Innovation cycle

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Innovation cycle
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Innovation cycle is a pattern based on valuable novelty theory. It is composed of four stages. An Idea Phase in which diverse new possibilities are generated, an Action Phase in which new possibilities are explored, a Reality Phase in which the consequences of those actions are felt, and a Feedback Phase in which the lessons learned are captured, processed, and utilized. The cycle continues as feedback generated in the last phase is then a foundation for creating more possibilities. Innovation cycle is described also as being cyclical, iterative, attractive, self-reinforcing, effectual and probabilistic. ( Dennis A. Stauffer, 2015)

Phases

  • Idea Phase

In this phase new ideas are being generated. That may be both new product ideas or scientific hypothesis. People tend to value more these ideas that lead to success, yet not only those are created. There are ideas that lead to failure and are generated during this phase. Ideas are diversify. Without diversity it is possible that innovation would stall.

  • Action Phase

In this phase ideas are tested. Experiments have to be done in order reveal the consequences of that idea. It can also be simply having the courage and the resources to act on one's ideas. It is the only definitive way to determine whether an idea works or not. However, some ideas are ruled out without being tested.

  • Reality Phase

In this phase the consequences of ideas are felt. Ideas are subjected to reality, to larger environment. Being presented to a larger environment is what ultimately determines whether an idea will lead to a success or failure. This test is entirely pragmatic.

  • Feedback Phase

In this phase information generated in previous phases is captured, processed and utilized. Future generations benefit from trials and failures of previous generations. This trials result in accumulated tools, knowledge, insights and capabilities that we have developed within any discipline or endeavour and are commonly used.

Innovation cycle characteristics

  • Cyclical

Innovation cycle is sequential, but has no start or end point. It is possible to pick up the cycle in any given moment. The is always some prior state-of-the-art. The are always some beliefs or scientific theories already existing in any intellectual pursuit.

  • Iterative

The cycle is iterative as it repeats the same steps, however it acquires new inputs and produces new outputs. It is constantly adjusting and redirecting itself. While still preserving its underlying pattern, it adapts and evolves.

  • Attractive

Innovation cycle is attractive as living organisms and businesses are effectively drawn to it. It is advantageous. It gives opportunity to survive. Successful innovations adapt a business to its environment. They provide competitive advantage and are used to ensure its survival.

  • Self-reinforcing

The Innovation Cycle has an internal logic that propels it from one phase to the next. It is confirmed that there is a substantial correlation between phases. New ideas must be acted on in order to create any value, what later leads to real world consequences, which will result in feedback. Then final information generated in Feedback phase will impact future generations of ideas.

  • Effectual

This termed is coined by Dennis A. Stauffer. “The crucial determinant of whether a new possibility becomes an innovation is outcome…. So, rather than being driven solely by a series of causal factors, this pattern is effectally guided by outcomes”- Dennis A. Stauffer Innovation Cycle is somewhat insensitive to specific causal factors because it is not necessarily important from where a new possibility originates. It is highly sensitive to its effect. When it comes to innovation, outcome is absolutely crucial.

  • Probabilistic

Innovation cycle is probabilistic as its future course is not knowable in advance. It originates from determinant mechanisms but is becomes indeterminate as it iterated. It is prone to failure and there are multiple potential impacts, outcomes and solutions. Innovation cycle never guarantees any particular outcome.

References