The following sections summarise over ten years of experience of informal modelling, undertaking formal modelling projects and training modelling. Our ideas are presented as working notes and guidelines rather than a finished article. We intend to keep updating and expanding these notes. Please let us know if you think there is something we should add. All contributions will be credited.
Section 1: Introduction
Section 2: Learning how to do a Modelling Project
Section 3: Defining a Modelling Project
Section 4: Stage 1: Preparing to do a Modelling Project
Section 6: Stage 3: Constructing a Model
Section 7: Stage 4: Testing Your Model
Section 8: Stage 5: Acquiring the Model
Section 9: References
Section 10: Modelling Methodologies
Some of our other articles about modelling on this site:
© 2001-2013, Penny Tompkins & James Lawley
If this is your first attempt at conducting a modeling project (perhaps you are on an NLP Master Practitioner course) remember, your primary outcome is to become familiar with the basics of NLP modelling. Until you have completed your first project from start to finish you will not know what is involved.
Your evidence that you have achieved your learning-to-model outcome will come in four forms, each demonstrating a higher level of competency. In our opinion, demonstrating the minimum criteria specified below fulfils the requirement for NLP Master Practitioner certification and anything else you gain is a bonus.
The MINIMUM is that you:
(a) Demonstrate you have acquired a model of modelling that enables you to:
- Specify, plan and implement your modelling project
- Gather information appropriate to the outcome of the project
- Construct and document a model from the information gathered
- Test model's effectiveness at reproducing the required results.
(b) Describe the difference having learned to model makes to you.
PREFERABLY you will also demonstrate that you can use the model you have constructed to reproduce results similar to your exemplar(s).
CONCEIVABLY, you will demonstrate that you can devise an approach which enables others to acquire your model and facilitate them to acquire it.
ULTIMATELY, you will demonstrate that the acquirers are able to reproduce results similar to your exemplar(s).
We are right behind David Gordon and Graham Dawes when they say:
Modeling is a doorway into the vast storehouse of human experience and abilities, providing access to anyone willing to turn the key. For the individual who pursues modeling, this means:
- Access to an ever-widening range of new experiences and abilities.
- An increasing ability to bring those experiences and abilities to others.
- A finer understanding of the structure underlying unwanted experiences and behaviors so that you know precisely what to change in those experiences and behaviors.
- Ever-increasing flexibility in your experience and responses.
- A growing appreciation of the beauty to be found in the patterns of human experience.
There is an excellent article, Why Model? by Joshua M. Epstein's based on his 2008 keynote address to the Second World Congress on Social
Learning to Model
Modelling, and learning to model, are highly systemic processes. Modelling is a type of learning, and therefore learning to model is 'learning to learn'.
You will realise very quickly that modelling is an iterative process. That is, the results of each activity feed back into other processes, which are modified by the new input. The now modified processes feed forward to the next operation, which feeds back, and so on. For example:
I decide on an outcome for my modelling project. This largely determines the information I gather from my first exemplar. The learning that comes from gathering that information means I change the emphasis of my outcome. Both the revised outcome and the learning from the first gathering of information influences how I gather information from my second exemplar. This in turn may alter my outcome, it may help me to see some gaps in the information gathered from my first exemplar, and will certainly influence how I gather information from my third exemplar, and so on, and so on.
Learning to be comfortable with not-knowing, an abundance of information and ambiguity about what to pay attention to, especially in the beginning of a modelling project are prerequisites for becoming a master modeller.
What constitutes a modelling project?
In general, almost anything that interests or excites you enough to want to acquire another way of doing, being, feeling, thinking, believing, etc. We recommend you go for something that will really make a difference in your life - and/or others' lives too.
Having said that there are some practical constraints (aren't there always?):
You need to have completed enough of your modelling to be able to demonstrate your learning and competence by the end of the programme.
You need to choose a topic where you have sufficient access to your exemplars.
And you need to remember that your primary purpose is to demonstrate you are learning how to model. The project is the primary means by which you will acquire that learning and then be able to demonstrate your learning.
As a minimum, you need to show that you can model patterns of:
One of the most interesting parts of the process will be selecting the 'chunk size' of the project. This will require you to balance your desire to acquire some big chunk skill with the resources available within the time scales. As a general rule, people learning to model initially overestimate what they can achieve (i.e. they bite off too big a chunk) and they underestimate the value of modelling a small chunk in depth.
