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.

More on the topic: The End of Certainty: Time, Chaos, and the New Laws of Nature by Iliya Prigogine. 1998. Chaos: Making a New Science by James Gleick. 1987

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The mainstream ways of thinking about management are based on the sciences of certainty. The whole system of strategic choice, goal setting and choosing actions to reach the given goals in a controlled way depends on predictability. The problem is that this familiar causal foundation cannot explain the reality we face. Almost daily, we experience the inability of people to choose what happens in their organizations – or in their countries. We live in a complex world. Things may appear orderly over time, but are inherently unpredictable.

Complexity refers to a pattern, a movement in time that is at the same time predictable and unpredictable, knowable and unknowable. Healthy, ordinary, everyday life is always complex, no matter what the situation is. There is absolutely no linearity in the world of human beings.

Human patterns that lose this complexity become repetitive and rapidly inappropriate for dealing with life. Unlike mechanical systems, human systems thrive on variety and diversity. An exact replication of behavior in nature would be disastrous and seen as neurotic in social life. For example, a failing heart is typically characterized by increasing loss of complexity.

A pattern is something that emerges through the complex interactions between elements in a system. Although there is apparent order, there is never exact repetition if the system is viable. This is why human interaction cannot be understood as processes in the way they were used in manufacturing, but as patterns.

Patterns that are more repetitive are normally called routines or habits. This conclusion is important for us. Novelty emerges in a radically unpredictable way. Creativity is seldom the end result of a repetitive process.

The Internet changes the patterns of connectivity, transforms our understanding what “local” is, and makes possible wide participation and new enriching variety in interaction. By relying on the interactions of millions of people instead of a few experts/managers to classify content on the net, Google democratized scientific citation indexing. To be able to manage the increasingly complex organizations of today, the same kind of democratization needs to take place in the corporate world. Companies are transforming themselves from industrial mass production to creating value in networks of mass communication.

Transparency of tasks is the corporate equivalent of publishing academic articles. Responsive linking, rather than predictive linking such as in corporate hierarchies and process charts, acts as a measure of relevance, control and value. This has served the academic community well. It made Sergey Brin and Larry Page billionaires. Now is the time to do the same in the corporate world.

The Google lesson for management is, that the more work is based on responsive, democratic processes of relating and the more organizing is an ongoing process of communicative linking, the more value we can create!

It is now time for the sciences of uncertainty.

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The claim is that the best way to understand complicated systems is to investigate the workings of each of the parts. If a car does not start, the mechanic looks for the problem and finds a dead battery. In a similar way a doctor finds a wounded muscle. The idea is that the best way to understand life is to investigate the workings of the parts separately from those of other parts.

In the economic world, the concept of markets is based on the same idea: autonomous sellers and buyers engage in discrete transactions where each agent is independent from the other agents and each transaction is separate from other transactions. The unit of analysis is the individual agent.

Network scientists have recently made very different claims. They say that all human systems are connected and that connected systems cannot be understood in terms of isolated parts. The study of isolated parts offers little help in understanding how the parts work in combination and what emerges as the result of network connections. The notion of emergence is central. Their aim is to discover emergent patterns: is it really so that individual greed turns into a pattern that can be called public good, as proponents of free markets have suggested following the rhetoric of Adam Smith?

The suggested unit of analysis is now communication and emergence, not entities.

This changes many of the beliefs we have taken for granted. The first change deals with the assumption of a knowing individual, the basic idea of Cartesian philosophy. The individual was understood as having a knowing mind. Individuals were thus treated as if they possessed properties such as expert knowledge. On the bases of her personal properties the knowing individual is then understood as the designer and controller of an internal and external world.

The perspective of network science views knowledge as socially created and socially re-created not as stuff of the mind that can be shared and stored by individuals.  Knowing is a process of relating. From the network-based, relational perspective knowing is viewed as an ongoing and, never-ending process of making meaning in communication.

Management literature typically emphasizes individuals and locates explanatory power in their personal properties. Leaders are the sources of motivation, control and direction. The manager’s perspective is taken for granted as setting the limits of action and what is thought of as right or wrong.

Management theory is based on the same Cartesian assumptions of the self as subject, the other as object and relationships as influence and manipulation. This is why the present management thinking severely restricts what is thinkable and doable in the world of networks.

The potential of social media cannot be realized without a very different epistemological grounding, a relational perspective. Independently existing people and things then become viewed as co-constructed in coordinated networked action. Accordingly, the role of management is different, opening up new possibilities: power in networks is about “power to” or “power with”, and not “power over”.

The emergent pattern changes when the local interactions change. Self-interest in the network economy looks different from self-interest in the market economy; individual success is likely to take place through enriching relationships and being part of networked interaction aiming to facilitate both the individual and the collective effort.

Cooperation is the new competition.

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Thank you Dian Marie Hosking for great conversations

More: Reid Hoffman interview.

