Patterns of Evolution:
Recent Findings on Structure and Origin[1]

Boris Zlotin and Alla Zusman

Ideation International

Southfield, MI

February 2006

Abstract

The Patterns of Technological Evolution are the heart of the Theory of Inventive Problem Solving (TRIZ) and the driving force in the transformation of TRIZ into a science of technological evolution. Since the mid-1970s, when Genrich Altshuller published his first set of patterns, numerous TRIZ specialists have worked in this area, primarily in attempts to find the most advantageous structure and create a complete system of patterns. These attempts, however, have had limited success due to the patterns’ empirical nature and a lack of understanding of their origin. In this paper the authors share their latest findings in the area related to the following:

• Linking technological evolution with the evolution of human needs (evolution of markets)
• Refining and deepening knowledge about existing patterns of evolution
• Formulating new patterns
• Developing the general structure of the patterns
• Developing analytical instruments for effective utilization of the patterns, not only for problem solving but for predicting future generations of systems and controlling their evolution.

 

Introduction

History

The main efforts of Genrich Altshuller (the originator of the Theory of Inventive Problem Solving, or TRIZ) and his followers were directed toward a very practical and well-defined goal: the development of methods for finding inventive solutions to difficult technological problems. This approach was successful in that it provided effective results relatively quickly. But this same success somewhat overshadowed the fact that the most valuable outcome of Altshuller’s endeavor was the discovery of patterns of technological evolution, which in turn provided a means of controlling the evolution of technological systems rather than merely solving ongoing problems.

Starting with Aristotle, the identification of a set of universal evolutionary patterns was a goal of philosophers, scientists, and many others; rather limited success was achieved, mostly by those who focused on the study and analysis of real-life systems[2] instead of abstract philosophical considerations.

Altshuller’s search for basic patterns of technological evolution started when he began his work on TRIZ.[3] Consequently, in the late 1940s he formulated patterns that became fundamental to TRIZ, such as the evolution of technological systems toward increased ideality through the resolution of contradictions. But Altshuller’s focus was a practical one and thus his main efforts were directed toward developing the Inventive (Innovation) Principles and the Algorithm of Inventive Problem Solving (ARIZ). The first seven principles were published in 1964[4]; by 1969 there were 35 principles, and finally in 1973[5] the 40 Inventive Principles were published (Altshuller had distributed the final list of principles among TRIZ followers and students around 1971).

The relatively wide practical application of the 40 Inventive Principles during the 1970s revealed the strengths and weaknesses of this first TRIZ knowledge-based tool.[6] The main problem was evident in the dramatic range of efficacy of the principles: while certain principles prompted fairly conventional solutions (such as principle 3, local quality), others yielded strong solutions with narrow application (32, changing the color) and some offered robust and widely-applicable solutions that could be further refined and strengthened. In time it became clear that the more powerful Inventive Principles represented strong, recurrent Patterns of Technological Evolution (such as 15, dynamicity) or supported them (25, self-service as a way to increase the ideality of a system).

In the spring of 1975 Altshuller distributed a manuscript with the first set of Patterns of Technological Evolution among TRIZ schools. These seven-pages became the most valuable component of TRIZ and established the foundation for TRIZ as a science.[7]

The set of patterns included three groups named after the laws of theoretical mechanics:

Group 1 – Statics – determines the beginning of a system’s life cycle, including:

1. Completeness of an engineered system
2. Energy flow in an engineered system
3. Harmonization of the synchronization rhythms or parts in an engineered system

Group 2 – Kinematics – determines the general evolution of a system, including:

4. Increasing ideality of an engineered system
5. Non-uniform evolution of subsystems comprising an engineered system
6. Transition to the overall system

Group 3 – Dynamics – reflects evolution in contemporary conditions involving certain physical and technical factors, including:

7. Transition from macro- to micro-level in an engineered system
8. Increasing substance-field involvement

While continuing his work on the Patterns, Altshuller established a critical requirement: a formulated pattern must not only be informative (describing how systems evolve) but must be prognostic, making it possible to predict the directions in which a given system would evolve; and instrumental, helping to realize these directions and ultimately control the system’s evolution.

In the fall of 1975, Boris Zlotin began teaching a course on the Patterns of Technological Evolution to second-year students at the St. Petersburg People’s University for Technical Innovation (SPUTI). During this and subsequent courses, Altshuller’s Patterns were presented in detail and illustrated with many examples, including military weaponry and even tactics and strategy.[8] The active participation of many of the students (among whom were a number of talented engineers) prompted new ideas on the subject.[9] At the same time, it was noted that the suggested structure of statics-kinematics-dynamics was more confusing than beneficial.

In 1980 the first TRIZ conference was held in Petrozavodsk, Russia, and the Patterns of Technological Evolution were a topic of discussion. A leading TRIZ theoretician, Vladimir Petrov, suggested that the Patterns be combined with certain aspects of classical system analysis; Boris Zlotin suggested the addition of patterns describing the evolution of technological processes; Esther Zlotin reported her findings about patterns in the evolution of music.