It's OK to start with a big chunk outcome and refine it as the project progresses. In fact, it is common not to discover "the difference that makes the difference " (Bateson) until well into the process. But when you do, that piece should become the focus of your project.
Modelling is a process whereby an observer, the modeller, gathers information about the activity of a system with the aim of constructing a generalised description (a model) of how that system works. The model can then be used by the modeller and others to inform decisions and actions.
The purpose of modelling is to identify 'what is' and how 'what is' works to produce the observed results - without influencing what is being modelled. The modeller begins with an open mind, a blank sheet and an outcome to discover the way a system functions - without attempting to change it.
[Note: We recognise this is an impossible outcome, since the observer, by simply observing, inevitably influences the person being observed. However this does not affect the intention of a modeller to not influence.]
Steven Pinker in How the Mind Works (p. 21) uses an analogy from the world of business to define psychology, but he could just as easily be describing the modelling process:
Psychology is engineering in reverse. In forward-engineering, one designs a machine to do something; in reverse-engineering, one figures out what a machine was designed to do. Reverse-engineering is what the boffins at Sony do when a new product is announced by Panasonic, or vice versa. They buy one, bring it back to the lab, take a screwdriver to it, and try to figure out what all the parts are for and how they combine to make the device work.
Pinker is not saying that people are machines. He is saying the process of making a model of human language, behaviour and perception can be likened to the process of reverse-engineering.
When 'the system' being observed is a person, what usually gets modelled is behaviour that can be seen or heard (sensory modelling), or thinking processes that are described through language (conceptual modelling). Figuring out how great tennis players serve is an example of the former, while identifying their beliefs and strategies for winning is an example of the latter.
The field of NLP (Neuro-Linguistic Programming) was established as a result of several modelling projects conducted by Richard Bandler and John Grinder. They, in collaboration with others such as Judith DeLozier, Leslie Cameron-Bandler, David Gordon, Robert Dilts did much of the original work to codify the process of modelling sensory and conceptual domains.
[Note added 2012: A more extensive list of collaborators is given in The Origins of Neuro Linguistic Programming edited by John Grinder & Frank Pucelik]
We used sensory and conceptual modelling to study David Grove at work, and as a result discovered a new way of modelling never previously documented which we called Symbolic Modelling.
[See Metaphors in Mind: Transformation through Symbolic Modelling by James Lawley and Penny Tompkins]
Definition of terms
The outcome (of a pattern of behaviour) which can be described in sensory specific terms.
An abstract formulation constructed from the information gathered from modelling the exemplar(s) which when actioned by an acquirer produces a similar class of results.
The person (or group or organisation) that consistently achieves the results the modeller is seeking to reproduce. (In the early days of NLP, also referred to as 'a model'.)
The person who gathers information from the exemplar, constructs the model, and tests its effectiveness, efficiency, elegance and ethics at reproducing similar results (usually by first acquiring the model themselves). Sometimes they then facilitate others to acquire the model.
The person (usually including the modeller) who 'takes
on' the model and attempts to reproduce results similar to
those obtained by the exemplar. The acquisition process usually needs to be facilitated by an accompanying narrative, metaphors and activities.
The process of gathering information from an exemplar, constructing a model, and testing its effectiveness at reproducing similar results (which requires someone to have acquired it). See diagram below.
Both the plan for accomplishing the production and acquisition of a model, and the implementation of that plan. We distinguish five stages that do not necessarily happen in this order:
The process of a person constructing a model of how they
achieve the results they get.
Facilitating the exemplar to
self-model in Stage 2 is often a very efficient way of
gathering information. At Stages 3 and 4, the modeller
self-models as a way of making explicit the out-of-awareness
information they have gathered. During Stage 5, the acquirer
can self-model as a way of monitoring their response to
acquiring an unfamiliar model.
[NOTE: A light bulb moment occurred when we grasped the implication of Michael Brean's statement (at the London NLP Group in about 1993): "All modelling is self-modelling."]
