Image Image Image Image Image Image Image Image Image Image
Scroll to top

Top

The Theory Of Ideal Supersmart Learning: A Versatile Holistic Framework for Rapidly Simplifying, Learning, and Applying TRIZ & Other Problem-Solving Methodologies - Parts II & III

| On 16, Apr 2002

The Theory Of Ideal Supersmart Learning:
A Versatile Holistic Framework for Rapidly Simplifying, Learning, and Applying TRIZ & Other Problem-Solving Methodologies – Parts II & III

Dr. Rodney K. King
http://www.supersmartnetwork.com
r.k.king@supersmartnetwork.com

Copyright 2002. Dr. Rodney K. King.
Readers of The TRIZ Journal are authorized to download and make one copy of this article for personal study. No other reproduction is permitted without prior written permission from Dr. Rodney K. King.

5. VERSATILE AND SIMPLIFIED TOOLS FOR TRIZ & OTHER PROBLEM SOLVING METHODOLOGIES

This article approaches problem solving, creativity, and ideas management from a learning perspective and in particular, Ideal SuperSmart™ Learning.

The Theory of Ideal SuperSmart™ Learning could be regarded as a generic methodology for rapidly learning about, studying, and mastering multifiarious subjects and disciplines. Here, the focus is on problem solving, creativity, and ideas management. The main roles of the Theory of Ideal SuperSmart™
Learning are as a meta-methodology (a methodology of other methodologies) and problem-facilitating methodology (a methodology for facilitating problem solving, creativity, and ideas management).

The discussions in the foregoing sections lay the foundation for a deep understanding of the Theory of Ideal SuperSmart™ Learning and its macrotools.
In subsequent sections, the focus is on a discussion of how to apply its meso- and micro-tools to methodologies such as Creative Problem Solving (CPS), TRIZ, ASIT, USIT, Profit Patterns, and Software Design Patterns. The discussions are largely conceptual and indicative. Nevertheless, it is hoped
that the versatility and usefulness of the meso- and micro-tools will be seen.

The meso- and micro-tools of Ideal SuperSmart™ Learning could be used to obtain conventional as well as “unusual (out-of-the-box or improbable)” improvements, designs, and inventions. The tools are mostly synthesis of existing tools, particularly from the literature on creative problem solving and
TRIZ. However, tools such as “CreaLogic”, “Paoisms”, and “Objecttemplates” are unique to Ideal SuperSmart™ Learning.

5.1 System of Problem Archetypes and Anti-archetypes
There are many approaches for identifying, describing, and structuring problems in systems. Ideal SuperSmart™ Learning focuses on identifying, describing, and analysing problems according to problem archetypes.

Problem archetypes are universal patterns of problems in systems. The patterns are interrelated and could be regarded as different or multiple perspectives of the same system. Problems, which are unsolvable as a particular problem archetype, may be solvable when framed as other problem archetypes. Creative or out-of-the-box solutions to problems may be obtained by bipolar framing, i.e., framing a problem as its opposite. For instance, a problem of perceived need could be reframed as a problem of “excess” and possible solutions explored for eliminating excesses. Similarly, problems could be perceived as opportunities. If the bipolar reframing refers to the same variable, then the statement becomes a physical contradiction.

Ideal SuperSmart™ Learning recognises eight problem archetypes. They are as follows:
Problem archetype 1: Undesirable “largeness/presence”
– What are undesirably large or present?1
Problem archetype 2: Undesirable “smallness/absence”
– What are undesirably small or absent?
Problem archetype 3: Undesirable inefficiency/sub-optimality/waste
– What are undesirably inefficient, sub-optimal, or wasted?
Problem archetype 4: Undesirable conflicts/contradictions/ bipolarities/dilemmas/paradoxes/disunity
– What are undesirably conflicting, contradictory, bipolar, paradoxical, discontinuous, or disunited?
Problem archetype 5: Undesirable complexity/sameness/ standardisation/symmetry
– What are undesirably complex, uniform, standardised, or symmetrical?
Problem archetype 6: Undesirable identification/detection/branding
– What are undesirably identified, detected, or branded?
Problem archetype 7: Undesirable dimensions/properties/parameters/ attributes
– What are undesirable dimensions, properties, parameters, or attributes?
Problem archetype 8: Undesirable situations/side effects/consequences/ systems/elements/super-systems
– What are undesirable situations, side effects/consequences/ systems, elements, or super-systems?
The eight problem archetypes could be organised into three categories:
· Mono-variable problem archetypes: Problem archetypes 1 and 2
· Bi-variable problem archetypes: Problem archetypes 3 and 4
· Multi-variable problem archetypes: Problem archetypes 5, 6, 7, and 8

In TRIZ, physical contradictions (dilemmas) focus on mono-variable problem archetypes, while technical contradictions (dilemmas) and the contradiction matrix directly focus on bi-variable problem archetypes. Ideality (ideal final result) and the 40 Inventive Principles deal with strategies for mono-, bi-, and multi-variable problem archetypes. Separation heuristics should, in theory, relate to mono-variable problem archetypes. In practice, however, separation heuristics deal with both mono- and bi-variable problem archetypes. The 76 Standard Solutions and database of effects are also applicable to mono-, bi-, and multi-variable problem archetypes. TRIZs patterns (trends/laws) of system evolution implicitly consider all problem archetypes.

Based on the dialectical (bipolar) approach of Ideal SuperSmart™ Learning, especially in the exploration of problem spaces, each problem archetype has a corresponding anti-archetype. For instance, problem anti-archetype 1 refers to desirable “largeness/presence” and deals with the question: What are desirably large or present? While problem archetypes facilitate the identification and classification of problems as well as corresponding solutionstrategies, problem anti-archetypes facilitate the identification of resources and the formulation of objectives. Together, problem archetypes and antiarchetypes could be used to rapidly identify and classify problems as well as comprehensively explore problem and solution spaces.

For a given discipline, templates could be developed for recording elements and features of problem archetypes as well as anti-archetypes. The format of a mind map is recommended for such templates. However, prior to formulating technical contradictions (dilemmas), possible parameters of the system could be summarised in a matrix as in table 2. Relationships between pairs of parameters could be investigated in order to find out which pairs demonstrate technical contradictions. A faster alternative may be to use qualitative change graphs2 as templates for mindstorming (brainstorming) on pairs of parameters that constitute case types I &II technical contradictions (dilemmas).

The formulation of problems as archetypes facilitates understanding of types of problems as well as generation of solution-strategies that specifically relate to problem-variables of a system. Problem archetypes 1 to 6 are directly related to solution archetypes in the SCAMPER-DUTION matrix in table 5. Consequently, corresponding solution-plots could be taken from cells of the matrix and applied to parameters of relevant problem archetypes. It is recommended that, before using the SCAMPER-DUTION matrix, a problem space should be dialectically explored and problems classified using the list of problem archetypes and anti-archetypes. The nature of problem archetypes may be more deeply investigated using methods such as deeper questioning (Why? What? Where? When? Who? How?); root-cause analysis; interaction (functional analysis) diagram; Substance-field analysis; triads; systems archetypes; SWOT analysis.

System archetypes and profit patterns, which generally focus on organisational (business) systems, belong to multi-variable problem archetypes. Organisational systems are open-ended and involve external recursive relationships, especially feedback. In contrast, artefacts are predominantly close-ended systems. In TRIZ, problems in systems are mainly treated as inventive problems or contradictions involving improvement in mono- and bi-variables. The SCAMPER-DUTION matrix (see table 5) may be used to obtain conceptual solutions that correspond to identified problem archetypes in a situation.

5.2 The Creative Web
The creative web provides a descriptive as well as normative framework for problem-based learning, creative project planning, creative problem finding & solving, and creative ideas management. The creative web also provides a framework for using multi-methodologies. Karl Popper once said, “All life is problem solving.” With due courtesy to Karl Popper, I’ll say: “All life is learning is problem solving is a creative web is …”
The creative web consists of five spaces5:
· Problem-definition space
· Methods-space
· Solutions-space
· Implementation-space
· Creative lifeSpace

The elements of the creative web are shown in Fig. 3. Elements 1 to 7 are to be regarded as “modules” rather than as “steps” or “sequences.”6 The seven modules could be categorised into four spaces as follows:
· Problem-definition space:
1. Creative (“inventive”)7 problem finding
2. Preparation and immersion
· Methods-space:
3. Re-engineering, Exploration, and Generation/Incubation
4. (Unexpected) Synthesis/Illumination
· Solutions-space:
5. Execution (Experimentation) and Testing
6. Evaluation and Verification
· Implementation-space:
7. Presentation, Acceptance, and/or Implementation
The creative lifeSpace is synonymous with the environment and common to all other spaces and elements.

Fig. 3 shows recursive or “trial-and-error” relationships between the spaces of the creative web. These relationships are consistent with the approach of Structured Intuition, Analysis, and Reflection (SIAR). The creative web assumes that trial-and-error or experimentation is an essential part of learning as well as problem solving, creativity, and ideas management. This assumption goes against the positivist epistemology of TRIZ which claims that TRIZ – unlike brainstorming – is a methodology not dependent on trial and error.

f1

As a descriptive model, the creative web could be used to generally explain processes of creativity, improvement, and invention. As a normative model, the creative web indicates how a novel, “wicked” or inventive problem may be approached as well as how a (creative) project or problem could be planned and structured, especially if a real-time dimension is introduced in a spacetime matrix.11 Time is implicit in the diagram of the creative web in Fig. 3. The creative web could be used for structuring and providing a holistic view of macro-projects involving the use of TRIZ.