In 1981, two full scale TRIZ seminars took place:

• A four-week seminar held in Moscow for Value Engineering specialists from the electrical industry
• A three-week seminar in Kishinev (Chisinau), Moldova for members of the local Society of Inventors

Both seminars were conducted by Genrich Altshuller, with Boris Zlotin serving as a second instructor. As was the custom, other TRIZ specialists and instructors attended these seminars to update their TRIZ knowledge and enhance their teaching skills; among them were Vladimir Gerasimov, Tatiana Kurashova, Valentin Bogach, Victor Fey, Isaac Bukhman, Valery Shteinberg, Igor Kondrakov, Boris Farber, Igot Kulikov, and others. Unrestricted communication and fruitful discussions led to significant contributions to the Patterns, and prompted Boris Zlotin to develop a hierarchical structure for the Patterns that included more detailed descriptions (sub-patterns) that were later called Lines of Evolution.[10] Although this structure was later criticized for its redundant complexity, the most important output of this attempt was the recognition that much room existed for enhancing and further developing the Patterns.

In late 1981, Alla Zusman, who had attended a TRIZ seminar in Kishinev, began teaching her own class on TRIZ in the organization where she worked. She gathered all available material on the Patterns and, in organizing it for teaching purposes, attempted to coordinate the Patterns with Hegel’s system of dialectics.

Since the summer of 1982 the authors have worked together in the field of TRIZ, often with other attendees from the Kishinev seminar (Vladimir Proseanic, Anatoly Ioysher, Bella Rykova, Valery Yanov) and students of Alla Zusman (Len Kaplan and Alex Chernobelsky). Gradually, the Kishinev TRIZ School was established and later included other TRIZ practitioners from Kishinev and elsewhere (Svetlana Visnepolschi, Zinovy Royzen, Vladimir Oleynikov, Vladimir Shapiro, Sergey Malkin, Lev Pevzner, Igor Kholkin, Valery Prushinskiy, and others).

The Patterns of Evolution have been the primary focus of the Kishinev TRIZ School since its inception.[11] Research efforts have included studies in biological evolution (advised by Vladimir Petrov and including non-Darwinian theories) as well as the evolution of science, art, language, social systems, etc. They were in continuous dialogue with Altshuller about their work, via correspondence and in person during numerous TRIZ seminars (12 seminars, from 2- to 4-weeks long between 1981 and 1986).[12]

Other TRIZ schools and independent TRIZ specialists have been actively working in this area. In 1982, Vladimir Petrov presented two important papers at the second TRIZ conference in Petrozavodsk, based on:

• Forecasting the evolution of electrical welding equipment (the first large-scale forecasting based on the Patterns of Technological Evolution)
• Introducing the concept of “excessiveness” in technological systems. According to this concept, every technological system possesses more capabilities than are necessary for normal functioning; these excessive capabilities can be revealed and utilized to increase the system’s ideality. In addition, it is possible to identify new applications for underutilized substances, fields, information, etc. – the concept of redundancy in technological systems.

In 1985, Genrich Altshuller introduced a well-developed concept regarding the utilization of substance-field resources (in other words, excessive capabilities) in the Algorithm for Inventive Problem Solving (ARIZ), which became a very fruitful concept.[13]

At the TRIZ conference in Novosibirsk, Russia in 1984, several interesting works on the Patterns of Technological Evolution were presented, including:

• The “pulsing” model of evolution, by Yury Salamatov and Igor Kondrakov[14]
• The increasing complexity and simplification of technological systems in the process of evolution, by Igor Vertkin[15]
• Evolutionary patterns of methods and devices for curing broken extremities, by Nikolai Predein[16]
• Two ways of increasing ideality of technological systems, by Boris Zlotin and Alla Zusman.

By 1985, the authors had concluded, based on work and discussions, that the approach to the process of revealing and formulating Patterns of Technological Evolution should be changed. Altshuller had always insisted that the creation of TRIZ tools be based solely on high-level inventions documented in the patent library. This approach had been successful for the Inventive Principles despite a disregard for whether the patented solutions had been implemented. But such an approach to revealing patterns of technological evolution created several problems:

• Excluding certain steps from the evolutionary lines just because they look obvious today renders the lines incomplete and narrows their application area; for example, dynamization in mechanical systems looks almost trivial, while dynamization in a chemical molecule can yield quite extraordinary effects.
• Many patented inventions have never been implemented because they are not feasible; others were patented for the sole purpose of misleading competitors, etc.

Given the above, the authors changed the focus of their research from the patent library to the history of technology. The first results were published in[17] The Profession of Searching for New Ideas. Besides the new approach, other changes were introduced, in particular:

• Upgrading the pattern of coordination of rhythms to matching-mismatching of all technological system parameters[18]
• Introducing a new pattern: reduction in human involvement
• A new structure for the Patterns, including multiple Lines of Evolution

In addition, several of Altshuller’s patterns were omitted from the new system for various reasons:

• Two patterns from the Statics group (completeness and energy flow in technological systems), as they represented the conditions for a system’s existence more than its evolution. Moreover, certain cases were found that contradicted these patterns.
• The pattern increasing substance-field involvement related more to system models than to the evolution of actual technological systems. However, the essence of the pattern related to the actual utilized field evolution, which was included as a line of evolution within the pattern transition to the micro-level.

Until 1985, the majority of studies on the Patterns were in technology, although examples of non-technical applications were known and utilized in educational courses. In 1986, a TRIZ course on the Patterns conducted by the authors at the Kishinev School included numerous case studies and a comparative analysis on evolution in biology, society, military strategy, arts, entertainment, sports, etc. The main focus shifted from problem-solving to TRIZ forecasting. Eight final projects of the 1986 course attendees were devoted to this topic; others included certain elements within it. For example, Alex Chernobelsky and Yakov Grinberg conducted TRIZ forecasting on methods for raising calves; Sergey Malkin and Len Kaplan developed methods for forecasting the evolution of measurement and control systems. Earlier, Boris Zlotin and Svetlana Visnepolschi conducted a comparison of traditional forecasting and TRIZ forecasting for water pumps. Later, TRIZ forecasting projects were performed for lifting cranes, helicopters, banks, mercantile and stock exchanges, educational systems, certain social systems, etc.