Fundamental or universal ways humans make sense of the world
'Experience' is a unified whole. Yet to be conscious of our map of the world we categorise, evaluate, compare, decide, reason, intuit, etc. These processes require us to delete, distort and generalise (Bandler & Grinder). The most common way to do this is to use one domain - usually our everyday experience of the physical world - to make sense of another domain, usually the non-physical world. In other words, we use metaphor (Lakoff & Johnson). The most commonly used metaphors, which appear to form the basis of all languages, are:
Sequence of events defined by a before, a during, and an after.
of a Sequence of Events
The attributes or qualities by which
perceived, and at the same time, distinguished
things, i.e. how it is known. The content of our
The someone who is perceiving the
something. To do this
the perceiver needs a 'means of
hearing, feeling and other ways of
sensing) and a 'point of
perception' (where the perception
is perceived from). The
perceiver is therefore always in a
certain relationship with
the form of the perceived within a
given context (time and
Perceiver-Perceived-Relationship-Context (PPRC Model)
[Note: This model is
David Grove's "Observer-Observed-Relationship between" and
John McWhirter's "FROM-TO-IN" models.]
Levels are a means of ordering and categorising experience in a hierarchy. They are
therefore usually referred to as 'Levels of' something e.g. Learning, Organization, Abstraction, Explanation, etc.
Your first task is to define your modelling project by specifying its:
What examples of excellence (impressive results) have you noticed other people achieve in the world that you would like to achieve?
Sensory specific evidence of completion
How will you (and others) know you have got these results?
Scope of project - what is included and what is not
Contexts in which you (and others) want the results
Definition of terms
Value to you
What's important to you about being able to consistently reproduce the results specified above?
Who consistently demonstrate the results you want?
What is your evidence that they are exemplars (of excellence)?
How will you get access to such people?
Be careful how you define your criteria for an exemplar. One modeller discovered the organisation that commissioned the work picked their 'top performers' by how much they contributed to the 'top line' (revenue). The modelling revealed that some achieved it at the expense of others – they burned relationships – and were not building the collaborate culture the organisation wanted.
What are you presupposing to be true before you start? (And what happens if you don't?)
What metaphors are you using to describe your project?
How do you describe the project to exemplars' with minimal presupposition and metaphor? (Hint: think context and behavioural examples.)
Your second task, is to plan how you are going to gather the
relevant information. To help you do that see the article: Introducing Modelling to
Organisations (Rapport 40, Summer 1998). It contains a chart, The Who, Why, How, What, Where and
When of Modelling which uses two of Robert Dilts' frameworks to
consider a modelling project from a number of perceptual positions
and Logical Levels.
See also: Choosing a Modelling Project [added April 2014].
Types and reliability of information
It is important to distinguish between different types of information gathered from the exemplar. The following five are in descending order of reliability of information:
i. Observed behaviour with sufficient repetitions to indicate a pattern
ii. Observed behaviour with insufficient repetitions to indicate a pattern
iii. 'Relived' descriptions or role-playing by the exemplar of what they do
iv. Explanation by the exemplar (i.e. the exemplar's conscious model of what they do)
v. Second-hand descriptions
Ways to gather information
The general rule is, the closer (and more often) you get to observe the exemplar achieving the results in their 'natural habitat' the better
While gathering information it is preferable that you first-hand examples of the exemplar's behaviour-in-context so that your questions are asked from within the frames and logic of the exemplar's experience.
High-quality modelling questions tend to:
A Modeller's Perspective
One vital aspect of modelling rarely made explicit is the perspective
adopted by the modeller when modelling an exemplar for an ability or
pattern of behaviour. There are a surprisingly large number of modeller
perspectives to choose from. This blog describes six: A Modeller's Perspective [added Feb 2014].
'Standard' Modelling Questions
Every question directs the exemplar's attention to some where,
when or what in their mindbody map. So it is vital to know the class of information you are going for (i.e. to have a process outcome for
each question; see our article on vectoring) and what your question is inviting the exemplar's
attention to do.
The following are examples of some commonly used modelling questions.
1. Developing pre-existing information
And is there anything else about ...?
And what kind of ...?
And where/whereabouts is ...?
And when ... what happens to ...?
And is there a relationship between ... and ...?
2. Context(s) where and when exemplar commonly achieves the results
Where do you ...?
When do you ...?
Under what circumstances do you ... / does ... happen?
3. Desired outcome(s) the exemplar is attempting to
achieve at the time
For what purpose do you ...?
