Let’s all have a good argumentPosted: December 3, 2013
Notes on the practice of innovation and technology commercialization
“I suspect that the fate of all complex adapting systems in the biosphere – from single cells to economies – is to evolve to a natural state between order and chaos, a grand compromise between structure and surprise.” Stuart Kauffman, At Home in the Universe: The Search for the Laws of Self Organization and Complexity (1995).
In this blog we continue, from the last blog Fury and Adrenaline https://innovationrainforest.com/2013/11/20/fury-and-adrenaline/ looking into the basic analytical infrastructure which underpins commercialization activities and the development of supportive ecosystems – with an emphasis on what is known about complex systems. I believe that more rigor leads to better explanation and prediction (the mark of a good theory is that it must not just explain but also predict) and thence to improved application by practitioners.
It was a warm cloudless summer morning in Central Asia as the glum looking group slid slowly but resolutely into the conference room to be appraised of new government initiatives to support R&D and technology commercialization. Several in the front rows sat, arms severely folded, questioning – sans words – the veracity of my colleague and I, and, by extension, that of the government’s sincerity.
A “presentation” was clearly not going to impress. Let’s have a debate instead I thought – with not entirely flawless logic – had not Frederick Engels, co-revolutionary with Karl Marx whose philosophy had once dominated this land, believed in the negation of the negation to deliver the future? A noisy dispute followed between audience and presenter (me, intervening only when the volume exceeded a decibel level sufficient to attract those in adjoining offices) and among audience members. One scientist became especially upset but was restrained by his colleagues from walking out in high dudgeon.
However, in the course of the bruising arguments which followed something exciting emerged out of the session’s flotsam; new thinking and agreements among the previously hostile audience which had taken the opportunity to vent against the government and their foreign consultants, and then moved on to a constructive deliberation.
The last blog introduced the idea of dis-equilibrium state (also called a far from equilibrium state); one in which it is definitely not business-as-usual and events are occurring which push a system into a highly dynamic and unstable state. Quite an accurate description of the Central Asian event.
Complexity science shows that when systems are in a dis-equilibrium state, small actions and events, “perturbations” in the system, can be amplified through a positive feedback cycle of self-reinforcement. This effect has been predicted and observed in evolutionary biology and also in studies of leadership in groups of people.
To show the theory behind all this we need to introduce the concept of a phase space (also called a state space). The term was originally use for substances which can exist in several phases or states. For example, water can exist in solid (ice), liquid, or vapor (steam) phases. The formal definition is “a multidimensional space in which each axis corresponds to one of the coordinates required to specify the state of a physical system, all the coordinates being thus represented so that a point in the space corresponds to a state of the system.” Note that, but don’t be too alarmed, we are using “space” as a mathematical term not as in everyday usage.
As an example, when you are riding your bicycle the physical space you inhabit is the familiar 3-dimensional space. However, your phase space is a 2-dimension one whose axes are position and velocity (remember velocity = speed and direction, such as 5 miles/hour due north). In economic systems, the phase space variables could the inflation rate, the interest rate, the national debt, and the unemployment rate, for example.
The Rainforest Canvas, created by T2VC, is a set of questions to help map an innovation ecosystem in a region by looking at factors such as: Leaders, Stakeholders, Frameworks, Resources, Activities, Engagement, Role Models, Infrastructure, Culture, and Communications. (The Rainforest: The Secret to Building the Next Silicon Valley http://www.therainforestbook.com/ ). In the Rainforest view of the world the system variables are these headings in the Rainforest Canvas. Parameters or constraints are the sub-questions under each heading. Changes in these parameters move the ecosystem to a new point in its phase space. As we can imagine, but cannot draw, a phase space diagram with these 10 variables let’s just consider three ecosystem variables a, b, and c, represented along the horizontal and vertical axes in the three dimensional phase space diagram (below).
Path 1 represents for example a big jump to a new business model, or a new set of resources, or possibly some disruptive innovation, whereas Path 2 represents continuous transformation: maybe a gradual culture change, or breaking down a problem or opportunity into manageable pieces and sequentially tackling each one. Diagram adapted from J. Goldstein et al. A Complexity Science Model of Social Innovation in Social Enterprise. Journal of Social Entrepreneurship, Vol 1, Mo 1, p.109, March 2010.
We will further build on this diagram in future blogs.
Once a complex system, of individuals in this case, is pushed to a far from equilibrium state, the more its leaders and members surface conflict and create controversy, the more likely that the system will generate novel opportunities and solutions. The more that leaders and members encourage rich interactions, the more likely that amplifying actions will be present in the system.
On the subject of leadership, my polyhistor colleague, Henry Doss, has written in his Forbes blog about organization’s which mistakenly focus on training leaders to lead people, rather than training leaders to build and lead systems: Why Your Innovation Leadership Training Will Fail http://www.forbes.com/sites/henrydoss/2013/06/06/why-your-innovation-leadership-training-will-fail/ Henry introduced The Innovation Syllogism:
Innovation is a product of culture (not individuals).
Culture is an emergent factor of systems (not individuals).
Therefore, systems drive innovation (not individuals).
“If the logic and assumptions of this syllogism hold, then you may find that the most critical aspect of building an innovative organization – systems – is absent from your training and development planning.” We will discuss emergence as a phenomenon in complex adaptive systems in a future blog.
Oh yes, what happened in the Central Asian meeting? Standing applause at the end, and the person who seemed most pleased with what emerged – you guessed it – was the scientist who had been the most voluble!