April 2, 2012
One of the basic ideas of modern science is that the laws of the material universe can only be meaningfully understood by expressing quantified measurements. Numerical terms are needed, not just words and stories. The belief was that instead of ordinary sentences we must use mathematical equations.
The values of the measurements at a given starting time are called the initial conditions for that system. The Newtonian, deterministic claim is that for any given system, the same initial conditions will always produce an identical outcome. Life is like a film that can be run forwards or backwards in time.
One thing we have learned is that no real measurement is infinitely precise. All measurements necessarily include a degree of uncertainty. The uncertainty that is always present arises from the fact that all measuring devices can record measurements only with finite precision. To be able to reach infinite precision, the instrument we use should be able to display outputs with an infinite number of digits.
By using very accurate devices, the level of uncertainty can often be made acceptable for a particular purpose, but it can never be eliminated completely. It is important to note that the uncertainty in the outcome does not arise from randomness in the equations, but from the lack of infinite accuracy in the initial conditions.
It used to be assumed that it was theoretically possible to obtain nearly perfect predictions by getting more precise information. Better instruments would shrink the uncertainty in the initial conditions, leading to shrinking imprecision in predictions. The lack of infinite precision was thought to be a minor problem. Well, our belief systems are still mostly based on the idea that very small uncertainties don’t matter.
Possibly the first clear explanation of a very different kind of understanding was given in the late nineteenth century by the French mathematician Henri Poincaré. He was the founder of the modern dynamical systems theory. His claim was that there were systems that followed different laws: the tiniest imprecision in the initial conditions could grow in time. Two nearly indistinguishable sets of different initial conditions for the same system would then result in two developments that differed massively from one another. This is the reason why seemingly random behavior can emerge from deterministic systems with no external source of randomness.
Poincaré was way ahead of his time. His early thoughts gained evidence in 1963, when Edward Lorenz found, by accident, that even computer models of the weather were subject to very sensitive dependence on initial conditions.
Numbers fool us and quantified measurements are very rarely the whole picture. Stories matter more than we think.
December 10, 2011
In our view of the world, we often think that competition creates and secures efficiency. But it may be that high performance is incorrectly attributed to competition and is more a result of diversity, self-organizing communication and non-competitive processes of cooperation. Competitive processes lead to a handicapping of the higher-level system that these processes are part of. This is because competitive selection leads to exclusion: something is left out. Leaving something out means a reduction of diversity. The resulting less diverse system is efficient in the very short term, but always at the expense of longer-term agility and viability.
Our assumption has also been that by understanding the parts of a system in detail, we understand the whole. This is simply not possible! What happens in the interaction between the parts is much more important than the parts. The whole is the emergent pattern of the interaction, not the sum of the parts. The focus of the high performance organization should be on communicative interaction: what is going on?
Enriching interaction and interactive energy
Chaos theory explains how the patterns form. A parameter might be the flow of information in the system. At low rates, meaning no input or more of the same input, the system moves forward displaying a repetitive, stuck behavior. At higher rates and more diversity the pattern changes. At very high rates the system displays a totally random behavior. The pattern is highly unstable. However, there is a level between repetition/stability and randomness/instability. This level where simultaneous coherence and novelty are experienced is called the edge of chaos.
Classical physics took individual entities and their movement (trajectories) as the unit of analysis in the same way we have lately analyzed individuals and firms. Henri Poincaré was the first scientist to find that there are two distinct kinds of energy. The first was the kinetic energy in the movement of the particle itself. The second was the energy arising from the interaction between particles. When this second energy is not there, the system is in a state of non-dynamism. When there is interactive energy, the system is dynamic and capable of novelty and renewal.
Interactive energy may be the single most important factor in business performance.
Every interaction is meaningful
Interaction creates resonance between the particles. Resonance is the result of coupling the frequencies of particles leading to an increase in the amplitude of motion. Resonance makes it impossible to identify individual movement in interactive environments because the individual’s trajectory depends more on the resonance with others than on the kinetic energy contained by the individual itself. We are the result of our interaction.
The lesson is that every interaction of all of the particles is thus potentially meaningful and can lead to the amplification of the slightest variation. Interactive systems with even the smallest variations take on a life of their own. The future form and direction of the system is not visible in the system at any given time. The future is not in the system and it cannot be chosen or planned by anyone.
The conclusions are important for us:
Firstly, novelty always emerges in a radically unpredictable way. The smallest overlooked variable or the tiniest change can escalate by non-linear iterations into a major transformative change in the later life of the system.
Secondly, the patterns of healthy behaviour are not caused by competitive selection or independent choices made by independent agents. Instead, what is happening happens in interaction, not by chance or by choice, but as a result of the competitive/collaborative interaction itself.
The new social technologies have the potential to change the patterns of connectivity as much as the sciences of complexity have changed our perspective and thinking.
Richer, more challenging, more exploratory conversations leave people feeling more alive, more inspired and capable of far more creative action. The focus of the high performance organization should be on communicative interaction creating the continuously developing pattern – a life at the edge of chaos.
Thank you Pekka Himanen and Doug Griffin
October 31, 2011
The approaches of industrial management have given us remarkable material well-being over the last few centuries, but are increasingly being criticized for not being suited to handling the needs of today. Organizations need to excel in innovation. Companies also need to embrace rapid change and uncertainty. Some of the most creative ones have even gone so far as to take a “let’s just do cool things and see what happens” approach, trying to avoid traditional governance systems. Is this yet another sign that management is in crisis?
The industrial theory of management is based on top managers choosing the future of their organization and guiding its development in the right direction. The belief is that managers can make useful forecasts and set goals. Their daily responsibility is to monitor activities to identify gaps between the goals and actual outcomes so that the gaps can be closed. Uncertainty plays a minor role. Managers know what is going on.
Every business is a set of assumptions that are taken as given, thus reducing the perceived uncertainty. The whole plan–execute cycle is a process designed to prove those assumptions correct. But assumptions are never totally right most often not totally wrong, either. Accordingly, it is quite seldom that ideas are turned into a successful business in just the way described in the business plan. Things change.
In conditions of rapid change and uncertainty, there have to be systematic processes indicating progress and new opportunities as they emerge. This is much more important than forecasting or planning. It is about testing the assumptions continuously and signalling which assumptions are helpful and which are not. It is about finding out repeatedly which of the efforts are creating value and which are wasteful. Are we on the right track? Are we progressing? What new possibilities have become visible?
Lean thinking defines value as providing benefit to the customer. Anything else is waste. But what if we really don’t know? Then the most important business process is to find out. We have to learn what creates value for different customers in different situations. “Anything that does not contribute to learning is waste” as Eric Ries puts it. The business challenge for a creative company is to learn fast and cheaply!
Management theory needs to leave behind the industrial, mechanistic model of reality and the belief in linear if-then, causality. The sciences of complexity, non-linear dynamics, uncertainty and creative learning are the foundations of modern, human-centric management.
The task of managers is not the reduction of uncertainty but to develop the capacity to operate creatively within it. Ilya Prigogine wrote in his book “The End of Certainty” that the future is not given, but under perpetual construction:
“Life is about unpredictable novelty where the possible is always richer than the real.”
Thank you Eric Ries, Stu Kauffman and Ralph Stacey