4. Operations performed internally and externally to achieve the outcome (and what is attended to while performing these operations)
How specifically do you do that?
What's the first thing you do ...?
Then what do you do?
What do you do next?
And then what happens?
And what happens just before you ...?
5. Evidence criteria/test of progress toward and completion of outcome
How do you know you are (achieving) ...?How do you know you have (achieved) ...?
What let's you know to ...?
What determines when you ...?
6. Motivation for having the outcome / Enablers for doing the operations
What's important to you about ...?
What's important about that [answer to previous question]?
What makes it possible for you to ...?
And where does ... come from?
7. Extraordinary / Exceptions. What does the exemplar do in unexpected situations, when they encounter difficulties, interference or distractions - especially when these might affect whether they achieve their outcome.
What do you do if it doesn't go well / doesn't work?
How do you know to stop trying to (achieve) ...?
Under what circumstances would you not ...?
When modelling multiple exemplars for a class of experience, one process for constructing your general model is to:
1. Describe how each exemplar does what they do to get the required results from their perspective and in their words; i.e. construct a model using their representations.
2. Evaluate each model for:
Completeness - It has all necessary
distinctions/components (it is 'full'). It answers 'what else?' questions with "nothing".*
Coherency - The relationships between components adhere to an internal logic (they 'cling together'). It answers 'why?' questions from within its own logic.
Consistency - It will still get similar results even when circumstances change (it 'stands firm'). It can answer 'what if?' questions.
* Evaluate the completeness by the degree to which your model shows 'operational closure'–
3. Compare and contrast individual models component-by-component, step-by-step and function-by-function.
At this point you must separate the information gathered from the
exemplar: It is no longer their model, it becomes your model because
you will represent the information in a different way that meet your modelling desired outomes.
4. Design your own model by one or more of the following methods.
a. Identify similarities across exemplars and construct a composite model based on similarities.
b. Use one of the models as a prototype and improve it by adding/substituting distinctions/components/steps from the other models.
c. Deconstruct the individual models into the function of each component/stage and construct a new model from the bottom-up.
d. Adapt existing models from other contexts that are compatible with the model you are constructing, and use them as the framework for your model (e.g. 'transformational grammar' was the basis for the Meta Model, and 'self-organising systems theory' formed the framework for Symbolic Modelling).
5. Evaluate and improve your model based on the degree to which it is:
Effective - It gets similar results to the exemplars.
Efficient - It requires the least number of steps/components (use Occam's Razor to make it "as simple as possible, but no simpler").
Elegant - It is code congruent, i.e. the content of the model, the manner in which it is presented/coded and the means of getting the results are congruent.
Ethical - The effects are aligned with your and others' existing or desired values.
[NOTE: We borrowed the first three E's from John McWhirter and added the fourth ourselves]
And, evaluate whether distinctions/components are necessary by the degree to which each is:
Effective - contributes to the overall outcome of the model.
Efficient - serves multiple functions.
Elegant - fits into the overall coherency (internal code
congruency) and enhances the consistency (external code congruency)
of the model. It is compatible and aligned with:
The exemplars (Stage 2)
Itself (Stage 3)
The context where it will be tested (Stage 4)
The acquirers (Stage 5)
6. Test, get feedback, adjust model; test again, get feedback, adjust; etc. ...
More on Model Construction
Exemplar's cannot not do their patterns of excellence. A key aspect of modelling is to determine how an
exemplar keeps achieving the same results even under changing circumstances. How is it that they cannot
not do it? How come they don't forget to do it? How do they adjust
for unfavourable circumstances and still get consistently
excellent results? In other words, how come it's habitual? This
information will not be in any of the components, but in the pattern
of relationships between perceptual components. It will be the
circular chains of relationships (Bateson) that keep the pattern
repeating. And your model needs to have comparable circular chains.
You can consider 'Is there any way I can I run this model and do something else?' and 'Under what circumstances would I not get the required results?'. Adapting your model to take these circumstances into account will make it more robust, and more consistent.
Except when, under inappropriate or extreme conditions, the pattern breaks down. At these times a values threshold or ethical issue is often involved. What are those conditions and
what do exemplars do then? Bateson warned that any behaviour taken to extremes will become toxic. What are you own values and ethical limits with regard to using this model? These are non-trivial questions that we believe need to be openly and honestly faced.