The tool in TRIZ, which is generally comparable to the creative web, is the ”Algorithm for the Solution of Inventive Problems.” This algorithm has the Russian acronym, ARIZ. The evolution of ARIZ is documented in Savransky (2000). ARIZ-85C is Altshuller’s last version and consists of nine main stages. The relationships between the main stages of ARIZ-85C and the problem-definition, methods-, and solution-spaces of the creative web are shown in table 3.

f2

Table 3 illustrates a multi-methodology framework that relates to TRIZ. This framework allows the matching and mixing of methods in TRIZ as well as between TRIZ and other methodologies. In table 3, methods in classic TRIZ are embolded. Methods outside TRIZ such as in ASIT, USIT, and the Theory of Constraints are enclosed in parentheses. Methods of the Theory of Ideal SuperSmart™ Learning are italicized. Table 3 could be used as a “pointer” and checklist for tools when solving problems.

5.3 The Versatile Map™, Implementation Map, and Creative LifeSpace Map
For more specific problem solving, creativity, and ideas management, the creative web translates into three maps: the versatile map; implementation map; creative lifeSpace map. Fig. 4 shows a graphic version of the versatile map™ in Axon file format. The versatile map™ consists of problemdefinition-, methods-, and solutions-spaces. The versatile map™ provides a framework for using multi-methodologies13 and could therefore be employed for structuring and solving a wide range of problems, including those in “soft” and “hard” systems.

As a file in the Axon software, the versatile map™ is hyperlinked to the implementation map as well as creative lifeSpace map. Each object on a versatile map could be a hyperlinked knowledge base on a computer or the Internet. The principles of object mapping apply to each object and map. Also, the “Generator” on a versatile map™ – in Axon format – could be used to automatically generate up to 200 solution-strategies for each parameter in a given system.

As indicated in table 3, the main stages of ARIZ could be mapped on to a versatile map™. A checklist of detailed steps of ARIZ or any problem solving methodology could be contained in “hidden” hyperlinked objects on the versatile map™. Currently, a template of the versatile map™ contains notes on elements, techniques, and procedures of methodologies such as TRIZ; strategic planning and management; creative problem solving. These notes provide a basis for rapidly learning, using, reflecting, and expanding on these methodologies. The icons, which are adjacent to descriptive categories or “basic ordering ideas” on the versatile map™, open-up as blank pages (“windows”) for input of problem-related information by the user. Unlike in ARIZ, the user could input data and information in a non-sequential manner.

On a printed template of the versatile map™, a user could record information using the technique of object mapping and in particular, mind mapping. Each icon becomes the central object of a classic mind map. I use A3 and A2 size papers for developing handwritten versatile maps™ as well as implementation and creative lifeSpace maps.

f3

The methods-space of the versatile map™ contains a versatile matrix as an object. An abridged versatile matrix is shown in table 4. All strategies and techniques, which are described in the versatile matrix, could be used on the versatile map. The versatile matrix is a useful resource for finding alternative techniques for particular thinking strategies. Ideal meta-cognition, metalearning, and reflective learning may be facilitated by use of the versatile matrix. Like in Edward de Bono’s Six Thinking Hats™, the versatile map™ could be used for team problem solving, especially for structuring, discussing, and solving problems in meetings.

The set of versatile, implementation, and creative lifeSpace maps could also be used for documenting software design patterns. In software development, a design pattern refers to a template or an object for documenting and storing “best practice (solutions).” There is currently no standard template or structure for recording design patterns.

f4

Ordering ideas for various design patterns could be categorised as follows:
· Problem definition-space:
(Pattern) Name/Problem/Context/Forces
· Methods-space:
Rationale
· Solutions-space:
Solution
· Implementation space:
Resulting context (Consequences)/Known uses/Examples/
Related patterns
· Creative lifeSpace:
Not available

Advantages of the approach of design patterns include the following: accessibility of best practice solutions to designers and problem solvers, especially those at low and intermediate levels of understanding; observation of evolution towards ideal design patterns; a structured and reflective approach towards software development. Although the explicit use of design patterns is most common in the software industry, there is no reason why design patterns cannot be used in other disciplines or domains such as product development and business management. In fact, the formal concept of design patterns originates from architecture and in particular, Christopher Alexander. In his classic book, The Timeless Way of Building, Alexander advocates the concept of a pattern language (for architecture), from which the concept of design patterns emerges. The concept of pattern language is consistent with the template theory for versatile creativity and applicable to many disciplines.

In recent years, the pattern language movement in the software industry has developed the concept of anti-patterns. An anti-pattern encompasses lessons learnt from a “bad” solution as well as how to move from a “bad” solution to a “good” solution. Anti-patterns reflect the concept of anti-IVYality and how to move from anti-IVYality to IVYality. Anti-patterns encourage bipolar and reflective thinking.

It is possible to develop, for a particular discipline or domain, a library of generic and domain-specific design patterns as well as anti-patterns. Such a library would be a useful resource for problem solving, creativity, and ideas management in the discipline or domain.

Worst patterns could provide materials for learning and reflective exercises.
With time, best practice design patterns or highly inventive solutions are expected to evolve towards ideality, while worst patterns move towards antiideality. A patent database could be regarded as a library of best practice design patterns for specific products or artefacts. The use of versatile, implementation, and lifeSpace maps should facilitate the organisation and management of a design patterns library, especially on the Internet, for any discipline.

5.4 The Basic IVY-Template for Strategic Problem Solving
Like the versatile map™, the basic IVY-template could be used as a tool for learning and teaching creativity as well for problem-finding, structuring, and solving. Both the versatile map™ and the IVY-template strongly relate to problem-definition, methods, and implementation-spaces. In the IVYtemplate, however, there is no “boundary” between the problem-definition and methods-spaces. An example of an IVY-template is shown in Fig. 5. The IVY-template could be presented on A4, A3, and A2 size papers; I often use A3 paper.

The versatile map™ is suitable for solving strategic problems in both “humanactivity systems”20 and “designed physical (product) systems”, while the IVYtemplate focuses on strategic (conceptual) problem solving for artefacts or in designed physical (product) systems. The IVY-template is predicated on the basic functional relationship:
[object or pattern] [interacts with] [object or pattern] to obtain [result/”emergent” object or pattern]

In my view, all dynamic systems reflect the above relationship. The symbols in Fig. 5 are explained below. The description of “core” may refer to resources or the unitary space at the system level, while “peripheral” and “remote” may refer to resources at “neighbourhood”/super- and supra-levels respectively. Archetypal tasks regarding “verb 1” include descriptions of a main problem as well as the following primary functions: “improve”21; “design”; “invent”; “identify”; “detect”; “brand”; “exploit”; “exhaust.” Such archetypal tasks or functions facilitate not only the categorisation and solution of problems but also pattern and analogical thinking. The term “focus” may refer to a sub-system or element.

Complementarity exists between the use of the versatile map™, within which open-ended, “wicked”, or ill-defined problems can be addressed, and the use of the IVY-template, within which conceptual solutions can be directly generated for more specific or well-defined problems. The IVY-template could be used to depict and more thoroughly understand a problem situation with a view to identifying principal root-causes. The IVY-template may also be used after an ill-defined problem has been transformed to a well-defined problem using a versatile map™. However, final solutions, after using the IVYtemplate, may be summarised, evaluated, and presented using a versatile map™.

The IVY-template may be used to carry out multi-level analysis either holistically (intuitively) or sequentially, e.g., using, one at a time, the framework of triads, substance-field analysis, and root-cause analysis. Multilevel analysis is highly recommended as it provides a comprehensive view of situations, systems, and problems.

f5

The IVY-template illustrates the fact that there are two categories of solutionsystems and three generic ways of solving any problem. The details of these systems and solution-paths are presented below.
Closed (self-contained)-system solutions22: internally-driven reengineering using given (and “freely available”) elements and resources of the system.
Solution-path
O3/O2 -> O1

Open-system solutions: using external (non-system) elements and resources
(a) Externally-driven reengineering of given system:
Solution-path
O3.1 -> O2/O3 -> O1
(b) Complete replacement of given system or problem:
Solution-path
O3.2 -> O1
Each description on the IVY-template in Fig. 5 could be regarded as an object. Letters on the IVY-template could have the following interpretations:
* O: “Object” (in the sense of the principle of object equivalence, a unitary space, or system of resources )
* F: Factor(s); Field(s)23; Force(s); Function(s); Failure(s)
* P: Pattern(s); Plot(s); Principle(s); Procedure(s);
Process(es); Properties; Parameter(s); Prompter(s)
The IVY-template could be related to and used within the context of many problem-solving methodologies. For instance, when using TRIZ and in particular, Substance-Field analysis24, the objects could be regarded as follows:
· O1: Substance (S1); “Constraint”; “Weakest link”;
(“Passive”)25 Resource 1
· O2: Tool (S2)/“Miniature Dwarves”; objectBots; Means;
“(Non-)Contacting Agent(s)”; targeted variable(s);
(“Active”) Resource 2
· O3: Given System; “Super-agent(s)”;
(“Enabling”) Resource 3
· O4: Ideal Final Result (IFR); IVY-Final Result; Resource 4
· F: Field – Mechanical; Thermal; Electrical; Electromagnetic;
Electronic; Acoustic; Optical; Magnetic; Nuclear;
Chemical; Biological
· O3.1: External elements; “Additives”; Resource 3.1
· O3.2: New (substitute/replacement) system; Resource 3.2
· O(-): Undesirable (harmful/negative) effects; Disadvantages;
· O(+): Desirable (useful/positive) effects; Advantages;
Opportunities

