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Kinerji Thinking

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OVERVIEW The Kinerji Method works on a number of levels (see the six other headings, below). This first one - i.e. 'Kinerji Thinking' - discusses one or two of the common reasoning processes that can hinder, or facilitate, an organisation's capacity for innovation. Like most of our methods it is inspired by Nature. We have found there to be useful similarities between human organisations and the way that living creatures cope with changes in their environment. In both cases, when disruptive events change a familiar landscape the organism's ability to flourish, or survive, may be compromised. When this happens, its ability to adapt becomes crucial. For an organisation, this means changing its habits which, in turn, probably includes questioning the assumptions and beliefs that are sustaining its behaviour. Over time, the competences and skills that once made it successful can become barriers to new ways of thinking. In addressing this problem, many commercial and public organisations have tended to hire in external 'creatives', who will offer new ways of working. However, even when an individual is exceptionally perceptive and creative, this is unlikely to work unless it is welcomed by shared understanding at many levels and a willingness to interpret the new ideas into terms that can be implemented by all concerned. Fortunately, everyone is creative, even if they have not been brought up to believe this. Kinerji offers a bespoke service designed to unlock the creativity that is latent within, and across, the whole organisation.

THE FIRST OF SEVEN INTRODUCTIONS TO KINERJI

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Logical Thinking 

Adapting to massive changes is not a trivial task because it calls for changes in behaviour. These, in turn, mean challenging assumptions and adopting different ways of thinking. Over the last few hundred years or so, industry has evolved analytical thinking skills for managing specific tasks and projects. Science played a key role in this process. For example, rational, evidence-based logic has enabled organisations to organise complex assets and processes in an increasingly efficient way. By accurately measuring, quantifying and recording data, it became possible to manage projects by imagining them as 'targets' and 'outcomes'. However, when there are too many innovations taking place on too many levels, this type of prediction becomes virtually impossible. This is because the logic of evidence-based reasoning assumes that the future situation can be compared, usefully, with the past. Unfortunately, we cannot extract 'evidence' from an unknown future the way we do from the familiar present. As Albert Einstein reminded us, solutions to big problems cannot be solved using the mind frame they came from.

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Up until the crash of Air France Flight 4590 in 2000, the Concorde SST had been considered among the world's safest planes. Suddenly, the Concorde's proud safety record dropped from 100% to near zero. Of course, after the event we can see it as predictable. Concorde was just another aeroplane and scientific data shows that any plane can crash. What this tells us is that predictability can become a dependable routine when everything stays the same. But, in an era when many innovations are taking place on many levels at the same time, certainty becomes rare. Whereas engineers can go back to the drawing board and improve their designs, human organisations are less bound by the relative simplicity of structures and aerodynamics.

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A possible reason why scientific reasoning has been so influential is that logic is easier to describe than emotions. It is more predictable, perhaps, because its ‘rules’ of engagement can be put into simple words that most of us can grasp, if not agree with. In pure logic the boundary between a right and a wrong answer is clear to all. This is because it was designed to do so. Questions must be simplified and answers have to match the form of the questions. Although this mode of thought is invaluable for certain tasks, it may not work in the more cluttered and shambolic world of human actions. Although we may try our best to follow rational thought patterns, humans are always biased by their prejudices, habits and emotions. Blaise Pascal, the 17th century mathematician famously noted that, "the heart has its reasons, of which reason is unaware". However, what Pascal meant by 'reasoning' (e.g. deductive and inductive thinking) has tended to find favour as a way to achieve order, because logic is more rule-based than emotions.

Adaptive Thinking

It is usual for organisations to organise themselves by identifying 'problems' and discussing them. This is a highly effective method, but it has certain limitations. Whenever we frame a situation as a 'problem' we are likely to focus our attention onto a compatible 'solution', rather than noticing its possible benefits. The Kinerji Method offers new ways to describe a given situation so that it reveals many unforeseen opportunities.

EXAMPLE When asked what he would do about air pollution (in this case, airborne particles of sulphur dioxide) the visionary engineer, Buckminster Fuller replied "The people who let the sulphur go into the air are not in the sulphur business".

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One of the barriers to creativity is the staunch belief that the world never changes. The artist, Alfred Jarry (1873–1907) founded the Pataphysical Society on the premise that exceptions were more important than 'norms', 'rules' and 'laws'. This seems to acknowledge the fact that the Universe is evolving all the time. For example, living creatures do not evolve according to a central set of policies or rules. Every now and then, Nature seizes upon a haphazard mistake and adopts it as a template for new ways of doing things. When this happens, those who are slow to adapt are at risk of becoming excluded from the game.

