Process innovation in Novozymes
correspondence between three levels of patterns, which provide the capacity to explore patterns on one level and apply those patterns on another level, 3) it requires a conception of the intended possibility. This is done by generating a conception of how a technology will function and then testing it, with the results feeding back through an iterative learning process leading to modification of the original design. Thus, scientific knowledge (of pattern) is not applied directly to produce technology, but indirectly to help test uncertain functional solutions, which have been produced by following technological traditions (Nightingale, 1998:703). Analysis and testing allows engineers to understand how changing the starting conditions affect the end result. This knowledge can then be built up and extrapolated to fine tune the technology to produce its intended behaviour.
In combination, the three theoretical building blocks summarise the cognitive process of translating an unknown starting condition to a known, and essentially it explains how knowledge (codified or abstract) is applied to innovation. The cognitive model describes the process in which knowledge is applied to innovation in the protease department. The primary task arising is then to reach the optimal starting condition through in-depth comprehension of the situation at hand.
The process innovation is intrinsically uncertain because uncertain patterns of behaviour are being extrapolated into the unknown. From ‘post it!’ notes to oil platforms, engineers can only know ‘for sure’ about failure after the technology is developed. They must therefore rely on getting as good an understanding as possible to optimise the starting condition for the innovation process. The better this starting condition is composed, the closer the innovation process arrives at the desired end result. It is a process of answering the question ‘what causes the end result’ and therefore a mixture of recognising the problem as similar to a previous situation, and experimenting to establish that similarity. The result of which resolves the problem to a more specific level. Achieving the necessary understanding to optimise the starting condition depends on the level of codification and abstraction, and the speed at which the starting condition is resolved depends on the ability to economise on data processing. Despite we see the information theory (Boisot, 1995, 1998) and the cognitive model of innovation (Nightingale, 1998) as distinct cognitive processes, we wish to emphasise that important interrelation and interdependency between the two.
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