It must be pointed out, however, that graphic representation and use of the IVY-template are closer to those of Triads26 and Object Functional Analysis (OFA) than the classic Substance-Field model. Triads are especially useful in the illustration and improvement of systems with dominant functions or core problems. The IVY-template could draw on the triads approach to initially document a system that is problematic and is to be consequently improved or redesigned. Like in Triads, the network of objects on the IVY-template could be expanded27. Unlike the triads approach, however, the IVY-template illustrates the ideal or IVY-Final Result and thereby gives a holistic view of the problem solving process. Also, using the technique of object (mind) mapping, diagrams as well as texts could be used to describe objects on an IVYtemplate. Other methods of TRIZ such as “Miniature Dwarves” and “Multi-screen Approach”28 could be applied within the framework of the IVY-template. Fig. 5 shows, for the core object (O3) as well as a 1×3 screen: past; present; future. This 1×3 screen could be used for the method of miniature dwarves as well as the ideal final result, which could be depicted as a scene in the longterm future (O4).

The IVY-template could be used to comprehensively illustrate each of TRIZs
40 Inventive Principles. As presented in classic TRIZ, the 40 Inventive Principles appear difficult to understand and interpret, especially in the context of problems that are not related to mechanical engineering or product development. It is difficult to see which dimension of a system’s ideality is enhanced by many inventive principles. Some examples, which are associated with specific inventive principles, neither describe the initial state of the system nor state the relevant dimension of ideality or targetedvariables, i.e., variables on which the principles operate. Targetedparameters may be different from TRIZs list of 39 parameters, pairs of which are featured in the contradiction matrix.

Using the IVY-template and object-mapping, one could prepare vertical and lateral IVY-templates for TRIZs 40 Inventive Principles. A vertical IVYtemplate, in Axon format, deals with a single inventive principle and involves “nesting” of examples on application of a specific principle. In contrast, a lateral IVY-template describes two or more inventive principles. Lateral templates facilitate comparison of heuristics (inventive principles) in and between problem-solving methodologies, e.g., between TRIZ, ASIT, and USIT. IVY-templates also enable myriad solution-paths to be automatically generated using the Axon software.

In ASIT and USIT, “P” could represent patterns of “solution-techniques.”
Using the technique of object- or mind-mapping with “P” as a central object, one could summarise solution-techniques of ASIT and USIT using the following acronyms as “basic ordering ideas:”

* ASITs solution-techniques: D.R.U.M.S. –
Dimensionality; Removal; Universality; Multiplication; Symmetry.

* USITs solution-techniques: D. /D.U.P.T. –
Dimensionality; Distribution; Uniqueness; Pluralization; Transduction.
The IVY-template provides a holistic framework for solving conceptual problems, especially using the ASIT or USIT methodology. The IVY-template facilitates the use of multi-methodology or “multi-techniques” when solving a given problem. Thus, rather than using the “multiplication” technique of ASIT to solve a problem, one could also use techniques of “segmentation” and “dimensionality.” Based on the concept of multi-methodology, solutiontechniques of ASIT could be combined with those of USIT and TRIZ in order to generate a wider range of solutions.

Other applications of the IVY-template include the preparation of templates for Profit Patterns as well as Scenario Planning/Learning. In Scenario Planning/Learning, the “F”-object could represent “driving forces” while the “P”-object could denote “Plots.” The “end states” of scenarios could be represented by object O4, which is equivalent to the “IVY-Final Scenario.” Problems could be solved using a problem (root-cause)-led approach and/or solution-led approach in conjunction with the IVY-template. Brainstorming is usually presented as a solution-led approach.29 Ideas generated from brainstorming could be recorded in the window of or next to the object, “IDEA LOG.” Questions, which are related to a system and come up during problem solving, could be recorded under “Strategic Inventive Questions.” Like in the case of a versatile map™, IVY-templates of best as well as worst solutions could be maintained in a library of patterns for a particular discipline. The SCAMPER-DUTION matrix (see section 5.6) is a useful resource for generating ideas and solution-paths.

5.5 System of Solution Archetypes
Basic Solution Archetypes
In section 5.1, eight basic problem archetypes were identified in a problemdefinition space. Corresponding to those problem archetypes are basic solution archetypes in a solutions-space. The basic solution archetypes, which are largely based on conditions of IVYality or ideality (see table 1), are shown below:
Solution archetype 1: Ideal (“functional”) nothingness
– Eliminating (or minimising/decreasing/reducing) an undesirable largeness/presence
Solution archetype 2: Ideal infinity
– Infinitely increasing (or maximising/”creating”) an undesirable smallness/absence
Solution archetype 3: Ideal efficiency & “automaticity”
– Achieving infinite (or maximum) efficiency;
Making completely automatic or self-operating (self-working)
Solution archetype 4: Ideal conflict resolution & unity
– Absolutely – without “trade-off” or compromise – resolving all conflicts, contradictions, paradoxes, dilemmas, and disunities (to the satisfaction of all objects);
Achieving perfect (network) unity or integration
Solution archetype 5: Ideal simplicity, variety, & beauty
– Achieving absolute simplicity, absolute/requisite variety, beauty (elegance)
Solution archetype 6: Ideal identification, detection, & branding
– Achieving universal identification, detection, & branding
Solution archetype 7: Ideal dimensions, properties, parameters, & attributes
– Obtaining ideal dimensions, properties, parameters, & attributes
Solution archetype 8: Ideal situations, effects, & objects
– Achieving ideal situations, effects, consequences, systems, elements, & super-systems

Basic solution archetypes describe solution patterns at a macro-level and could be used after identifying particular problem archetypes, for example, in brainstorming sessions and through detailed causal analysis. Basic solution archetypes provide a framework for universally organising existing as well as normative solution strategies in systems, including disciplines. In other words, a library of methods and solutions – in a system or discipline – could be based on the system of basic solution archetypes. Descriptions of sub-categories for each solution archetype are referred to as closed-system solutions and opensystem solutions. Eco-systems are predominantly cases of closed-system solutions. In fact, Humberto Maturana and Francisco Varela argue that “all living systems are organizationally closed, autonomous system of interaction that make reference to themselves.”30

A template for generating and exploring conceptual solutions could have the format:
“Consider [solution archetype] using [field-based]31 means relating to variable(s)”

A basic solution archetype could “operate” on one or more variables, i.e., (causal) parameters, of a given system. Categories of variables include the following: materials/substances; functions/actions/processes; fields/forces; artefacts devices/tools); naturfacts. These variables, which are similar to objects on the IVY-template, could be used to create a matrix of solution archetypes. More specific solution-strategies for each solution archetype – at a meso-level – could be obtained by either repeatedly asking, “How?” or using the SCAMPER-DUTION matrix, which is discussed in the next section. Basic SCAMPER-DUTION Matrix of Patterns for Solution-Plots, Properties, and Devices

A SCAMPER-DUTION matrix is a tool for organising as well as summarising solution-patterns, plots, properties, devices, and tools. The basic matrix is a 14×8 table, i.e, it consists of fourteen rows and eight columns; see table 5. The letters of the acronym “SCAMPER-DUTION” and the description for the rest of the alphabet, “Miscellaneous” make up the rows. SCAMPER is a well known acronym that summarises manipulation verbs and is attributed to Osborne and Eberle; my contribution is the acronym, “DUTION.”

The development of the matrix is my idea as well as the introduction of columns with the following headings: “Ideal (“functional) nothingness”; “Ideal infinity”; Ideal efficiency & “automaticity”; “Ideal conflict resolution & unity”; “Ideal simplicity, variety, & beauty”; “ideal identification, detection, & branding”; “Targeted variables.” The majority of the columns cover conditions of ideality, i.e., basic solution archetypes 1 to 6. The remaining solution archetypes could be subsumed under the heading of “Targeted variables.”

While contents of targeted variables vary from discipline to discipline, conditions of ideality are constant. In TRIZ, targeted variables include “engineering parameters” and causal factors in given situations. Higher-level targeted variables could be elements and super-systems of a given system. The level of abstraction of targeted variables influences the level of detail in proposed solutions.
In the SCAMPER-DUTION matrix, each letter in a row is an abbreviation that represents patterns that begin with that particular letter. A pattern could be expressed as follows:

Patterns at Level 1: Keyword (idea prompter/trigger/hint)
· Verb/Action: Operations; Manipulations; Reengineering actions
· Noun/Nominalisation: Devices; Tools; Substances; Materials;
Artefacts; Persons; Organisms
· Adjective/Description: Properties; Attributes; Characteristics
Patterns at Level 2: Phrases/Sentences/Paragraph/Diagrams/Multimedia
· Phrase: Title of “solution-plot”32, heuristic, or means; (in two or three words)
· Sentence: Brief description of “solution-plot”, heuristic, or action
· Paragraph: Context-specific elaboration or example of “solutionplot”, heuristic, or means
· Multi-paragraphs: Story; Detailed “solution-plot”, heuristic, or means; Algorithm
· Diagrams/(Interactive) Multimedia

The higher or further down the level of pattern is, the more detailed and relevant is the solution-pattern to a given problem. Osborne and Eberle’s technique of SCAMPER and various lists of manipulation or reengineering actions deal with “verb/action”-patterns, i.e., at level 1. TRIZs 40 Inventive Principles deal with patterns at both levels 1 and 2. The descriptions of thirteen inventive principles are at level 1 (single nominalisations), while twenty-seven are at level 2 (phrases and sentences). TRIZs “Examples”, which are associated with each principle, are all at level 2. In the Axon software, each keyword at level 1 could be hyperlinked to patterns at level 2.