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Imagine a caterpillar creeping along a branch of a tree. One day it will change its shape and become a butterfly. But until it begins to change, does it have the capacity to imagine itself fluttering above the tree it is crawling upon? If so, does it use the same type of reasoning throughout the whole process of metamorphosis? I must admit that I do not have the knowledge to answer this question, although I believe it is an important one to ask. The same question could be put to those innovators and pioneers who caused huge disruptions in the market. What kind of reasoning did they apply to their task, and did things turn out as they planned? Indeed, do any of us have the capacity to plan for circumstances that are, at best, hazy and ill-defined? If, as I have suggested, pure logic is not the best form of reasoning to apply when radical, or complex, changes are under way, what would be a better way to think?

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Abductive Reasoning 

Although Conan Doyle's Sherlock Holmes mysteries are often cited as examples of deductive reasoning, this is inaccurate. For a start, thinking deductively does not require such imaginative creativity. Whereas it is a self-contained process with one right answer and many wrong ones, the thinking process that Sherlock Holmes used is anything but self-contained. It draws upon a wealth of seemingly disparate facts that he had somehow acquired before confronting the task. More importantly, it is likely that he sifted through many imaginative conjectures and possibilities before sharing his successful solutions with others. The more precise name for this non-deductive type of reasoning is ‘abductive reasoning’. Charles Peirce coined the term in 1877, a few years before Doyle created Holmes. Whereas a deductive reasoning problem asks what we might expect if we were to combine quantity 'A' with quantity 'B', abduction usually starts with a mystery (i.e. 'C') and requires us to work backwards. If we are surprised to find that 'C' is the case, what 'A' (perhaps in a context 'B') is likely to have caused it? This is where things get messy, because there could be many equally valid answers that might account for the mystery. Indeed, many 'real-world' problems are far from simple, especially where a particular answer raises new questions before it can be tested.

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Sometimes, organisations have to face problems that are even more difficult to solve than those described in a Sherlock Holmes tale. How can they re-shape themselves, or acquire novel ways of thinking, when their future is uncertain? Whereas an amateur sleuth might be able to remain aloof from the mystery he is trying to solve, organisations are fully immersed in the situation they want to change. Doyle casts his hero as a kind of rare genius, who has powers well beyond the rest of us. Although this is a very entertaining idea, it should not mislead us into believing the myth that creative thinking is a gift bestowed upon special individuals. everyone has some capacity to be creative....("elementary, my dear Watson"). The anthropologist, Gregory Bateson, has suggested that abductive reasoning is common. As he puts it: "all thought would be totally impossible in a universe in which abduction was not expectable......"

Combinatorial Creativity

So far, we have discussed a few types of 'reasoning', using Sherlock Holmes as an example of 'creative thought'. This exemplifies the popular myth of the creative genius as an individual who, singlehandedly comes up with singular ideas. But organisations need more than answers to difficult puzzles. Often, they must innovate in a way that delivers new products, services, or business models. Richard Cantillon coined the term 'entrepreneur', characterising him, or her, as an "intermediary between capital and labour" (Cunningham & Lischeron, 1991). Although it has changed its meaning over the last three hundred years, the word 'entrepreneur' literally means someone who 'takes from between'. It therefore implies the presence of several (at least 3) players or assets.

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In 1967, Arthur Koestler suggested that all creative thinking is a process of combination. Since then, studies of the living brain seem to confirm this idea. There is, therefore, an interesting parallel between ‘creative innovation’ and sexual reproduction. In both cases, two ‘parent’ factors combine to create a new outcome that differs from each.

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Koestler applies this combinatorial logic within an idea-generating technique that he calls ‘bisociation’. This is a creative method that starts with two, or more, apparently incompatible frames of thought. (By ‘frames’ he means "any ability, habit, or skill, any pattern of ordered behaviour governed by a 'code' of fixed rules"). By mentally forcing together things that are highly incompatible, the mind is tricked into making a creative leap that may be surprising, or comical. The fact that creativity is combinatorial means that it does not need to take place within one individual mind. Kinerji methods show that any two items of difference can be 'bisociated' to deliver an unexpected outcome, whether this happens within an individual, a one-to-one discussion, a team, or a large organisation. Whether in sexual reproduction, or in ‘creative innovation’, successful innovation may take time, because it depends on the appropriate alignment of a huge number of complex, usually hidden, or unknown, factors.