The first course was recorded and transcribed by TRIZ specialists Victor Ladoshkin and Yury Bychkov, supplied with comments from the authors, and distributed among TRIZ professionals. Valuable feedback from this course led to further development; the results were published in Searching for New Ideas: From Insight to Methodology; The Theory and Practice of Inventive Problem Solving,[19] and included:

• Development of definitions and fundamental elements for Patterns of Evolution
• Development of requirements for the process of revealing and formulating Patterns in any area
• Revealing the links between patterns in technological evolution and laws of nature and human intuition.
• Constructing a new set of patterns, including:

–        Stages of evolution (infancy, growth, maturity and decline)

–        Evolution toward decreased human involvement

–        Non-uniform development of system elements

–        Evolution toward increased ideality[20]

–        Evolution toward increased complexity followed by simplification

–        Evolution toward increased dynamism and controllability

–        Evolution with matching and mismatching elements

–        Evolution toward micro-levels and the increased use of fields

In addition, the following topics were discussed in Searching for New Ideas:

• General patterns of evolution
• Methodology for TRIZ forecasting
• Patterns of organizational evolution
• TRIZ and patent science
• TRIZ and elements of creative education
• TRIZ education
• A structured system of typical resources enabling the evolution of technological systems
• Typical mistakes in the evolution of technological systems, and ways to avoid them
• Approximately 30 lines of technological evolution, with examples

By 1991, the authors had attempted to adapt general patterns of evolution to the evolution of scientific systems (hypotheses and theories) and to R&D organizations.[21]

Since 1993, the authors have been working on patterns of evolution within the framework of Directed Evolution™, an extension of TRIZ forecasting.

The main challenges

Given the above, it can be said that over the last 60 years TRIZ has grown from a problem-solving methodology to a science of technological evolution, with the Patterns of Evolution at its core. At the same time, we know that all known Patterns are empirical in nature and therefore can describe the main direction (“what”) of a system and its actual evolution (“how”) but lack the “why” – that is, an explanation of the origin and driving forces of technological evolution. Obviously, finding answers to these questions is critical for revealing and structuring the Patterns and for TRIZ becoming widely recognized as a science.

Another important aspect of converting knowledge about evolutionary patterns into a real science is consensus with regard to the main definitions and assumptions. To date, TRIZ literature refers to laws of evolution, patterns of evolution, trends of evolution, and lines of evolution. Different translations from Russian into English and other languages also contribute to the confusion.

Definitions and assumptions

Definitions

The first attempt to clarify definitions for English terms for the main TRIZ elements related to technological evolution was made in 1999,[22] as follows:

An evolutionary trend is a sequence of events directly and/or indirectly connected through cause-effect relationships. Each event in the chain (alone or together with the others) leads to the next one and thus increases the probability of its emergence. A trend may represent a limited (specific) model of an evolutionary process that describes its specific feature(s). Examples of trends in social life, technology, science, fashion, art, etc. are well known.

Examples:

• Growth of “high-tech” technologies
• Increasing attention to the environment
• Increasing utilization of synthetic materials

The Patterns of Evolution represent a compilation of trends that document strong, historically-recurring tendencies in the development of man-made or natural systems. (And as was noted earlier, an identified pattern has predictive power.)

Examples:

• Evolution toward decreased human involvement
• Evolution toward increased dynamism and controllability
• Evolution toward micro-levels and the increased use of fields

The Lines of Evolution reflect the historical sequence of changes that a technological system undergoes during its evolution.

Example:

A multi-step transition that includes the following steps:

1. Use of a permanent field
2. Transition to a pulsed field
3. utilizing a pulsed field with matched frequency

While a trend might be a short-lived event (certain styles in consumer products, for example) patterns and lines represent the strongest long-term (often permanent) trends. In other words, a pattern of evolution addresses what exactly will happen as a result of evolution (increasing dynamism, for example); a line of evolution shows how this goal will be accomplished (step-by-step).[23]

Assumptions

Below are 19 assumptions supported by an extensive study of the history of evolution of various systems of different scale.[24]

Patterns and trends of evolution

The majority of man-made systems evolve not randomly but according to the pre-determined patterns described below. These patterns can be revealed by studying the history of evolution of various systems and can then be used to accelerate system evolution instead of waiting for the system to evolve “naturally.”

Patterns are hierarchical in structure and include multiple lines of evolution. The evolution of a system can be impacted by specific trends that occur at specific times. These trends are relatively short-lived and have their own lifecycle, including typical stages such as emergence, slow growth/impact, strong growth/impact, and weakening followed by disappearance and/or transformation into another trend.

The driving force of evolution

The majority of existing man-made systems evolve to satisfy customer requirements and needs (either spelled out or unrecognized). In general, customers want more functionality and quality at reduced cost and with fewer harmful effects.

Generation of change combined with selection

Any technological system evolves by the realization of various ideas that result in system change or in the creation of a new system; a selection process is then applied to choose the best system for satisfying the requirements (if they represent an increase in the system’s ideality). The main selection factor is market response, which in turn provides the financing that is crucial to system development.[25]

Two types of selection – positive and negative – impact a system’s evolution:

·        Positive selection – works in healthy economic situations to favor systems capable of effectively capitalizing on available resources and that can be quickly spread throughout the industry or market

·        Negative selection – works during times of economic depression to favor systems capable of surviving with minimum resource-consumption and which are well protected from the negative impacts of the environment.