Different forms of testing occur throughout the modelling process. The primary purpose of testing is to get feedback from:
The 'real world'
Testing your model with the exemplar
a. Test the components and steps of your model for accuracy.
As you gather information from your exemplar you can recap (in their words) as much of your model of their behaviours, abilities and states as you have. This will give them a chance to evaluate your description for accuracy.
Use your sensory acuity to calibrate that the pace of your description enables the exemplar to 'try on' your model of them so that they can compare it to their own experience, component-by-component and step-by-step.
Every response you get from your exemplar is feedback as to the accuracy of your model. They are the world's expert on their model, and at this stage, that's what you are attempting to reproduce. Anything they think is confusing, illogical, or that doesn't fit, is a signal that your model is incomplete.
b. Test the logic of your model for accuracy
After you have confirmation of the accuracy of your model from the exemplar, you can start to make predictions as to how the exemplar has or would 'run' their model in some as yet unspecified context.
The aim is to test if your understanding of the exemplar's logic enables you to go beyond what you have been specifically told or observed.
Testing your model on your own
'Try on' your model by 'running it through' your system
Can you run the model - from 'before', when the starting Test criteria are triggered, through 'during' the Operations, until the ending Test criteria are met, and on to Exit 'after' (TOTE model)?
Would you expect to get the required results?
Does it all fit together?
Can you break it - under what conditions would you not get the required results?
At this stage you are only acquiring the model 'for the moment'. You are not seeking to integrate it with your pre-existing models, instead you 'put them aside' while you run your tests. In other words, you are self-modelling to obtain feedback from your own system within an 'as if' frame.
Testing the model for real
Having tested your model with the exemplar, and used your own neurology as a test bed, your outcome changes. You now seek to test for the degree to which you can reproduce the required results. You want to compare the results you get with the results your exemplars get. To do this you need feedback from the external world. Two ways to do this are:
a. Prepare safe 'test conditions'
Taking into account the ecology of the wider system and depending on the potential effects of your model not working, you may want to establish some 'test conditions' in which to test the model's efficacy and your competency.
b. Go 'live'
The ultimate personal test. Can you get similar results to your exemplars under similar conditions? And can you do that consistently and under a variety of conditions? (Steve Andreas has said that when he constructs a new model for change, i.e. a new NLP technique, he has to test it out with 20-30 clients before he is confident he has ironed out the majority of creases.)
Remember, your model may work perfectly but you may not yet have enough background knowledge or experience of running it to get the same results as your exemplars. Acquiring Einstein's problem solving strategy won't make you an Einstein overnight, but you can expect it to give you access to a different way of thinking about problems and to a wider range of solutions than you had before.
Other acquirers testing the model
If your modelling project is for other people (who were not involved in Stages 2-4) to make use of your model, your outcome for testing changes again. Your design for an acquisition process (Stage 5) should include testing by the acquirers. The feedback you want now is: To what degree are the results the acquirers get similar to those achieved by the exemplars.
And to reiterate: Test, get feedback, adjust model; test again, get feedback, adjust; etc. ...
Over the history of NLP the metaphors used to describe Stage 5 have changed from:
Installation of the model by the modeller in the acquirer
Transmission of the model by the modeller to the acquirer
Acquisition of the model by the acquirer (facilitated by the modeller).
Interestingly, these changes seem to parallel a general trend within NLP; that is, the focus of the practitioner-client relationship is moving away from the practitioner and towards the client. We support this trend, since our preference is for the acquirer (to be facilitated) to self-model their own process of acquiring.
Acquiring presents a paradox: The exemplar gets their results largely through unconscious processes, but the acquirer initially acquires the model and uses it consciously. This is a double paradox when the skill being modelled has to be unconscious, e.g. an intuitive signal.
Generalised process for acquisition
Starting with a thorough understanding and experience of using your model:
1. Gather information about the acquirer's outcome, the context where they want the required results, their existing map in relation to the model to be acquired, and their learning preferences.
2. Where possible, modify your model to align with the acquirer's existing map as long as the integrity and essence of the model is retained.
3. Design an acquisition process that includes multiple descriptions and is congruent with both the model and the exemplar's map.
