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Use the Eight Patterns of Evolution to Innovate

By Michael S. Slocum

Use the Theory of Inventive Problem Solving’s(TRIZ) eight evolutionary patterns to construct a technology road-map that profiles the life curves of key products and systems. We need the wisdom of maturity mapping and these patterns to accurately predict when a product or system will become profitable, and when we can expect profitability to erode. Moreover, we use the patterns of evolution to define the fuzzy edge of what we will be tomorrow compared with what we are today.

The Eight Patterns of Evolution

Pattern One: Evolution Toward Increased Ideality

The first of theevolutionary patterns is evolution toward increased ideality, which asserts that every system generates both useful effects and harmful effects. For example, the system known as a car usefully gets you from point A to point B, but it does so while harming the environment to some extent. Over time, the car has evolved in a way that has increased its useful effects while decreasing its harmful effects. Therefore, the goal for any system is to maximize the ratio of useful to harmful effects and approach ideality.

Pattern Two: Stages of Technology Evolution

Principle two is the stages of technology evolution, which is essentially an S-curve that forms the basis of the maturity mapping framework. A product or system is conceived in the mind and lingers there until it reaches a point of reality. Then an invention is made to meet some need, but the invention has numerous unsolved problems and contradictions.

After this, society recognizes the value of the new system and investment is made to overcome its problems and contradictions — its barriers to commercialization. This is when the S-curve turns sharply upward and profitability grows as lower level inventions and optimization efforts push the new wave of change to its limit. System development slows, small improvements are made and profitability either levels or starts to decrease.

Personal computers are a good example of this non-linear progression from system initiation to system commoditization or extinction. When PCs first became available, they were expensive and problematic, and it was difficult to make money making them. But then technology and demand converged, and the PC industry moved dramatically from early adoption to mass adoption.

Today, however, PC technology has reached a limit of profitability, marked by the wave of change brought on by the Internet. Yes, many more people still need PCs, and the Internet only drives PC sales, but the profitability associated with strictly making PCs is highly constrained, because the process has been optimized and commoditized.

Without innovation, mature systems are lucky to eke out a living, and this may be what Dell saw when it decided to change the way PCs are ordered, built, stocked, shipped and serviced. The strategic minds at Dell saw the S-curve of the PC and figured it was time to change the rules. So they built a new model within which to make, sell, and service desktop computers — thereby extending profitability around its commoditized products. (This move by Dell is a lower-level innovation, because the basic technology of the PC has not changed for quite some time. And other S-curves are in full force, such as the one that represents all the handheld computer devices, or the one that’s experimenting with embedding computing devices in watches, eyeglasses and clothing.)

Pattern Three: Non-Uniform Development of System Elements

The third of these inventive patterns is the non-uniform development of system elements, which purports that each system component has its own S-curve. Therefore, different components evolve by their different schedules, reaching their inherent limits at different times. In turn, this creates contradictions and/or constraints, as certain components can hold back the progress of the whole system.

A strategic TRIZ practitioner analyzes systems to discover constraining components. A tactical TRIZ practitioner then uses the contradiction resolution process to solve the constraint – behind every barrier to innovation is some physical or technical contradiction, or possibly a family of contradictions. If you can solve the contradiction, you can leapfrog beyond its associated limits.

Pattern Four: Evolution Toward Increased Dynamism and Controllability

Inventive pattern four is evolution toward increased dynamism and controllability, which means that as systems become more flexible over time, they also become easier to monitor. You see this in manufacturing, where the ability to interchange machinery and parts has been met with the ability to control processes capability. Another example is the increased dynamism you see between customers and providers, enabled by Internet-based transactions. Looking at your account online, trading stocks, buying books — all these increase relational dynamism while improving the control of that interaction.

If you lead a transactional business, you look underneath your specific product and service portfolio; you look at the tectonic patterns of evolution that are pushing your systems. Therefore, if the world is always moving toward increased dynamism and controllability, you want to tap into that movement. In a way this is the Tao of business: listening to the voice of evolution and letting it tell you what to do. This way, you’re flowing with the wind, not against it.

Pattern Five: Increased Complexity, Then Simplification

The fifth evolutionary pattern is increased complexity, then simplification, which is the tendency for systems to add functions that at first increase complexity but over time collapse into simpler systems that provide the same, or more, functionality. For example, cameras became more complex when such functions as focusing and flashes were added. But later, these functions were integrated and automated into systems that provided multi-functional capability.