Evolution at the expense of resources

A system’s evolution proceeds via the consumption of resources existing in the system itself, its neighboring systems, and/or the system environment. Each evolutionary step generates new resources that can be used to further develop the given system as well as other systems. However, negative resources that can cause undesirable effects might also result from the evolutionary process.

Excessiveness of an existing system

The majority of existing technological systems have redundant resources, that is, they have more resources than are necessary to perform their intended function.

Co-evolution of different systems

Many technological systems are connected with one another; the strength of these connections increases with the process of evolution.

Co-evolution of systems belonging to different hierarchical levels

Systems belonging to different hierarchical levels (a system and its supersystem(s), or a system and its sub-systems) are tightly connected in their evolution and evolve with each other in a coordinated manner.

Short- versus long-term forecasting

A system’s short-term evolution (improvement) depends primarily on the resources inherent in the system. Long-term development, including next-generation systems, breakthroughs, etc., depends on the evolution of the overall technology and/or market rather than on the particulars and resources of the given system.

Limited number of ways to perform a function

A function can be realized in a limited number of distinguishable ways based on the utilization of known resources. New types of resources might arrive as a result of a discovery.

Evolutionary alternatives

There is more than one (though still limited in number) fairly equal directions by which a given system can evolve from its current position to the next one, based on the involvement of different types of resources. The “winner” is usually the one that starts first and attracts the majority of financial and human resources.

Standard ways to solve problems

Common ways to solve problems or improve a system, based on the Patterns of Evo­lution, exist. These ways can be revealed through an analysis of the history of invention, allowing innovation knowledge to be collected and transferred.

Mechanisms behind the realization of trends or patterns

Each trend or pattern is supported by certain mechanisms (cause-effect relationships) which determine how they are realized. The same trend/pattern can be provided by several different mechanisms acting either separately or together; one mechanism can support more than one trend/pattern.

The weight of trends and patterns

Each trend/pattern has a weight (or power) that is determined by the number of people involved and the strength of this involvement. This weight can change over time and as conditions change.

Interaction between trends/patterns

Actual evolution is a product of the interaction of numerous trends with different weights and directions (including opposing directions). This product doesn’t comply with the superposition principle but is a non-linear result of multiple factors.

Resistance to evolution

The realization of a trend/pattern produces system change that is not always welcomed. Moreover, system change creates various types of resistance. This might be a force toward maintaining the status-quo, a general response to any change. In other cases it might be an opposite trend. Given the above, the evolution of a particular system can be controlled by managing either the trend itself or the response to its enforcement.

Evolution as a specific ability of certain non-linear systems[26]

Practically all evolving systems are non-linear; their evolutionary history includes crisis zones in which their behavior is principally unpredictable and therefore often appears to violate cause-effect relationships. The evolution of a non-linear system is a combination of pre-determined and random events.

Inertia of trends/patterns of evolution

As a specific system evolves, if a certain trend, pattern or line has been realized, it is highly probable that this trend/pattern/line will continue to exert a strong influence for some time.

Change of system goals and functions over the evolutionary process

A system often emerges in a “foreign” market to perform a function and satisfy a need that can be articulated in the given evolutionary period. As the system develops, new features, possibilities and applications are invented and, as a result, the system creates its own market.

Formation of specialized lines of evolution

For a specific system or for systems of a certain type (for example, measurement and control systems, milling systems, software, etc.) a set of specialized lines of evolution can be developed that will reflect and take into consideration the main particulars of that system or system type.

General scenario of system evolution

Man-made systems follow certain steps as they evolve, including:

• Discovery of a new function and multiple attempts to realize it
• Screening of developed variants by the overall current level of technology
• Development of selected systems through further competition
• Hybridization of known variants
• Building a new generation of the system using known variants and new enabling technologies.[27]

Driving forces of technological evolution

Any TRIZ specialist practicing TRIZ forecasting or Directed Evolution for products and/or technologies would eventually realize that to make a reliable forecast for a particular subsystem (such as a car door or cleaning products) one must first understand where the higher-level system is headed (the automobile for the car door, the home for the cleaning products). Furthermore, the design of the car or home might be governed by certain environmental and/or social regulations. The reason for this is found in a derivative of the assumption co-evolution of systems belonging to different hierarchical levels, which states that requirements imposed by a higher-level system are always dominant and “force” the subordinate system (or sub-system) to evolve accordingly.[28] Indeed, technological evolution is not an isolated process but rather is an aspect of the more general evolution of society; moreover, the evolving world resembles a Russian nested doll (matreshka) with multiple evolution processes of different scale taking place both independently and interdependently. For our purposes, the following levels (from the top down) can be identified together with the main features, including certain fundamental specifics and patterns and trends.