4. Facilitate (or make available) the acquisition process.
5. Utilise acquirers responses - preferably in the moment - as feedback to adapt the process of acquisition to acquirer's model of the world and metaphors.
6. Test: to what degree do results acquirers get match those of the exemplar?
Some ways to present your model to an acquirer are to:
Enact the activity of each step of the sequence
Map components, their location, their functions and their relationships
Chart the flow of information and decision points
Physicalise or use non-verbal metaphor (Dance/Movement)
Tell stories and analogies
Write descriptions and give examples
Facilitating the acquisition process
It may surprise you to realise that your primary aim is not for the acquirer to acquire your model. Your model is only a means to an end. Your joint aim is for the acquirer to be able to reproduce results similar to that of the original exemplar(s).
As much as possible the acquirer needs to fully experience the model as they acquire it. So pay attention to and calibrate whether the acquirer is replicating the model in their own mind-space and body. i.e.
Do they describe it in the correct order?
Do they gesture, look and move as specified by the model?
Do they use the same or equivalent descriptions and metaphors?
Not all components of the model will be
equally important for the acquirer to acquire. Often a single piece
will make a big difference. But you are unlikely to know in advance which one!
Acquiring is an iterative process. Acquirers need both big chunk information (how the model all fits together as a whole and its purpose) and small chunk information (what to do).
Different acquirers will prefer to start with different aspects of the model. For example, they might first like to get know all the bits and what they do; or how the bits fit together and relate to each other; or the order in which things happen; or where and how they can use it.
Time, repetition, multiple descriptions and feedback are useful co-teachers.
Common responses to acquisition
According to Gordon & Dawes there are 5 common ways people do not acquire a new model (assuming they want to). In effect the acquirer indicates:
I can't get out of my present model
I can't get into the new model
I can't make sense of the model
I am concerned about the consequences of taking on the model
The model does not fit with who I am
One way to respectfully respond to this type of feedback is to facilitate the acquirer to self-model what is happening that means they are not acquiring the model (including how you are presenting it):
1. Fully acknowledge the way it is for them.
2. Confirm that they still want to achieve the required results.
3. Facilitate them to discover:
Where is there a mismatch between the existing and the new model?
What is making that mismatch possible and what is maintaining it?
Have they been in a similar situation and what did they do then?
What needs to happen to resolve it now?
What other metaphors/descriptions/representational systems will enable the acquirer to achieve the required results?
What are other circumstances where they could use the model?
What knowledge, skills or experiences need to be in place that will ease the acquirers' acquisition process?
Notes on Expert to Novice Acquisition
By definition, exemplars are
experts while acquirers are novices (cf. Dreyfus & Dreyfus).
Your exemplar will have years of experience and lots of unconscious habitual strategies. With so much happening unconsciously, the exemplar has spare capacity to pay (conscious) attention to other things that are happening. For example, comprehending language is a completely unconscious process for a native speaker, and hence they can attend to puns, patterns, double meanings and all sorts of subtle communication that is not available to the novice second-language learner. (cf. Gregory Bateson: as behaviour is repeated it becomes ever more deeply embedded in the organism, i.e. pushed down the levels of organisation.)
An acquirer does not have the same level of experience and so the acquisition process has to act as a bridge from the novice's way of doing things to the expert's way of doing things. To do this you may well need to add in some extra steps that are not part of your exemplar's model. The NLP Spelling Strategy is a good example (Joseph O'Connor and John Seymour, Introducing NLP, 1990, p.182). This model includes a step where the acquirer spells the word they are learning backwards despite the fact expert spellers never do this. So why is it is in the strategy?
When the modellers first tried to teach the spelling strategy to poor spellers, they found that even though they learned it, they did not believe this was enough to become a good speller. So someone had the bright idea of getting them to spell the words they were learning backwards on the basis that "If you can spell the word backwards, you know spelling it forwards will be easy." This extra 'convincer' step was added to make the spelling strategy more effective. (A second advantage of the backwards spelling step is that it allows the facilitator to very easily calibrate whether the acquirer is using the required visual accessing or reverting to the less efficient auditory method - with the latter it is almost impossible to spell words backwards.)
So, you might need to add extra
steps to prepare an acquirer to access a state that the exemplar
switches into naturally. For example, Penny Tompkins was modelled for
her ability to "notice a client's nonverbal cues and subtle
presuppositions of logic" when she is in therapy or coaching mode.