FURTHER READING

  • Arthur, B. (1996) ‘Increasing returns and the new world of business’, Harvard Business Review, July/August 1996, p. 100
  • Bateson, G. (1980). Mind and nature: A necessary unity. New York: Bantam Books.
  • Christensen, Clayton and Raynor, Michael (2003). The Innovator’s Solution: Creating and Sustaining Successful Growth. Boston: Harvard Business School Press.
  • Cox, G., & Dayan, Z., (2005), Cox Review of Creativity in Business: building on the UK’s strengths, TSO: Norwich, Chapter 1.
  • Cunningham, J. B., & Lischeron, J. (1991). Defining entrepreneurship. Journal of small business management, 29(1), 45-61
  • Fuller, R. B., (1975), “Synergetics: Explorations In The Geometry Of Thinking”, in collaboration with E.J. Applewhite. Introduction and contribution by Arthur L. Loeb. Macmillan Publishing Company, Inc., New York.
  • Kauffman, S., (1995), At Home in the Universe, the search for the laws of self-organization’, Oxford University Press Inc, New York
  • Koestler, A., (1967), The Ghost in the Machine, Penguin: London (reprint 1990).
  • Lakoff, G., & Johnson, M., (1980), Metaphors We Live By, University of Chicago: Chicago and London
  • Landry, C., (2000), The Creative City: A Toolkit for Urban Innovators, Earthscan Ltd, UK & USA, ISBN-10: 1853836133, ISBN-13: 978-1853836138
  • Lovelock, J. (1979), Gaia: A New Look at Life on Earth, Oxford University Press: Oxford.
  • Margulis, L. (1998) Symbiotic Planet: A New Look at Evolution, Basic Books: New York.
  • Maturana, H., & Varela, F., (1992), The Tree of Knowledge; biological roots of understanding, Shambhala, Boston
  • McGilchrist, I., (2009). “The Master and His Emissary: The Divided Brain and the Making of the Western World”. USA: Yale University Press. ISBN 030014878X
  • Meadows, D., (1999), ‘Leverage Points; places to intervene in a system’, The Sustainability Institute, Web version here, accessed 14 August, 2009.
  • Nieuwenhuijze, O, & Wood, J. (2006), ‘Synergy and Sympoiesis, in the Writing of Joint Papers’; anticipation with/in imagination, International Journal of Computing Anticipatory Systems, edited by Daniel M. Dubois, Centre for Hyperincursive Anticipation in Ordered Systems: Liège, Belgium, Volume 10, pp. 87-102.
  • Norman, D. (1988), The Psychology of Everyday Things, New York, Basic Books, pp. 87-92
  • Robinson, K. (2011). Out of our minds: Learning to be creative. John Wiley & Sons.
  • Romer, P., (1991), Increasing Returns and New Developments in the Theory of Growth, In Equilibrium Theory and Applications: Proceedings of the 6th International Symposium in Economic Theory and Econometrics, edited by William Barnett et al.
  • Seyfang, G., & Haxeltine, A. (2012). Growing grassroots innovations: exploring the role of community-based initiatives in governing sustainable energy transitions. Environment and Planning-Part C, 30(3), 381.
  • Sullivan, C., Gilmore, T. N., & Blum, R. (2010). The Power of "Small Leadership”. The 2010 Pfeiffer Annual: Leadership Development, Chichester: John Wiley & Sons, 220-231.
  • Surowiecki, J. (2005). The wisdom of crowds. Random House LLC
  • Thackara, J. (2005). In the bubble: designing in a complex world. MIT press.
  • Wood, J. (2007:1), Design for Micro-utopias; thinking beyond the possible, Ashgate: UK.
  • Wood, J. (2009), Auspicious Reasoning; can metadesign become a mode of governance? in the Journal of Postcolonial Studies, Volume 12, Issue 3 September (2009) pp. 315 – 327
  • Wood, J. (2011), ‘Languaging Change from Within; can we metadesign biodiversity?’ in Journal of Science and Innovation, Volume 1, Number 3, October 2011, pp. 27-32.
  • Wood, J., (2013:1), “Metadesigning Paradigm Change: an ecomimetic, language-centred approach”, a chapter in Handbook of Design for Sustainability, edited by Stuart Walker & Jacques Giroud (Berg), 2013, pp. 428-445
  • Yeang, K. (2013), Ecomimicry: ecological design by imitating ecosystems, Routledge, 2013

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