Examples clarify and give deeper, i.e., situation-relevant meanings to patterns at level 1. In Ideal SuperSmart™ Learning, TRIZs 40 Inventive Principles are regarded not only as strategies for resolving technical contradictions (dilemmas) but also as idea prompters or hints for generating ideas (for IVYobjects) and operationalising basic solution archetypes.

The description of five solution-techniques of both ASIT and USIT deal with noun-patterns at level 1. For simplicity in presentation, level 1 solutionpatterns for TRIZ, ASIT, and USIT are presented in table 5. This table also contains manipulation (reengineering) verbs. The numbers, which are adjacent to keywords, refer to those of TRIZs inventive principles. In a way, the SCAMPER-DUTION matrix could be regarded as a creative web that is structured as follows:- Problem-definition space: Problem archetype(s); Targeted variable(s); Methods-space: Operators (contents of cells) of SCAMPER-DUTION matrix; Solutions-space: Operator(s) + Targeted variable(s).

The summary of some principles in table 5 involves the introduction of a keyword with a different starting letter from that in TRIZs inventive principles.

Some inventive principles (such as TRIZs “segmentation (1)” and “combining (5)” and manipulation verbs fall into more than one category. In order to facilitate comparison between solution-patterns of TRIZ, ASIT, and USIT, properties and devices as well as TRIZs Standard Solutions and Database of Effects are not summarised in table 5.

The matrix in table 5 shows that a particular solution archetype could be achieved using several patterns. Combination of patterns could be “means” for achieving other patterns, which could be regarded as “ends” or “goals.”

The largest proportion of TRIZs inventive principles deal with ideal efficiency and automaticity. A pattern such as “Dimensionality” is common to TRIZ, ASIT, and USIT. Also, some manipulation verbs such as “combine”, “divide”, and “remove” are synonymous with TRIZs keywords. From the perspective of TRIZ, an advantage of the SCAMPER-DUTION matrix in table 5 is that it is independent of the contradiction matrix. Consequently, technical contradictions need not be found before using the inventive principles.

Patterns in the SCAMPER-DUTION matrix could be used intuitively, e.g., after brainstorming on problem archetypes or logically, e.g., after determining rootcauses of problems; alternatively, object (mind) maps could be used. Solution patterns or inventive principles can therefore be more rapidly selected from table 5 as well as applied to a wider range of problems.

In table 5, the contents of cells may be augmented by a user in a specific discipline. For instance, the cells could be filled in – especially at level 2 – by extracting and summarising solution-patterns or strategies from a library of best solutions such as in a patent database or a “best practice” database.

Also, the SCAMPER-DUTION matrix could be used as a pattern object, i.e., a “P”-object in the IVY template; see Fig. 5.

The SCAMPER-DUTION matrix could serve as a resource for idea generation as well as problem-solving that involves the resolution of physical and technical contradictions. The matrix goes beyond TRIZs inventive principles and facilitate goal-oriented problem solving as well as brainstorming. For instance, if a certain “object” is to be eliminated, a problem solver could review as well as generate solution-patterns for “Ideal (functional) nothingness” in core, peripheral, and remote domains. In idea generation, it is recommended that the matrix also contain properties, tools, and devices for each dimension of ideality. More creative (unusual) ideas may be obtained by using bipolar problem-reframing, bipolar solution archetypes in the IVYtemplate, and variables from the IVY-matrix.

f6

The contents of the matrix could serve as “trigger words”, idea prompters, or hints for generating solution-strategies. Various high level solution-patterns or plots may therefore be generated using words in one or more cells of the SCAMPER-DUTION matrix. Such generated solution-patterns or plots may directly relate to actual problem-solving, developing a database of solutionpatterns, or practising creativity.

With the aid of the SCAMPER-DUTION matrix, solution-patterns in any system, subject, or discipline (e.g., solution-strategies in business management, total quality management, business process reengineering, biomimetics, and patent database) could be documented. The SCAMPERDUTION matrix also lends itself to activities as diverse as magic tricks, graphic design, origami, art, drama, and humour. The Fantogram33, one of the tools for creative idea generation in TRIZs course of Creative Imagination Development, is subsumed in the SCAMPER-DUTION matrix. As a file within the Axon software, a SCAMPER-DUTION matrix could be used to generate myriad fantasy ideas and higher-level solution-patterns.

A basic template for generating solution-patterns is the following:
“Consider or change (a)symmetrical means for [field-based34] [“SCAMPERDUTION”] of (micro-/meso-/macro-) [Targeted variables] in space and/or time to obtain [solution archeype] or [IVY-object]”

To generate higher level conceptual solutions, only the highlighted words need be considered. As more words are included in the template, solutionpatterns become more specific but thinking becomes more restricted and convergent. Templates with few keywords are useful in sessions of structured mindstorming (brainstorming). More specific features of given situations could be related or hyperlinked to targeted variables in table 5.
Creativity games and quizzes could be developed for a SCAMPER-DUTION matrix. When filling in the cells of such a matrix, questions may include the following:
· Which “S” may satisfy the objective of ideal infinity?
· Which targeted variables or objects begin with a “T?”
· Which solution-plots and/or parameters of the object could satisfy the objective of ideal efficiency & automaticity?
· Select known (intriguing) objects and explain, using the
SCAMPER-DUTION matrix, how the products could have been designed, improved, or invented.

5.6 IVY-Matrix of Bipolar Variables, Dimensions, and Criteria
The IVY-Matrix consists of thirty “spectra of bipolar dimensions.” Each spectrum or row is divided into bands on an ordinal scale. Alternatively, a spectrum may be “calibrated” using an interval scale and specific values from a family of objects. Table 6 shows an IVY-Matrix™ of bipolar variables, dimensions, and criteria. The dimensions are based on categories of IVYality as well as common attributes of parameters in both physical and nonphysical systems. Variables such as quality, safety, and beauty/ergonomics are regarded as bipolar dimensions. The variables in the IVY-matrix could be used to describe dimensions about which the evolu-tion of products take place as well as a range of dimensions for parameters. Like in the SCAMPERDUTION matrix, the descriptions in the IVY-matrix refer to patterns at level 1, i.e., keywords. The IVY-matrix may be extended and made more disciplinespecific by hyperlinking patterns at level 1 with patterns at level 2, i.e., phrases, sentences, and paragraphs that refer to specific examples.

Each spectrum in the IVY-matrix is bipolar and ranges from “Anti-[Dimension] through “Nothing” to “[Dimension].” The extreme value for Anti-[Dimension] is “minus infinity”, while that for [Dimension] is “plus infinity.” The bands of Anti- [Dimension] and [Dimension] could be sub-divided into three parts that may be ordered as “Low”, “Medium”, and “High/Extreme.” However, in the IVYmatrix in table 6, only [Dimension] is so finely divided. Anti-[Dimension] is considered as a single band in order to simplify the presentation and subsequent discussion. It is assumed in the IVY-matrix that ideality or IVYality could be bi-directional. Cells or “states” that unanimously reflect ideality, are embolded. Using the SCAMPER-DUTION matrix in combination with the IVY-matrix, one could generate ideas as well as alternative solutionpaths and processes for moving from one state to another.

Several tools of TRIZ could be mapped on to and demonstrated using the IVY-matrix. For instance, the Size-Time-Cost (STC) operator refers to spectra nos. 2, 12, and 20. The STC operator is useful for extreme contingency (“what if?”) analysis. The IVY-matrix indicates that extreme contingency analysis could be carried out for other dimensions, including those in TRIZs list of 39 engineering parameters.

Like in the patterns (laws/trends) of technological evolution, TRIZs extended “level design” or “stepwise heurithm”35 could be depicted on the IVYMatrix.

Thus, fantasy ploys such as in science fiction could be developed using the IVY-Matrix. An advantage of the IVY-Matrix is that a user could develop templates or story plots other than the one presented in the extended heurithm. This use of the IVY-matrix could encourage creative visualization as well as improbable thinking and consequently, reduce psychological inertia in problem solving and creativity.

f7

f8

Perhaps, the most valuable use of the IVY-matrix is with regard to “object profiling.” Using the IVY-matrix, one could carry out horizontal and vertical profiling of products. The uses of object profiling include idea generation, benchmarking, and fantasy exploration.

Horizontal profiling deals with ascertaining the various “states” of a family of products on a chosen bipolar spectrum. Horizontal profiling often deals with “morphing” or transforming a singular dimension of an object and observing a new “dynamic” scenario containing the morphed or transformed object.