The nature of the relationship between customers and firms has changed dramatically. For over a hundred years, companies have assumed that consumers are an undifferentiated mass. Lately, we have moved through different degrees of market segmentation. Today, we have reached a point where the latest interaction technologies are creating an entirely new dynamic between the firm and the people we used to call consumers. Tomorrow firms will compete in making unique customer experiences possible.

The traditional approach was that the firm created value and then exchanged it with its customers. This firm-centric view of value creation is now being replaced by customers’ contextual experiences and co-created value. Value is created in interaction, but outside the corporate firewall. Even if a company is dealing with a very, very large number of customers, the firm must focus on one customer at a time.

We are in a world in which value is determined by co-created experiences – all a bit alike but all a bit different.

During the still (mentally) prevailing industrial era, most firms were vertically integrated. It was only around twenty-something years ago that firms started to source components from outside, from suppliers on a large scale. Today it is natural to rely on global supply chains. This is because the business goal is to access the most competent, knowledgeable sources and paradoxically, at the same time the lowest-cost producers. Access to resources and resource allocation is today by default multi-vendor, crowdsourced and global.

The changing relationships with customers and vendors are the main drivers behind the new ecosystems for communication and participation.

These trends also explain the situation we are in at the moment. The network is the architecture of work. People need to communicate and participate in order to invite contributions and to co-create unique experiences. It is about the relational view. It is not necessary to own the contributing parties. Capacity to connect and cooperate is what is needed. Cooperation is the new competition.

The world we live in today is in many ways the polar opposite of what we have been used to. The management challenge in the era of social media is to invite and combine the contributions of many in order to participate with one (at a time).

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Thank you C K

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

Higher performance patterns may occur through the very simple combination of different experiences and enriching interaction.

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.

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Thank you Pekka Himanen and Doug Griffin

Cathy N. Davidson has studied the way we make sense and think. Her claim is that we often end with problems when we tackle important issues together. This happens “not because the other side is wrong but because both sides are right in what they see, but neither can see what the other does”. In normal daily conditions, it may be that we don’t even know that other perspectives other than our own exist. We believe we see the whole picture from our point of view and have all the facts. Focus however means selection and selection means blind spots leading to (attention) blindness. We have a partial view that we take as the full picture.

This is one of the reasons why people in companies are often stuck in narrow, repetitive and negative patterns that provide them with numbing, repressive and even neurotic experiences.

The opportunity provided by social tools lies in the widening and deepening of communication, leading to new voices taking part and new conversations that cross organizational units and stale process charts.

According to Cathy Davidson, attention blindness is the fundamental structuring principle of the brain. Attention blindness is also the fundamental structuring principle of our organizations and our political system. We see and understand things selectively.

Knowing in the brain is a set of neural connections that correspond to our patterns of communication. The challenge is to see the filters and linkages as communication patterns that either keep us stuck or open up new possibilities.

The opportunity lies in the fact that as we don’t all select the same things, we don’t all miss the same things. If we can pool our insights we can thrive in the complex world we live in. In this way of thinking, we leave behind the notion of the self-governing, independent individual for a different notion, of interdependent people whose identities are established in interaction with each other.

From this perspective, individual change cannot be separated from changes in the groups to which an individual belongs. And changes in the groups don’t take place without the individuals changing.

Our attention is a result of the filters we use. These filters can be a mix of habits, company processes, organizational charts or tools. Increasingly these filters are social. They are the people we recognize as experts. Our most valuable guides to useful bits of insight are trusted people whose activities we can follow in real time to help us enrich our views.

Management research has focused on the leadership attributes of an individual. Leading and following in the traditional corporate sense have seen the leader making people follow him through motivation and rewards. The leader also decided who the followers should be.

Leading and following when seen as a relationship, not as attributes of individuals, have a very different dynamic. Leading in this new sense is not position-based, but recognition-based. People, the followers, also decide. The leader is someone people trust to be at the forefront in an area, which is temporally meaningful for them.

People recognize as the leader someone who inspires, energizes and empowers them.

Another huge difference from traditional management is that because of the diversity of contexts people link to, there can never be just one boss. Thus, an individual always has many “leaders” that she follows. You might even claim that from the point of view taken here, it is highly problematic if a person only has one leader. It would mean attention blindness as a default state.

We are now at the very beginning of understanding leadership in the new contextual, temporal framework. The relational processes of leading and following should be seen as temporary, responsive activity streams, not only on the Internet but also inside companies. They are manifested as internal (Twitter) feeds, (Facebook) updates and blog posts from the people you associate with.

Richer, more challenging, more exploratory conversations leave people feeling more alive, more inspired and capable of far more creative and effective action.

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Thank you Cathy N. Davidson and Doug Griffin

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.”

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Thank you Eric Ries, Stu Kauffman and Ralph Stacey

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