 

Evolutionary Level	Main Trends/Patterns and Non-Linear Effects
1.      Universal	§         Growth of complexity and variety §         Acting feedback mechanisms §         Self-organization §         Emergence of systemic effects §         Evolution through the emergence and resolution of crises
2.      Biological evolution	§         Directed toward unlimited growth and expansion; growing utilization of various resources §         Biological “products” as a combination of the “product” itself and the “production plant” (reproductive system) §         Evolution toward an increasing degree of survival of organisms based on haphazard mutation (trial and error) and natural selection §         Combination of evolutionary and revolutionary processes (gradual improvement of existing species and emergence of new species) §         Co-evolution within the biosphere as a whole, specific biological systems (biogeocenoses, ecosystems) and evolutionary “duos” such as prey and predator
3.      Evolution of human civilization as a whole	§         Gradual increase in the quality of life (personal ideality[29]) for an average individual in the society §         Increase in the role of technology and overall human intelligence §         Constant “tag war” between two opposing trends – integration and disintegration – with the gradual increasing of integration in the society §         Emergence of evolutionary waves in human civilization (primitive, agricultural, industrial, informational)
4.      Evolution of man-made systems	§         Separation of production plants from products, greatly simplifying and accelerating the evolution of both §         Utilization of resources unfavorable to biological evolution (high pressure and temperature, powerful energy sources, dangerous substances, etc.) §         General growth in the ideality of man-made systems by an increase in benefits and a reduction in associated costs §         Replacement of human labor with machines in situations ill-suited for humans §         General increase in the “intelligence” of man-made systems, providing improved performance and human interface
5.      Micro-evolution steps – inventions and innovations	§         Enhancement of the trial-and-error method as an evolutionary tool for man-made systems, based on the utilization of analytical and psychological stimulation approaches §         Transition from trial-and-error with purposeful utilization of evolutionary patterns and other instruments that have been developed, based on theoretical models of evolution §         Transition from innovations created by extraordinary individuals to mass innovation via education and utilization of innovation methodology and tools, including computerized processes of managing innovation activity

It is important to understand that the trends and effects inherent to a higher level can work on lower levels as well.[30] It can therefore be suggested that the evolutionary trends/patterns of the higher level serve as evolutionary driving forces of the lower levels. This suggestion can explain why the Patterns of Technological Evolution are so strong. For example, the pattern increasing dynamism is strong because increased dynamism means more flexibility – an important performance feature that in turn provides more convenience for the user and thus an increase in personal ideality (a feature of the level higher than the ideality of technological systems).

Orientation according to the main user benefits can help create a certain structure for evolutionary patterns. These main user benefits could be listed as follows (in no particular order):

• System performance (i.e., providing a certain positive function)
• Cost
• Quality (reliability, absence or limited number of drawbacks and side effects)
• Safety/security
• Fun associated with the owning and/or utilization of the given system

It seems reasonable to suggest that these main requirements serve as a natural selection mechanism for all man-made systems.

See Appendix 1 for selected groups of the general patterns of evolution.

General aspects of the evolution of man-made systems

The rate of evolution depends on both driving forces (positive impact) and impeding forces (negative impact).

In general, the evolving human civilization is like a vehicle carrying us from our past to our future. At the same time, in an effort to achieve the best ride, we are continuously redesigning the vehicle, in particular:

• Increasing the engine power (driving forces)
• Removing various impediments that compromise higher speed (friction, air resistance, etc.), reliability and safety (impeding forces)
• Enhancing the vehicle’s control systems

Using the above analogy, this group of patterns describes the following general aspects of evolution:

• Driving forces of evolution
• Impeding forces and limitations
• Means and methods to control the evolution of man-made systems

Evolution of driving forces

General description

The most powerful driving force of our evolution is the chain reaction[31] of the development of human civilization that started about 100,000 ago. In the process of this development, various participating elements and sub-systems directly and/or indirectly influence the evolution of one another to result in an overall evolutionary acceleration. This chain reaction generates local driving forces responsible for the evolution of various specific man-made systems.

Interestingly, the recent “dot.com” boom that occurred in the area of computer and Internet technologies was not the first burst of activity.

An earlier “explosion” took place at the end of the 17^th century, when Europe began a rapid recovery after a devastating 30-year war. In England, Parliament ceased to be the main power, which opened the path for business development; in France, the financial genius Colbert built a system of governmental support for businesses. In 1697, Daniel Defoe, a successful businessman, writer, and one of the founders of the British Intelligent Service published An Essay on Projects in which he described in great detail (and with much criticism) the new passion of inventing and pursuing new and tricky ways to get rich. Although some projects targeted building a production plant to produce new goods, most of the projects were related to trades, speculations, changing laws and taxes. The burst of new projects spread all over Europe, with England and France leading the way. Surprisingly, many projects were successful, generating revenue and accelerating the overall business but often creating crises, business scandals, frauds, etc.

Another explosion took place in the U.S. during the second half of the 19^th century as the country recovered from the Civil War. Enormous business opportunities in the former Confederate states, the gold rush in California, and rapidly growing railroad transportation initiated avalanche-like business and industrial development associated with the burst of patents. Inventors were able to find investors and quickly implement their inventions, for example:

1869	The Hyatt brothers patent celluloid; production began in 1872.
1876	In February, Bell patented the telephone; the first working sample appeared in March; by August 800 units were in use. In 1877 the first central telephone station was created in New York…
1879	Edison began working on lighting; ten years later electric power stations, production of bulbs, fixtures, cables, etc. appeared
1884	Charles Parsons patented the steam turbine; in 1889 about 300 turbines were producing electrical power.
1884	Hiram Maxim designed his first machine gun. In 1887 it was accepted by British army. By the end of the century it was accepted worldwide.
1886	The first patent on aluminum production via electrolysis; in 1890, 40 tons of aluminum were produced; soon thereafter 450 tons were produced annually. The price of aluminum dropped by a factor of ten, stimulating wide implementation.
1888	Tesla and Ferraris discover the rotating magnetic field; in 1889 the mass production of a.c. motors began.
1892	Diesel files his first patent; in 1898 mass utilization of Diesel engines began.
1886	The first patents and automobiles of Daimler and Benz. By 1900, thousands of cars by numerous manufacturers existed in various countries.