Consequently, horizontal profiling bears some similarity with extreme contingency (what if?)analysis. The objective of each, however, is different. In horizontal profiling, one may consider a family of products, choose a “state” in the bipolar spectrum, and “plot” or describe categories of the dimension for the products. For instance, plotting the size of playing cards may reveal that “mega-“ and “molecular” sizes of cards have not yet been produced! Extreme contingency (what if?) analysis is a type of sensitivity analysis.

Vertical profiling is carried out for a specific product item rather than a family of products and involves visually connecting cells of all spectra that describe the dimensions of the product. Some ideal states are highlighted in table 6 as embolded cells. A few dimensions have no unique ideal state.

Vertical profiling relates to ideal benchmarking, i.e., benchmarking an ideal object. From a product’s vertical profile, one could determine how far the current dimensions of the product are from each ideal as well as determine alternative scenarios for evolution of the product. Also, the method of vertical profiling could be used for facilitating the formulation of inventive problems and design specifications for a product as well as mission statements for organisations. In generating ideas for product development, the maxim of “novelty before utility or justification” is recommended. In other words, “modify object’s state or form before reviewing advantages, functions, properties, or opportunities of emergent object.”

TRIZs eight “patterns (laws/trends) of technological evolution” could be summarised as meta-patterns using variables from the IVY-matrix. Table 7 shows categories of meta-patterns for patterns of technological evolution. Some meta-patterns refer to single variables like quantity and time while others combine two or more variables. Table 7 contains seven meta-patterns. Two patterns of evolution, which have similar descriptions and expected final results, are classified under the conflict meta-pattern.

Table 7, in particular expected final results (EFRs), could be used to develop heuristics for generating ideas on product development. A possible heuristic for the quantity meta-pattern is: “Change to, consider, or introduce bisociation of subsystems, elements, or parts.” For the conflict meta-pattern, a heuristic might be: “Change to, consider, or introduce a contradiction between parts, subsystems, or elements.”

f9

The evolution of technical systems, which is presented in graphical (network) form in classic TRIZ, is presented below as a matrix of metapatterns in table 8. For examples on the evolution of technical systems in classic TRIZ, see Savransky (2000, p. 116) and Salamotov (1999, p. 193).

Meta-patterns in table 8 relate to variables in TRIZs evolution of technical systems as well as those in the IVY-matrix. It may be noted from table 8 that TRIZs evolution of technical systems does not explicitly describe bi-functional states. Also, the primary progression of a system is from a quantity metapattern to a simplicity meta-pattern. There seems to be a logical inconsistency in this scale of progression. Table 8 may be used as a template for documenting states in the evolution of technical systems as well as for generating ideas for technological forecasting.

f10

5.7 ObjectBots and the Scene-Transformation Matrix ObjectBots
The concept of “objectBots” has its roots in PAO thinking™, IVY-paradigm, TRIZs modelling of miniature dwarves (smart little people), and (molecular) robotics. An objectBot could be an IVY-object and is related to the following TRIZ-derived concepts: SITs “inanimate particles”; USITs “magic particles”, and Savransky’s “agents.” TRIZs concept of miniature dwarves, which is based on personal analogy models in the creativity technique of Synectics, is useful for reframing a given problem. Often, an object of focus is replaced by miniature dwarves that possess multi-dimensional characteristics and behaviour that would lead to solution of a problem. In some cases, emergent functions in the solved problem may be transferred to the original object of focus. ObjectBots are useful for reducing psychological inertia in problem solving.

In PAO thinking™, an object refers to both tangible and intangible items. An objectBot is synonymous with an object and could be regarded as a “gimmick” for problem solving. An objectBot may be represented by a symbol, “x.” It could be of any size – from molecular to galactical – and could ideally perform any desired function. An objectBot could be animate and have magic-like properties. The IVY-matrix of bipolar variables, dimensions, and criteria could be used to select a range of properties and orders of magnitude (scales) for specific objectBots.

The behaviour of objectBots is governed by a set of bipolar tenets:
(i) The logic of IVYality, i.e., Ideality, Versatility, and “Ympossibility.”
An objectBot could be an IVY-object and therefore have ideal, versatile, and apparently impossible properties.

(ii) Laws of conservation of energy (matter) and momentum.
Energy (matter) can neither be created nor destroyed.
The total momentum of an objectBot in motion is constant.
From both tenets above, one could say that the working space of an objectBot ranges from the mundane through cutting-edge (undiscovered) technology to “probable impossibilities.” The first tenet indicates that an objectBot could be anything and have any desired property or behaviour. The second tenet, in particular the law of conservation of energy (matter), is a constraint and ensures that objectBots operate within known physical worlds, even though they may behave magically. A problem solver should therefore account for the existence, introduction, transformation, and removal of all objectBots in a system.

Ideally, objectBots should already exist or be obtained through replacement or transformation of existing resources in the system, or be freely available. In other words, closed (self-contained)-system solutions should be sought when using objectBots to solve problems. Ideal solutions in a given system are obtained when objectBots in open and closed-system solutions transfer their emergent functions, properties, and parameters to elements of the given system.
ObjectBots are useful for typifying objects. For instance, objects which produce undesirable effects could be described as “villainBots.” In contrast, objects that experience deleterious effects could be described as “victimBots.” An advantage of such classification is that, like in problem archetypes, a set of corresponding strategies could be developed to deal with particular classes of objects.

Any item could be perceived as and translated to an objectBot by attaching the suffix “-Bot” to a description of the item. Thus, for analysis using the IVYtemplate, we may have “materialBots”, “FieldBots”, “ForceBots”, “ToolBots”, and “IVY-Bots”36.

For problem solving involving processes in physical systems, the following objectBots may be useful: “bodyBots”37; “manualBots”; “mechanicalBots”; “biologicalBots”; “thermalBots”; “electricalBots”; “chemicalBots”; “acousticBots”; “opticalBots”; “magneticBots”; “nuclearBots.” Any ideal state or Ideal Final Result (IFR) could be achieved by a system of objectBots. ObjectBots are also useful for conceptually analysing “Scene-Transformation Matrices.” The next section discusses the tool of Scene-Transformation Matrix.

Scene-Transformation Matrix
A scene-transformation matrix refers to a table that contains not only multiple visio-verbal scenes or scenarios arranged in a timeline but also descriptions of key assumptions and possible solution-paths for attaining a desired result in the future. A scene-transformation matrix is essentially nonlinear and solution-paths could be obtained by combining scenes from different “epochs” or time-bands. The simplest form of a scene-transformation matrix is a storyboard38. A classic storyboard, especially for final presentation, shows scenes in a row or sequence, i.e., one solution-path for the unfolding of an event. In contrast, a scene transformation matrix may show multiple solution-paths for an event.

The template for a scene-transformation matrix is shown in table 9. A scenetransformation matrix may serve the following purposes:
· Presentation of scenes, scenarios, or strategic action plans in a timeline; illustration of a storyline
· Visual conceptual (strategic) problem solving, including change analysis for personal and business development as well as explanation of how things work in time
· Idea generation and object (product) design, especially those based on ideal objects or IVY-products
· Illustration of the evolution of a product or system
· Tool for scenario learning39, especially using IVY-final results from the IVY-matrix of bipolar variables, dimensions, and criteria
· Illustration, exploration, and analysis of change patterns in Neuro-Linguistic Programming (NLP)
· As an object on an IVY-template

Although the scene-transformation matrix may be used for many purposes, this article focuses on using a scene-transformation matrix for conceptually solving problems and/or inventing objects. This use of the matrix is similar to TRIZs graphic use of miniature dwarves and USITs morph cartoons. While TRIZ and USIT use the “And/or Tree” to generate ideas, Ideal SuperSmart™ Learning uses CreaLogical Object-FieldBot Analysis and Structured Intuition, Analysis, and Reflection (SIAR).

f11

When a scene-transformation matrix is used for conceptual problem solving or design, scenes may be sketched for initial (present) and end (long-term) situations of the system, like in the graphic method for miniature dwarves and morph cartoons. The end, desired, or long-term situation may be a sketch of the Ideal Final Result (IFR). Adjacent scenes on a timeline – past and/or medium-term – may then be inserted in cells of the scene-transformation matrix. Next, consecutive scenes are examined and the differences marked using an “x.”
Each difference indicates a change in position, materials, and/or equilibrium of forces. Such changes are referred to as changeBots and may involve the use of existing objectBots (bodyBots) as well as the introduction, transformation, and removal of objectBots. Introduced objectBots are also represented using an “x”, while removed or redundant objectBots are represented using a strike-through symbol (-) on the symbol “x”.

Like in TRIZs Substance-Field model, creaLogical object-fieldBot analysis assumes that materialBots and fieldBots (forceBots) are the fundamental causes of changes in scenes. MaterialBots may be represented using a circle on top of a rectangle (as for bodyBots) and forceBots using arrows. In a scene-transformation matrix, forceBots are introduced within the framework of Newton’s laws of motion. Of particular use is Newton’s third law of motion, which could be interpreted as: “To every action (forceBot), there is an equal and opposite reaction (forceBot).” Thus, the forceBots in each scene should be in equilibrium.

Scenes are visually analysed using the logic of IVYality as well as the laws of conservation of energy (matter) and momentum. BodyBots and materialBots could therefore acquire “magical” properties that obey physical laws. The magical properties of materialBots may be described as “technologically highly advanced.” The aforementioned statement is a reflection of Arthur C. Clarke’s statement: “Any sufficiently advanced technology is indistinguishable from magic.”