Penny can instantly "clear my mind" and be in a very open and
receptive state. She suggested that if someone else wanted to acquire
her noticing ability but couldn't take on her instant process, they might modify the SWISH technique so
that they could temporarily move away all the stuff that is present for them
until it is a dot on the horizon, and in its place bring back a
"clear space" in which the client and their stuff
can be situated. Although this is not how Penny does it, it would probably have the same effect.
Most NLP books are about the results of modelling projects, not about the modelling process itself. For example, the first five (pre-NLP) books by John Grinder & Richard Bandler (and others) were the product of their modelling. You have to read between the lines to infer the process of modelling they used.
Bandler, Richard & Grinder, John, The Structure of Magic vol. I, (Science and Behaviour Books, 1975)
Bandler, Richard, and John Grinder, Patterns of the Hypnotic Techniques of Milton H. Erickson, M.D. Volume 1, (Meta Publications, Cupertino, CA, 1975)
Grinder, John, and Bandler, Richard, The Structure of Magic vol. II (Science and Behaviour Books, 1976)
Bandler, Richard, Grinder, John, and Satir, Virginia, Changing with Families (Science and Behaviour Books, 1976)
Grinder, John, Judith DeLozier, and Richard Bandler, Patterns of the Hypnotic Techniques of Milton H. Erickson, M.D. Volume 2 (Meta Publications, 1977)
For more information on modelling you can consult (listed in approximate chronological order):
The original and highly technical work on eliciting, designing, utilising and installing strategies is by Richard Bandler, John Grinder, Robert Dilts & Judith DeLozier, Neuro Linguistic Programming Vol 1: The Study of the Structure of Subjective Experience (Meta Publications, 1980).
Leslie Cameron-Bandler, David Gordon & Michael Lebeau wrote The Emprint Method: A Guide to Reproducing Competence in order "to provide you with tools that will enable you to identify and acquire (or transfer to others) desirable human aptitudes." Although David Gordon now says it is really about modelling emotional competence. (Real People Press, 1985)
account of her and John
Grinder's modelling of people who have completed
interesting modelling projects can be found in Turtles All The Way
Down (Grinder, DeLozier & Associates, 1987).
Also see her article 'Mastery,
Coding, and Systemic NLP' in NLP World (Vol. 2 No. 1,
March 1995) which has a brief description of a "not knowing" state that is
excellent for "intuitive modelling".
Steve & Connirae Andreas have published numerous books on the results of their modelling including: Change Your Mind - And Keep The Change (Real People Press, 1987), Heart Of The Mind (Real People Press, 1989). See also Steve Andreas' article, Modeling With NLP (1999).
For a short and simple introduction to strategy elicitation, see chapter 4 of Charlotte Bretto's, A Framework for Excellence (Grinder, DeLozier & Associates, 1988).
Charlotte Bretto Millner, John Grinder and Sylvia Topel edited an excellent book Leaves Before the Wind: Leading Edge Applications of NLP (1991/1994) includes the results of some fascinating modelling projects.
Anthony Robbins has a very readable couple of chapters on modelling strategies in Unlimited Power (Simon & Schuster, 1988).
Joseph O'Connor and Brian Van der Horst aimed to update the strategies model in a three-part article, Neural Networks and NLP Strategies (Anchor Point, 1994)
Robert Dilts & Todd Epstein's Tools For Dreamers is packed with micro and macro processes for modelling with lots of examples of strategies for creativity (Meta Publications, 1991).
Robert Dilts. His three volumes, Strategies of Genius Volumes I, II & III are the definitive work on "conceptual modelling", especially when your exemplar is an historic figure. (Meta Publications, 1994/1995)
Robert Dilts, Modelling with NLP, provides an in-depth look at the modelling process and its applications (Meta Publications, 1998). For an short article see Robert's 'Overview of Modeling in NLP' (1998).
David Gordon has reissued his Modelling With NLP: An Introduction To Effective Modelling as a set of 4 CDs (NLP Comprehensive 1998/2004)
Robert Dilts and Judith DeLozier Encyclopaedia of NLP provides a description of many of the concepts and practices associated with modelling (NLP University Press, 2000).
