is completely irrelevant to the question of how effective a model is—even if the first two methods have a somewhat better “track record.”

In the past, St. Clair and Grinder have only specified a more inclusive criterion based solely on results: that the modeler can use a model to transfer a pattern of excellence to someone else (not necessarily the modeler). For instance, St. Clair and Grinder write:

Models are simpler creatures; the sole criterion (at least thus far accepted) for their evaluation is,

Does this pattern/model work—that is, is it learnable and upon learning it, does the learner display behavior similar in results and quality to the source from which it was extracted. (7, p. 55)

As we stated previously, the principal criterion for evaluating an NLP model is whether it works—this seems roughly equivalent to two issues:

1. Is it learnable?
2. Does it lead to the learner producing results congruent with the original source of the model? (7, p. 159)

Notice that these statements, published only four years ago, state that the “sole” or “principal” criterion of the effectiveness of a model is the outcome—that a skill can be successfully modeled and transferred to someone else.