For conceptual problem solving using the scene-transformation matrix, the following questions may be useful:
· What are the initial (present) and end (desired/long-term/ideal) scenes?
· What are the other scenes, past and/or medium-term?
· What are the basic assumptions for materialBots (bodyBots), forceBots, interfaces (connection/joints), and multi-level resources in each scene?
· What are the changes between consecutive scenes?

· What do the changes or changeBots represent?
· What fieldBots (forceBots) and materialBots are responsible for these changes? How could forceBots and resourceBots be introduced to cause the changes?
· What (side) effects, in terms of forces and materials, are caused by the materialBots and forceBots? And how?
· What (ideal) properties as well as parameters of materialBots, forceBots, and resourceBots are required to cause desired changes as well as side effects?
· How to introduce, transform, remove, and neutralise materialBots and forceBots, especially those that are undersired?
· To what other transformation-events, situations, or patterns could selected solution-paths be applicable?

5.8 CreaLogic
“CreaLogic” is a concept I developed for classifying objects according to certain criteria of equivalence or coherence. CreaLogic is strongly related to the principle of object equivalence. CreaLogic may be used to multidimensionally improve one’s perception of situations and objects as well as to explain instances of sudden insight and breakthrough thinking.

It is my experience that many creative insights that appear logical in hindsight reflect the concept of creaLogic. For example, Kekule’s discovery of the benzene molecule as a result of an alleged reverie is more convincingly explained using “bisociation” and creaLogic. The discovery is a case of “morphoLogic”, i.e., the equivalence of shapes (a snake biting its tail & a “ring”), that occurred after Kekule had implicitly established the criteria for the structure of the benzene molecule.
MorphoLogic is a category of creaLogic. Common categories of creaLogic are stated below:
· MorphoLogic: similarity and equivalence of shapes (forms), e.g., number-shape system for mnemonics; ambigrams; fractals; topological shapes; digits/letters-parts of human face; visual metaphors; “impossible” objects; metonymies; icons.
· StructurLogic: similarity and equivalence of structure, e.g., Noam Chomsky’s “phrase-structure” template; object-templates; isomorphic objects.

· FunctionLogic: similarity and equivalence of functions, meanings, or uses; this is often the basis of symbolic logic or rationality. Examples are mathematical equations and formal scientific proofs; synonyms; similar functions of artefacts; functional metaphors; abbreviations.
· AuraLogic: similarity and equivalence of sounds, e.g., puns; rhymes; number-sound system for mnemonics.
· KinesLogic: similarity and equivalence of movements, e.g., sign language; digit-letter system for mnemonics; equivalence in kinetic paradoxes.
· SynaesLogic: similarity and equivalence between different sensory representations or forms of creaLogic, e.g., synesthesia; logograms; nomograms or Root-Bernsteins’ pictograms (equivalence between a picture/shape and a word); concrete poetry (equivalence between a picture/shape and sentences/paragraphs).
· MisceLogic: similarity and equivalence of the miscellaneous, e.g., temporaLogic, spatioLogic, and colourLogic.

The concept of creaLogic may share some similarities with “analogic” (Holyoak & Thagard, 1996) and Ulam’s “metalogic” (Root-Bernstein & Root- Bernstein, 1999). Like in analogic, creaLogic – especially morphoLogic, auraLogic, and kinesLogic – may be innate and intuitive. Holyoak & Thagard state that, “[A]ll vertebrates have implicit knowledge of similarity and can make use of it to react adaptively to their environments.”

Related to the concept of creaLogic are isomorphism (which refers to both morphoLogic and structurLogic) and Holyoak & Thagard’s multiconstraint theory for interpreting analogies. In the language of creaLogic, the multiconstraint theory deals with functionLogic (“similarity” and “purpose”) and structurLogic (“structure”). CreaLogic is also strongly related to “paoisms.” Both creaLogic and paoisms facilitate “creative seeing”, multi-level thinking, and knowledge transfer through analogies. And both could be used as tools for idea generation and creative exploration, especially if one decides to develop a thesaurus and dictionary of creaLogic.

5.9 Object-Templates
There are four basic types of structural templates: stone-heap, chain (linear), tree (hierarchical), and web (network)-templates; see item 6 in the IVY-matrix (table 6). Categories of descriptions for each of these templates include the following: visual, verbal, kinaesthetic, olfactory, and gustatory. Brief explanations of functions of the basic structural templates are given below:
· Stone-heap-Templates: for individual “objects”, i.e., discrete elements that appear not to relate to each other.
· Chain-Templates: for “objects” that are in a sequence or form a “chain.”
· Tree-Templates: for “objects” that are in a hierarchy or form a “tree.”
· Web-Templates: for “objects” that are in a network or form a “web.”
Object-templates may be used to classify objects and patterns as well as visually record, explore, and generate ideas in diverse domains. All node-link diagrams could be classified using the four templates. Examples of objecttemplates are shown in table 10.

As could be seen in table 10, object-templates exist in and could be applied to diverse domains. Mintzberg & van der Heyden (1999) note that the basic forms of organising business as well as the four philosophies of managing could be described as the “set”, “chain”, “hub”, and “web.” These concepts of organising and managing are respectively similar to the templates of stone-heap, chain, hierarchy, and web. Mintzberg & van der Heyden present their tool of organigraphs, which deal with visually presenting the structure and activities of organisations using the set, chain, hub, and web. According to Mintzberg & van der Heyden, organigraphs are far more useful than traditional organisational (hierarchical) charts.

The principles of object equivalence and multi-polarity could be used to draw several conclusions from table 10. For example, objects in a particular cell of the table could be considered equivalent so that one object could be transformed into another “equivalent” object. With regard to creativity tools and techniques, the classic mind map, fishbone diagram, toothache tree, and a table may be considered structurally equivalent. Consequently, information expressed in any of these forms could be converted to another equivalent form. Of course, there are advantages and disadvantages associated with each form with regard to the purpose, ease of use, and understanding.

Another conclusion is that systems such as in writing and production generally evolve from chains through hierarchies to networks.

f12

6.0 RAPIDLY EVALUATING STRATEGIC (CONCEPTUAL) SOLUTIONS
There are many methods for evaluating alternative solutions to open-ended problems. Evaluation methods could be categorised as qualitative and quantitative. Qualitative evaluation methods are quick and relatively easy to use, especially for shortlisting and group evaluation of alternatives.
Common qualitative methods include the following:
· intuition (aesthetic sensibility or visual inspection using binary categories such as impressive/not impressive; beautiful/not beautiful; acceptable/not acceptable)
· classification or sorting (using spider diagrams; grids; tables; affinity diagrams; sticking dots; clustering);
· voting or (experts’/peers’) consensus on preferences
· checklist (using binary categories of yes/no; satisfied/not satisfied; symmetrical/asymmetrical)
· negative brainstorming
· critical analysis (advantages/disadvantages; SWOT:

Strengths/Weaknesses/Opportunities/Threats; force field: forces for/forces against)
The rating scales for qualitative evaluation are mainly nominal and ordinal. In qualitative evaluation, objectives are usually subsumed in the selection of rating scales, especially in critical analysis. This approach contrasts that of quantitative evaluation.
Quantitative evaluation methods use explicit objectives and criteria such as “zero- or minimum” variables (cost/energy/time/defect) on the one hand and “maximum or infinity-” variables (benefit/profit/quality/safety) on the other hand. Quantitative criteria are usually rated on ordinal and interval scales. In general, quantitative methods are more time-consuming than qualitative methods and therefore more applicable to shortlisted alternatives and the phase of detailed analysis. The most commonly used quantitative approaches belong to the category of multi-criteria methods. As the focus of this section is on rapidly evaluating conceptual solutions, quantitative approaches are not considered in detail.

Ideal SuperSmart™ Learning is primarily based on the objectives of ideality, versatility, and impossibility. Ideal SuperSmart™ Learning uses both qualitative and quantitative criteria. Archetypal or macro-criteria of Ideal SuperSmart™ Learning are based on the following conditions of (practical) ideality:
· ideal (“functional”) nothingness, e.g., zero defect; zero tolerance; least effort; minimum energy; free (external) resource
· ideal infinity, e.g., total quality; infinite versatility; perfect information
· ideal efficiency & automaticity, e.g., maximum efficiency; selfcontainment40; self-organisation; self-regulation; self-working; selfoperating; automatic
· ideal conflict resolution & unity, e.g., win-win; no trade-off or compromise; no conflict, contradiction, dilemma, or paradox; perfect unity, integration, or networking
· ideal simplicity, variety, & beauty, e.g., the most simple (Occam’s razor); requisite variety; symmetry; beauty; asymmetry; elegance · ideal identification, detection, and branding, e.g., universal recognition or branding
To rapidly classify and assess alternative solutions that are related to the objectives and criteria of Ideal SuperSmart™ Learning, the IVY-pyramid of innovation is presented; see table 11. This pyramid of innovation uses concepts from TRIZs levels of inventions (solutions) and Magaret Boden’s levels of creativity41. The concepts of ideality, versatility, and impossibility are subsumed under “Unusuality.” 42
Like in TRIZs level of inventions, the IVY-pyramid of innovation has five levels. Thus, the IVY-pyramid could be directly related to the levels of invention. Unlike the levels of invention in TRIZ, categories in the IVY-pyramid reflect ordinal rather cardinal (empirical) relationships between levels.

f13

The IVY-pyramid of innovation in table 11 could be regarded as an inverted pyramid.43 At level 1 is the base of the pyramid. Closest to the apex or vertex of the pyramid is level 5. The pyramid indicates that the highest levels of unusuality are obtained in open-system solutions. Nevertheless, closed (self-contained)-system solutions can also be strikingly unusual, especially those at level 3. Albert Einstein, the great physicist, is reputed to have said: “The significant problems we face cannot be solved at the same level of thinking we were at when we created them.” My interpretation of this comment is that if a problem in a paradigm44 or closed system is intractable, then its solution would be found at a higher level or in a more open-system. In other words, solutions to intractable problems are likely to involve a paradigm shift. This interpretation is consistent with the evolution of solution-spaces in the IVY-pyramid of innovation.