James Lawley and Penny Tompkins detail a new form of modelling derived from their study of David Grove in Metaphors in Mind: Transformation through Symbolic Modelling (Developing Company
Their website contains numerous articles on modelling: www.cleanlanguage.co.uk/articles/categories/Modelling/ including an extensive report with video clips of their 'Modelling Robert Dilts Modelling' (2010).
John Grinder and Carmen Bostic St Clair, Whispering in the Wind (J & C Enterprises, CA, 2001) www.nlpwhisperinginthewind.com See also videos of John talking about modelling at: youtube.com/watch?v=CO_cHCuz9BU and youtube.com/watch?v=nSI7z9_Ga0Y
6 minute video: John Grinder on Modelling (2008)
John McWhirter article 'Re-modelling NLP: Part Fourteen: Re-Modelling Modelling' (Rapport 59, 2002)
David Gordon and Graham Dawes have written Expanding Your World: Modeling the Structure of Experience (2005) with a DVD which provides an excellent introduction to modelling using their "experiential array". There is also a wealth of information at: www.expandyourworld.net
Lukas Derks used "population modelling" to discover how we structure our inner social landscapes: Social Panoramas: Changing the Unconscious Landscape with NLP and Psychotherapy (Crown House, 2005)
Steve Andreas has modelled how "scope and category" creates meaning Six
Blind Elephants Vols 1 and 2 (Real People Press, 2006).
He has also written an article, 'Modeling with NLP' (Rapport 46 Winter 1999), and a couple of articles in response to John Grinder & Carmen Bostic St Clair's comments about NLP modelling: 'The Emperor's New Prose' (The Model Magazine, Summer 2006) and 'Modeling Modeling', 2006.
John Grinder & Frank Pucelik (Editors) Origins Of Neuro Linguistic Programming (Crown House, 2013). If you read between the lines you can discern much on how the original modelling gave rise to NLP in the early 1970's.
Fran Burgess has made a mammoth contribution to the field by publishing The Bumper Bundle Book of Modelling. It is the result of 15 years observing many leading modellers first-hand. It is the first publication which provides an extensive compilation and comparison of a number of modelling methodologies used in NLP.
Book: Whispering in the Wind (Grinder & Bostic St Clair, 2001) www.nlpwhisperinginthewind.com
Article: Chris Collingwood & Richard Thompson (2013) NLP Magazine #09 inspiritive.com.au/nlp-research/modelling-mirror-neurons.htm
Article: Interview with Steve Gilligan
Book: Generative Trance: The Experience of Creative Flow (Gilligan)
Book: NLP II: The Next Generation: Enriching the Study of the Structure of Subjective Experience (Dilts & Delozier with Bacon Dilts, 2010)
Book: Magic in Action (Bandler)
|Robert Dilts & Todd Epstein||
Book: Tools For Dreamers (Dilts & Epstein, 1991)
Books Strategies of Genius Volumes I, II & III (Dilts, 1994/1995)
Book: Modelling with NLP (Dilts, 1998).
Article:'Overview of Modeling in NLP' (Dilts, 1998).
|David Gordon & Graham Dawes||
Book & DVD: Expanding Your World: Modeling the Structure of Experience
(Gordon & Dawes, 2005)
|John McWhirter||Article: 'Re-modelling NLP: Part Fourteen: Re-Modelling Modelling' (McWhirter, Rapport 59, 2002)|
Article: Modelling an Expert; The missing piece in Knowledge Management (Faulkner, 1998)
L Michael Hall
Book: Going Meta: Advanced Modelling Using Meta-Levels (Hall, 1997/2001)
Book: Persuasion Engineering: Sales & Business Sales & Behavior (Bandler & La Valle, 1996)
Book: Social Panoramas: Changing the Unconscious Landscape with NLP and Psychotherapy (Derks, 2005)
|James Lawley & Penny Tompkins||
Book: Metaphors in Mind: Transformation through Symbolic Modelling (Lawley & Tompkins, 2000)
Website: cleanlanguage.co.uk/articles/categories/Modelling/ including an extensive report with video clips of their 'Modelling Robert Dilts Modelling' (2010)
|Stefan Ouboter||Article: Modelling Shared Reality: avoiding unintended influence in qualitative research (van Helsdingen & Lawley, Kwalon Vol 3, October 2012)|
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