Using the above examples we can summarize the typical reasons and conditions associated with a period of super-active evolution:

• Investors ready to invest are pressed by accumulating capital to put them to work
• Science is ready to support technology due to the accumulation of discoveries capable of launching numerous inventions.
• Technology is ready to provide the needed materials and processes, greatly increasing the feasibility of inventions.
• Industry is ready to quickly build production plants and equipment.
• The culture supports innovation (compared with countries having certain cultural and/or religious bans, government interference with businesses, etc.)[32]

Successful innovation is typically a result of the close cooperation of people and/or organizations, each of which play an important role[33]:

• Subject matter experts (an inventor, designer, researcher, etc.) provide a system that performs at a cost acceptable to the customer.
• Investor(s) finance the development and implementation of the invention
• Manager
• Sales and marketing personnel convince potential consumers to try the invention.
• Consumers support the invention by paying for it

Driving forces of evolution and the system’s life cycle

The forces that drive the evolution of a particular system change with the system’s life cycle, in particular:

Stage 0: Birth

• Personal motivation of certain individuals (enthusiasm, curiosity, ambitions, greed, creativity, etc.)
• Demand and/or pressure from a system at a higher level of hierarchy (super-system) that cannot further evolve without the particular function

Stage 1: Childhood

• Personal motivation of certain individuals – hope for success
• Motivation of the group(s) involved to sustain and grow
• Economic interests – the need to receive a return on investment; high potential of a large (although perhaps not yet existing) market
• Societal interests – satisfaction of a new and not yet widely recognized need
• Demand and/or pressure from a super-system

Stage 2: Rapid Growth

• Personal motivation of certain individuals – the quest for a career
• Group(s) interest – growth and expansion
• Economic interests –ensure high and sustainable profit, high potential of a large opening market, high ROI potential.
• Societal interests – satisfaction of a growing need
• Demand and/or pressure from a super- system

Stage 3: Maturity

• Personal motivation – the quest for a career
• Group(s) interests – growth and expansion of the bureaucratic part of the group
• Economic interests – ensure a sustainable and reasonable profit
• Societal interests – satisfaction of a stable need

Stage 4: Decline

• Personal motivation – attempt to survive an inevitable collapse
• Group(s) interests – self-preservation of the organization’s top group
• Economic interests – reducing or possibly compensating for losses
• Societal interests – preventing the costly crash of the system to avoid a chain of undesirable events or even a depression.

Stage 5: Life after death

• Personal and group interests – the quiet existence of the system, which has practically exhausted its resources but can still provide a modest profit
• Search for new applications and new markets to return to stage 2.

The main components of the driving forces are:

• Human needs
• Evolutionary challenges
• Evolutionary opportunities

Evolution of human needs

In the process of evolution, various needs stimulate the evolution of the means for satisfying these needs, which in turn originate more sophisticated needs, resulting in a reinforcing loop. In other words, a need can stimulate technology (the invention of the telephone was stimulated by the need for communication) and technology causes greater need (using microwave technology for home cooking).

The first significant research in the area of human needs was conducted by Abraham Maslow[34] in the early 1940s, followed by numerous marketing studies.

According to Maslow, the typical hierarchy of basic human needs can be described

Typically, the satisfaction of needs starts from a basic level (elimination of hunger, thirst, obtaining shelter) then moves to higher levels (a starving person has little regard for prestige or image).

Practically all industrial technologies (with the exception of military technologies) targeted the satisfaction of basic human needs through the use of industrial methods. However, as basic needs were satisfied it appeared that, in addition to providing certain functions and satisfying certain needs, the consumption of products and/or services can be associated with certain emotional feelings (positive or negative) that can increase or reduce satisfaction respectively.[35] This new factor (we can call it the Enjoyment Factor or E-factor) is capable of increasing the value of products/services and thus increasing personal ideality.[36]

While realization of the main functions of products and services is rather standard and can be provided by mass production methods, the E-factor is much more personal and thus less defined and, as a result, difficult to predict. At the same time, it is a very important factor for mass customization. Moreover, when products/services from different producers or providers are practically the same, the E-factor can become the critical issue for customer product selection.

Five selected lines of evolution related to the evolution of human needs are presented below.

Line: General evolution of basic human needs

According to Maslow, the needs of an individual evolve from pure physiological needs to safety, social, self-esteem and self-actualization needs. Satisfying a lower, more pre-potent need is a condition for seeking satisfaction of the needs at the next hierarchical level. Accordingly, human civilization is evolving toward the development of technological abilities and the accumulation of resources that allow its average members to move to the next level of basic need satisfaction, as follows:

1. Physiological needs, including:

–        Air, food and drink, physical activity, rest, sex, etc.

–        Clothes, healthy and comfortable shelter, etc.

–        Physical and psychological health

–        Need for new impressions, feelings, etc.

2. Existential (safety) needs, including:

–        Safety, freedom, ownership of one’s life (business); being the object of someone’s care.

–        Stability of life, confidence in the future, access to information, understanding of one’s surroundings.

–        Absence of cognitive dissonances (irresolvable conflicts, contradictions)

3. Social needs, including:

–        Strong relationships with family and friends; communication

–        Being a member of a certain group(s); participation in joint activities

–        Desire for power, recognition, conformism, taking responsibility

–        Caring for others and seeking care from others

4. Spiritual needs, including

–        Self-confidence, self-expression

–        Moral obligations

–        Striving for pleasure

–        Curiosity; desire for knowledge

–        Need for playing (role playing)

–        Need for risk and self-improvement

–        Need for novelty, change

5. Need to care and serve, including:

–        Caring for children and other dependents

–        Being of service to a certain social and/or religious group

–        Being of service to humanity

–        Being of service to science, culture, arts

–        Being of service to a certain cause

–        Taking care of pets, the environment, etc.