In Ideal SuperSmart™ Learning, objects that move towards ideality, ideal efficiency, or level 5 would loop through the IVY-pyramid in a spiral or dyadic cycle of closed- and open-system solutions. A “first-time ever” solution or genus is initially regarded as a closed system at level 1. However, the system may have disadvantages, deficits, or undesirable side effects. The system is easily improved using core knowledge in the domain. Many and mostly superficial variants of closed-system solutions exist at levels 1 and 2.

Variants of closed-system solutions, however, reach their limit or saturate at level 3 where available core domain ideas would have been exhausted.

Nevertheless, the system may still have unresolved disadvantages, deficits, or side effects. Further improvements of saturated closed-system solutions may result in added complexity (technical contradictions) in other parts of the system; the situation is similar to that in a wicked problem. Rare core domain ideas and “limited” peripheral knowledge must therefore be applied. At level 4, a “knowledge impasse” is therefore imminent. Consequently, major breakthroughs in saturated closed-system solutions would require more external knowledge, which is likely to be available in peripheral domains.

As the complexity of saturated closed-system solutions increases, more refinements may be obtained by using little known or available knowledge, especially knowledge from remote domains. At full maturity and complexity of the solutions, further refinements are inefficient and the highest level solution – of which a paradigm shift is a prerequisite – may produce a next-generation object or genus which subsequently emerges at level 1. This cycle of closed and open-system solution is analogous to a product’s “extended” S-curve.

Level 1 corresponds to the birth of a product; level 3 is the stage of growth;
level 5 is maturation. If further improvements are not made to solutions at
level 5 to obtain a contiguous S-curve, the product may “die” in time. This latter description corresponds to the decline and death phases of the life cycle curve.

The IVY-pyramid of innovation is both descriptive and normative. It could be used to describe, classify, and determine the level of innovation of single product, a family of products, system’s outputs, generated ideas, and alternative solutions. The pyramid could also be used to “guesstimate” or forecast45 next-generation solutions and consequently, gaps in the solutionspace for improving a product or system. Thus, artefacts or products need not progress directly or sequentially through the pyramid. Finally, the IVYpyramid of innovation could facilitate the finding of inventive problems and identification of knowledge deficits as well as the formulation of strategies for product development and system evolution.

7.0 CONCLUSIONS
The Theory of Ideal SuperSmart™ Learning is many things to many people.
To me, the Theory of Ideal SuperSmart Learning is like a “theory of everything” for personal, business, product, and institutional development. The Theory of Ideal SuperSmart™ Learning places “understanding” at the core of personal, business, product, and institutional development. At a personal level, the result of successfully applying the Theory of Ideal SuperSmart™ Learning should be a “SuperSmart-understanding” individual. At an institutional level, successful application of the theory should result in a “SuperSmart-understanding” organisation. At an operational level, the Theory of Ideal SuperSmart Learning could be regarded as a tool for uncovering as well as creating patterns for practical problem solving, creativity, and ideas management, much like in algebra. The Theory of Ideal SuperSmart™ Learning may also be considered as a multi-faceted learning approach.

The multi-methodology framework of the Theory of Ideal SuperSmart™
Learning facilitates the integration of tools for problem solving, creativity, and ideas management. In particular, the theory could be used to rapidly simplify and learn TRIZ as well as integrate TRIZ with other problem solving methodologies, for example using the creative web – ARIZ framework. The simplification of TRIZ is mainly obtained through deconstruction, restructuring, and generification of classic (C-) TRIZ, not through the elimination of parts of TRIZ. I have termed as “S-TRIZ” the combination of the Theory of Ideal SuperSmart™ Learning and classic TRIZ.

S-TRIZ is different from C-TRIZ in many ways. First, S-TRIZ does not depend on a technical knowledge base such as in a library of patents or detailed algorithms as in ARIZ. Thus, S-TRIZ could be more easily and rapidly applied to a wider range of situations, such as in product development, strategic management, and software development. Second, the epistemology of STRIZ is different from that of C-TRIZ. While C-TRIZ abhors the trial-and-error (experimental) approach to problem solving and creativity, S-TRIZ considers trial-and-error, in particular selective trial-and-error, as inherent in learning, creativity, and problem solving. The epistemology of S-TRIZ is therefore more suited to dealing with ill-defined or personally novel problems. In these latter cases, S-TRIZ advocates a structured intuition, analysis, and reflection approach (SIAR) as well as use of the creative web.

S-TRIZ is also a multi-level approach. On the one hand, S-TRIZ could be simple and provide an overview of TRIZ together with application of some basic tools. On the other hand, S-TRIZ could be deeper and provide a more comprehensive view of TRIZ, especially in combination with other methodologies. The use of a particular level of S-TRIZ depends on a user’s expertise and demands of a problem situation.

The Theory of Ideal SuperSmart™ Learning could be used for conceptual as well as detailed problem solving and creativity. A user could select tools from the “menu” of tools and apply them to a given situation. However, for rapid problem solving, the following “quartet” of tools could be particularly useful: IVY-template; IVY-matrix; SCAMPER-DUTION matrix; IVY-pyramid of innovation. If a user is thoroughly familiar with heuristics and algorithms of problem solving or creativity, then only the IVY-template may be used within the framework of structured intuition, analysis, and reflection. The IVYtemplate also provides a framework for comprehensively managing ideas.

In this article, only one part of the cycle of the PSLT game is covered, i.e., expository learning. For completion of the basic learning cycle for the PSLT game as well as proficiency in the Theory of Ideal SuperSmart™ Learning or S-TRIZ, the modules of problem-solving learning, experiential learning, and hierarchy of reflection should be completed by a user, for example, by applying the tools to problems in real-life situations and reflecting on the process. More practical, theoretical, and reflective experiences on the Theory of Ideal SuperSmart™ Learning could be obtained by joining a learning community (network) at the following web site: www.supersmartnetwork.com.

The presentation of the Theory of Ideal SuperSmart™ Learning in this article places emphasis on a systematic (structured) approach to problem solving, creativity, and ideas management. In other words, I have focused on one end of the bipolar spectrum of learning. At the other end of the spectrum is an organic (unstructured) approach. The overall shape of systematic creativity is characterised by convergent thinking, while organic creativity focuses on divergent thinking, “chaos”, and intuition. My experience is that both approaches are useful and should be accessible when solving problems.

Using this bipolar approach which is espoused in the B.E.A.R strategy, I have managed to develop a software prototype that invents not only magic tricks but also humourous pieces, story plots, and aphorisms.

The more ill-defined or wicked a situation is, the less useful may be detailed systematic approaches. In an “impossible” or a “goalless” situation, organic creativity may be a most desirable option. The creative web could also be useful. However, as organic creativity is difficult to describe, I have summarised my experience of it in a poem below. So end my ruminations on the Theory of Ideal SuperSmart™ Learning.

THE MAGIC OF ORGANIC CREATIVITY
You are in the jungle.
You are walking.
But you don’t know exactly where you are going.
You are searching.
But you don’t know exactly what you are looking for.
Meanwhile, you’re gathering, picking up, discarding, and carrying forward pieces, pieces of an unknown jigsaw puzzle.
Perhaps, a 1050-piece Photomosaic Jigsaw Puzzle.
Some pieces may in fact not relate to the final picture.
But you’re unaware of this.
You continue your blind adventure,
roaming, picking up, discarding, carrying forward, and rearranging pieces.
Suddenly, you realise that you’ve formed a novel, harmonious, beautiful but rough picture.
You smile to yourself, “Aha! That’s it!”
That’s Organic Creativity!
It’s fun, it’s mysterious, it’s magic, and
it’s a joy!