When pizza parlors decided it was a good idea to deliver, functions were added, like taking orders, transcribing addresses and dispatching drivers. The system added complexity to provide greater functionality. When you call into a pizza place now, it likely has an automated system that recognizes your phone number, displays your address and identifies the types of pizza you’ve ordered lately. Increased complexity collapsed into greater simplicity and, again, the key is to predict when and how best to make this happen in an organization.

Pattern Six: Evolution with Matching and Mismatching Elements

Pattern number six is evolution with matching and mismatching elements, which says that evolving system elements are matched or mismatched to improve performance or compensate for undesired effects. It is the configuration of elements that sometimes holds the secret to how you can either extend the life-cycle of a system or cannibalize it with a new one.

Matching elements are those that have the same functional nature. A vacuum cleaner that utilizes suction might evolve from constant suction to pulsating suction to resonance pulsation and so on. Then, the act of suction in any of these forms might be augmented with a rotor brush – the spinning brush part of the power nozzle. The addition of the rotating brush is a matching-element evolution, because it adds a part that only enhances the one function of suction.

An example of evolution with mismatching elements is the suspension system of a vehicle or the way the wheels of a vehicle are attached to its body. The function of rolling and the function of passenger comfort exist in the same system, and they need to be connected in a way that enhances both as much as possible.

Pattern Seven: Evolution Toward the Micro-level and Increased Use of Fields

The seventh pattern, evolution toward the micro level and increased use of fields, which says that technological systems tend to transition from macro- to micro-systems, and that different types of energy fields are used to achieve better performance and control during this transition.

A computer used to be a huge system of mechanical card reading. The field used for computing shifted from mechanical to electrical and the machines got a lot smaller. The same is true of systems that transition from thermal energy to atomic energy. We instituted nuclear power as an alternative to thermally combusting coal and oil, and the space needed to perform the function got smaller.

Generally speaking, a system evolves toward increasingly smaller energy fields, beginning with the field of mechanical interaction and progressing all the way to the field of electromagnetic interactions, which are the smallest of all in size (the size difference between the hinges on your door, mechanical, and the radiation of an X-ray, electromagnetic. In between, you have the fields of thermal, molecular, chemical, electrical and magnetic. It is important to understand how these fields connect in the same system and how systems tend to evolve toward the most micro-cosmic level possible.

Pattern Eight: Evolution Toward Decreased Human Involvement

The final evolutionary pattern is evolution toward decreased human involvement. Washing machines, remote controls, power windows, cars and almost everything else in society follows this trend.

Interaction Among the Patterns

Because all eight evolutionary patterns are networked in nature, one can serve as a funnel for another, and vice versa, depending on the situation. For example, the patterns of matching and mismatching elements can help the innovator determine a general pathway of focus. The system might evolve in a way that connects functionally different but co-dependent elements (mismatches), rather than in a way that taps into the progression of matching elements.

From here, the pattern of increased complexity, then simplification could apply as the engineer designs a new system for evolving mismatching elements. At first, the innovative adaptation makes the mismatching system more complex, but later it becomes simpler. And maybe it also becomes smaller as the forces of evolution toward the micro-level and increased use of fields pattern dictate.

Although one evolutionary pattern may illuminate the path of innovation better than the others under certain circumstances, most technology development road-maps will embody more than one of the eight evolutionary patterns. A strategic thinker should not see technology development as a specific problem to be solved, but a specific expression of underlying patterns.

The pure TRIZ-inspired strategist looks at patterns and principles, almost like seeing in another dimension, to configure innovations that meet some underlying societal need. You do not want to know how to increase the bandwidth of your gaming system so it can meet the customer need of “more realistic gaming.” You want to know which patterns of evolution will characterize the next innovative incarnation of what it means to engage in gaming for human entertainment.


The task of the innovator is to supplement the classic paradigm of design with a deeper pool of intellectual capital. If the design engineer thinks in terms of customer-based requirements, parameters and variables, TRIZ provides direction for that thinking in terms of need-based constructs and innovations.

About the Author:

Michael S. Slocum, Ph.D., is the principal and chief executive officer of The Inventioneering Company. Contact Michael S. Slocum at michael (at) or visit