Line: Increasing role of spiritual needs

1. People have time free from work that can be used for thinking and entertainment.
2. Emergence of certain spiritual needs that help with survival (curiosity, imagination, intelligence that enables one to learn and understand the connections between events, etc.)
3. Haphazard appearance of people with higher-level of spiritual needs
4. Emergence of certain demand for spiritual “products”; disciples and followers of the most successful storytellers, prophets, competition between spiritual leaders for disciples and followers. Emergence of positive feedback promoting the growth of spiritual needs.
5. Emergence of an individual’s internal need for self-improvement and positive feedback for improvement.

Line: Expanding base for enjoyment (E-factor)

To have fun, an individual must be capable of emotion. As human civilization has evolved, people’s attitudes toward fun, and the ways in which it is achieved, have constantly changed, as follows:

1. Enjoyment from satisfying the most basic needs – food, sex, relaxation. For example, the taste or presentation of food was not important.
2. Once basic needs have been satisfied, people enjoy a variety and quality of life.
3. Increasing fun (to fight boredom and counteract a reduction in fun associated with habitation) through the introduction of non-essential changes such as fashion.
4. Fun for individual tastes, often artificial.
5. Introduction of fun elements into any human activity, including work, business, etc.

Line: Increasing the degree of work-fun conversion

In the process of social enhancement, the relationship between an individual and his/her work changes, as follows:

1. Work as a curse (as in the Bible)
2. Work as a shameful occupation (a noble should only hunt and war)
3. Work for living (natural resentment toward work)
4. Work as an honest obligation (the Protestant work ethic, which began with the establishment of capitalism and the industrial revolution).
5. Work as a path toward a career and to establish a better position in life.
6. Work as fun – free schedule, high level of satisfaction and enjoyment.

Note: At first, work and fun were connected only for people of certain professions (actors, artists, scientists, professors, etc.). Gradually, this category grew to include more engineers, entrepreneurs, business people, etc.). People started looking for jobs that bring maximal “return” in terms of fun as well as monetary rewards).

7. Enjoyment of work is transformed from an important criteria in choosing a job or profession to the main criterion. Emotional attitudes (including love) toward work grow, increasing the probability of success.

Line: Increasing the fun associated with product consumption

1. Introduction of a product capable of performing a particular useful function
2. Improving a product’s ability to perform a useful function
3. Introduction of auxiliary and/or additional functions that increase the product’s real value
4. Introducing functions related to enjoyment (fun), such as:

–        Fun directly associated with performance, for example, enjoyment of working on a computer equipped with a large screen, driving a car with a powerful motor, etc.).

–        Fun associated with auxiliary functions (for example, attractive packaging).

–        Fun from additional functions not associated with the main performance (enjoying a good audio system in one’s car).

5. Increasing amount of fun associated with products that utilize human senses and motives, in particular:

–        Vision – nice colors, beautiful forms

–        Hearing – pleasant sounds, reduction of annoying noise

–        Tactile – enjoyment of touching things

–        Olfactory – enjoying nice scents

–        Psychological and social positioning

6. Transformation of fun functions into the main criterion for product success
7. Product diversification on the basis of fun and the method by which it is created (such as products that perform the same main function but provide different types of fun).

Evolution of impeding forces and limitations

Impeding forces

Any fairly complex system resists change in one or another way. In social and man-made systems this resistance is primarily associated with the attitudes of people whose positions are somehow affected by imposed changes and the associated psychological inertia. At the same time, objective aspects of resistance also exist. In effect, when a system is transformed from one stable position (not necessarily a bad position) into to another, better position, the situation temporarily worsens before it improves (for example, it is inconvenient to live in a house during remodeling). The greater the change, the worse this effect can be.

Resistance generated by the temporary deterioration of a situation adds to the resistance caused by psychological inertia. Attempts to “push” the change only strengthen the resistance. After several cycles of pushing and repelling, the maximum resistance occurs – usually before the deterioration has stopped. Resistance then gradually decreases to zero (although the situation might still get worse) and the system becomes “attracted” to the new, better situation.

The scale of deterioration associated with the transition to a better state grows with the process of system improvement. A very poor system can make the transition with little temporary deterioration, while a well-developed system (which is typically very stable) can suffer dramatically over the short-term from overall positive change.

Limitations

The history of evolution offers numerous examples of systems that develop due to the removal of imposed limitations (technological, psychological, social, etc.). For example, contemporary navigation devices (GPS systems, for example) lifted the limitations associated with the special skills a sailboat captain must acquire in order to successfully convey a boat to its destination. The refined skills with which scientists in the late 19^th and early 20^th centuries conducted experiments with primitive, inaccurate equipment are no longer required, given the computerized and highly accurate tools available today. Clearly, at certain evolutionary steps man-made systems can be freed from natural limitations through the use of new resources, approaches and technologies. Another way to avoid limitations is to take advantage of the existence of alternative methods for achieving a particular a goal. The process of lifting limitations results in the following:

• Substantial simplification of the system and its operation
• Standardization of the system’s design, processes, technologies; transition to mass production methods.
• Increasing process efficiency
• Continuous system growth along its S-curve, avoiding the maturity stage

Another fundamental limitation to the evolution of man-made systems is the exhaustion of alternative ways to perform a function. As was stated earlier, the TRIZ assumption of evolutionary alternatives suggests that there is more than one way by which a given system can be evolved from its current position to the next one, based on the utilization of different types of resources. Certain long-standing areas of technology dealing with relatively simple systems produced in volumes, where a large number of specialists and competitive companies are involved, can be quite close to this type of exhaustion, which typically takes between 20 to 50 years. In younger, more complex systems we can expect that the next-generation transition will occur before all possible alternatives have been exhausted.