REFERENCES
Alexander, C. (1979) The Timeless Way of Building. New York: O.U.P.
Altshuller, G. (1996) And Suddenly the Inventor Appeared. Massachusetts:
Technical Innovation Center.
Barker, J.A. (1993) Paradigms. New York: HarperBusiness.
Barrow, J.D. (1999) Impossibility. London: Vintage.
Barrow, J.D. (2000) The Book of Nothing. London: Jonathan Cape.
Biggs, J. (2000) Teaching for Quality Learning at University. Buckingham:
Open University Press.
Boden, M. (1996) The Creative Mind. London: Abacus.
Bowman, C.F. (ed.) (1996) Wisdom of the Gurus: A vision for object technology. New York: SIGS.
Bransford, J.D.; Stein, B.S. (1984) The IDEAL Problem Solver. New York:
W.H. Freeman and Company.
Brockbank, A.; McGill, I. (1998) Facilitating Reflective Learning in Higher
Education. Buckingham: SHRE & Open University Press.
Buzan, T.; Buzan, B. (2000) The Mind Map Book. London: BBC Books.
Campbell, J. (1993) The Hero with a Thousand Faces. London: Fontana.
Checkland, P. Soft Systems Methodology in Action in: Rosenhead, J.;
Mingers, J. (eds.) (2001) Rational Analysis for a Problematic World Revisited:
Problem structuring methods for complexity, uncertainty, and conflict. West
Sussex: John Wiley & Sons, Ltd, pp. 91-113.
Clarke, T.; Clegg, S. (2000) Changing Paradigms: The transformation of management knowledge for the 21st century. London: HarperCollinsBusiness.
Cowan, J. (1998) On Becoming an Innovative Teacher. Buckingham: SHRE &
Open University Press.
Covey, S. (1999) The Seven Habits of Highly Effective People. London:
Simon & Schuster UK Ltd.
Dawkins, R. (1988) The Blind Watchmaker. London: Penguin Books.
De Bono, E. (1994) De Bono’s Thinking Course. London: BBC Books.
De Bono, E. (1995) Serious Creativity. London: BBC Books.
Delp, P.; Thesen, A.; Motiwalla, J.; Seshadri, N. (1977) Systems Tools for
Project Planning. Indianna: PASITAM.
Domb, E. (2000) Strategic TRIZ and Tactical TRIZ: Using the technology evolution tools. http://www.triz-journal.com/archives/2000/01/e/index.htm
Domb, E.; Dettmer, H.W. (1999) Breakthrough Innovation in Conflict
Resolution. http://www.triz-journal.com/archives/1999/05/b/index.htm
Edwards, B. (1995) Drawing on the Artist Within: How to release your hidden creativity. London: HarperCollinsPublishers.
Eysenck, H.; Keane, M.T. (1999) Cognitive Psychology. Sussex: Psychology Press.
Fahey, L.; Randall, R.M. (eds.) (1998) Learning from the Future. New York:
John Wiley & Sons, Inc.
Fisher, R.; Ury, W. (1991) Getting to yes: Negotiating an agreement without giving in. London: Business Books Limited.
Fitzkee, D. (1989) The Trick Brain. USA: Lee Jacobs Productions Publication.
Forsha, H.I. (1995) Show me: The complete guide to storyboarding and problem solving. Wisconsin: ASQC Quality Press.
Goldratt, E.M. (1994) It’s Not Luck. Hampshire: Gower.
Greenfield, T. (ed.) (2002) Research Methods for Postgraduates. London:
Arnold.
Gross, R.; McIIveen, R. (1997) Cognitive Psychology. London: H & S.
Hall, L.M.; Bellnap, B.P. (2001) The Sourcebook of Magic: A Comprehensive
Guide to the Technology of NLP. Carmathen: The Cromwell Press.
Heller, R. (2000) Bill Gates. London: Dorling Kindersley.
Hermann, K.R. (2001) Visualizing Your Business. New York: John Wiley &
Sons, Inc.
Higgins, J.M. (1994) 101 Creative Problem Solving Techniques. Florida: The
New Management Publishing Company.
Hirshberg, J. (1999) The Creative Priority. London: Penguin Books.
Holyoak, K.J.; Thagard, P. (1996) Mental Leaps: Analogy in creative thought.
Massachusetts: The MIT Press
Horowitz, R. (2001) ASIT’s Five Thinking Tools With Examples.
http://www.triz-journal.com/archives/2001/09/b/index.htm
Horowitz, R.; Maimon, O. Creative Design Methodology and the SIT Method in: Proceedings of DETC ’97 – 1997 ASME Design Engineering Technical
Conference. Sacramento: September 14-17, 1997.
Jones, J.C. (1980) Design Methods. Bath: The Pitman Press.
Kelly, T.; Littman, J. (2001) The Art of Innovation. London: HarperCollins.
King, R. Synthesis and Evaluation of Creativity in: Greenfield, T. (ed.) (2002)
Research Methods for Postgraduates. London: Arnold, pp. 126-136.
King, R. When to use Creativity in: Greenfield, T. (ed.) (2002) Research
Methods for Postgraduates. London: Arnold, pp. 121-125.
Koestler, A. (1971) The Art of Creation. London: Pan Books Ltd.
Koestler, A. (1976) The Ghost in the Machine. London: Hutchinson & Co. Ltd.
Kolb, D.A. (1984) Experiential Learning. New Jersey: Prentice Hall, Inc.
Kovalick, J. (1997) Altshuller’s Greatest Discovery – And Beyond.
http://www.triz-journal.com/archives/1997/08/a/index.html
Kovalick, J. (1998) Triads: Their Relationship With TRIZ.
http://www.triz-journal.com/archives/1998/06/a/index.htm
Kuhn, T.S. (1996) The Structure of Scientific Revolutions. Chicago: The
University of Chicago Press.
Laurillard, D. The Changing University. The Open University.
http://itech1.coe.uga.edu/itforum/paper13/paper13.html
Majaro, S. (1991) The Creative Marketer. Oxford: Butterworth-Heinemann.
Mann, D.; Stratton, R. (2000) Physical Contradictions and Evaporating
Clouds. http://www.triz-journal.com/archives/2000/04/b/index.htm
Mann, D. (2001) Systems Operator Tutorial 1) 9-Windows on the World.
http://www.triz-journal.com/archives/2001/09/c/index.htm
Mann, D. (2001) Systems Operator Tutorial 2) Between the Boxes – Changing
Perspectives.
http://www.triz-journal.com/archives/2001/11/b/index.htmMichalko, M. (1998)
Cracking Creativity. California: Ten Speed Press.
Michalko, M. (1998) Thinkertoys. California: Ten Speed Press.
Mintzberg, H.; van der Heyden, L. Organigraphs: Drawing how companies work in: Harvard Business Review, September – October 1999, pp. 87-94.
Morgan, G. (1997) Images of Organization. California: Sage Publications, Inc.
Nader, G.; Hibino, S.H.; Farrell, J. (1999) Creative Solution Finding. California:
Prima Publishing.
Popper, K. The Logic and Evolution of Scientific Theory in: Popper, K. (1999)
All Life is Problem Solving. London: Routledge.
Root-Bernstein, R.; Root-Bernstein, M. (1999) Sparks of Genius: The 13 thinking tools of the world’s most creative people. New York: Houghton Miffin Company.
Rosenhead, J.; Mingers, J. (eds.) (2001) Rational Analysis for a Problematic
World Revisited: Problem structuring methods for complexity, uncertainty, and conflict. West Sussex: John Wiley & Sons, Ltd.
Salamotov, Y. (1999) TRIZ. Hattem: Insytec B.V.
Savin-Baden, M. (2000) Problem-based Learning in Higher Education.
Buckingham: SRHE & Open University Press.
Savransky, S.D. (2000) Engineering of Creativity: Introduction to TRIZ methodology of inventive problem solving. Florida: CRC Press.
Schön, D.A. (1983) The Reflective Practitioner. USA: Basic Books.
Schön, D.A. (1987) Educating the Reflective Practioner. USA: Basic Books.
Schragenheim, E. (1999) Management Dilemmas: The Theory of Constraints approach to problem identification and solutions. Florida: CRC Press.
Senge, P.; Kleiner, A.; Roberts, C.; Ross, R.B.; Smith, B.J. (1999) The Fifth
Discipline Fieldbook. London: Nicholas Brealey Publishing.
Sickafus, E.N. (1997) Unified Structured Inventive Thinking. Michigan:
NTELLECK.
Siler, T. (1997) Think Like a Genius. London: Bantam Press.
Simon, H.A. (1998) The Sciences of the Artificial. Mass.: The MIT Press.
Slywotzky, A.J.; Morrison, D.J.; Moser, T.; Mundt, K.A.; Quella, J.A. (1999)
Profit Patterns: 30 Ways to anticipate and profit from strategic forces reshaping your business. West Sussex: John Wiley & Sons, Ltd.
Sternberg, R.J. (ed.) Handbook of Creativity. New York: C.U.P.
Taylor, D.A. (1992) Object-oriented Information Systems. New York: John
Wiley & Sons, Inc.
Von Oech, R. (1992) A Whack on the Side of the Head/Whack Pack.
California: Creative Think.
Wallas, G. (1926) The Art of Thought in: Vernon, P.E. (ed.) (1970) Creativity.
Middlesex: Penguin Education, pp. 91-97.

About the author
Dr. Rodney K. King
www.supersmartnetwork.com
r.k.king@supersmartnetwork.com
* Meta-inventor
* Inventor/Author of many items including the following:
Theory of Ideal SuperSmart™ Learning;
Versatile Thinking™ (including PAO Thinking™ and Versatile Map™);
Six Colored Eyes
* Developer/Teacher of “S-TRIZ”
* Conjurologist
* Civil Engineer; Infrastructure Planner; Regional Development Planner
* Problem Solving, Creativity, and Ideas Management Consultant/
Facilitator
Copyright 2002. Dr. Rodney K. King.
Readers of The TRIZ Journal are authorized to download and make one copy of this article for personal study. No other reproduction is permitted without prior written permission from Dr. Rodney K. King.