The most important limitations influencing system evolution are:

• Fundamental limitations for growth imposed by laws of nature (laws of energy conservation, the speed of light, the Heisenberg uncertainty principle, etc.)
• Exponential growth of certain parameters (such as the dramatic increase in the aerodynamic resistance of an airplane as it approaches the speed of sound).
• Systems that are radically different from their predecessors (such as systems with too many novelties or systems based on new ideas and/or discoveries), or which require new markets, perform new functions, etc. tend toward slow implementation until they become less novel.
• General technological limitations, in particular:

–        Increasing cost and life cycle of certain technological systems (airplanes, for example).

–        Increasing system complexity and infrastructure, causing unpredictable systemic effects.

–        Increasing cost and time required for testing new products

–        Achieving a certain level of customer satisfaction

–        The absence of systematic methods for problem solving and system improvement.

• Limitations imposed by the environment:

–        The presence of a natural environment that is not optimal for the majority of processes and systems.

–        Potential environmental damage due to technological progress.

• Limitations associated with other systems:

–        Systems that compete with one another in the same market

–        Systems that compete for the same resources

• Limitations associated with system parameters:

–        Functioning of the system

–        Operating principle

–        Components, processes, design

–        Energy sources

–        Scale effects that occur as the system expands

• Limitations associated with the end-users of a product:

–        Physiological limitations (force, reaction speed, ergonomic issues, etc.).

–        Psychological limitations (inertia, subconscious fear of new things, conscious resistance, etc.).

• Social limitations – certain general cultural aspects, societal groups and/or institutions (parties, religions, organizations) can induce passive or active resistance to progress in specific areas or even in general:

–        Unorganized resistance of a relatively large group

–        Organized resistance of certain groups and/or organizations

–        Legal regulations that hinder the implementation of innovations

–        Culture and education that do not encourage innovation

• Market limitations:

–        Possible market size and market share

–        Presence of competing systems on the market

–        Realistic size and time table associated with possible investments and expected return on investment (ROI).

Impeding forces and limitations and system life cycle

Impeding forces and limitations change as the system progresses through its life cycle. In particular:

Stage 0: Birth

• The absence of theoretical foundations, financing, knowledge about potential markets, high uncertainty and low predictability of results.
• Society doesn’t recognize the importance of the problem (or invention) and does not support system development

Stage 1: Childhood

• General psychological and social inertia
• Absence of an appropriate market sector
• High competition for a limited preliminary market sector
• Resistance from areas of activity in which people are threatened by new competition.
• Technical problems associated with insufficient theoretical foundations, technology availabilities and the absence of methods for systematic and effective problem solving.

Stage 2: Rapid Growth

• Limited speed of obtaining necessary resources, organizing production, training people, etc.
• Limited speed in market growth
• Fierce competition for market share and investments
• Technical problems associated with increased scale, undesired long-term effects, etc.
• Resistance from certain social groups (religious, ecological, extremists, etc.)

Stage 3: Maturity

• Exhaustion of the resource base
• Exhaustion of market space; rigid and stable market share distribution
• Reaching certain fundamental limits imposed by nature or otherwise
• Continued resistance from certain social groups (religious, ecological, extremists, etc.)

Stage 4: Decline

• Market shrinks when a new system supplants a mature one
• The new system draws off resources, especially the best managers and specialists, which accelerates the old system’s decline (“brain drain”).
• Diminishing reputation of the old system, which compromises consumer and investor trust in the future (“capital drain”).

Stage 5: Life after death

• Limited demand and resources
• Loss of trust

Main components of psychological resistance

Psychological inertia was formed as a survival mechanism, deterring humans from new and possibly dangerous activities. Different cultures have different degrees of acceptance of new things; typically, older cultures have less tolerance for change. Despite the fact that in recent decades innovation has grown and produced more useful and pleasant changes than negative ones, long-term, deeply rooted fears remain. The main components of psychological inertia are:

• System of psychological protection (introduced by Freud). If an individual is afraid that a new idea might be dangerous or cause conflict with colleagues or supervisors, the idea will be “blocked” by the subconscious.
• Protection of territory common to many species. People have similar instincts; moreover, they greatly expand the definition of territory to include their professional knowledge and experience, scientific and business interests, etc. This factor causes the “not invented here” syndrome, rejection of ideas suggested by others, etc.
• Perceptions established in childhood by strong propaganda and/or strong authorities often become undisputable doctrines. Any threat (real or imagined) to these doctrines produces a strong negative (and often subconscious) reaction to the suspicious ideas and their carriers.
• Fear of logical inconsistencies and contradictions thwart the reception of new ideas that look especially weak or strange.
• Negative feelings based on the intuitive belief that new ideas are dangerous and prone to failure.
• Asymmetrical reaction of gain and loss. People hate to lose what they already have; the addition of certain useful features often cannot compensate for the frustration caused by the loss of features to which customers have grown accustomed.
• Use of logical proofs to justify subconscious psychological resistance.

 

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