LINKS360 – Knowledge

Knowledge is Power ... Knowledge is Influence

Understanding Knowledge


The whole systems approach illustrates the complexity of Collective Leadership below.

Whole Systems as a four faced cube

Systems surround us. They frustrate us, they get in the way of problem-solving and they can be highly unpredictable! This section provides a brief introduction to what whole systems are and the characteristics that they exhibit.

The study and practice of leadership, like so many other complex issues, lends itself well to its reliance on what some describe as ‘whole systems approaches’. This is a popular phrase in both the management and leadership literature today. We are going to look at this through the lenses of synergetic and cybernetic perspectives; it is more about looking through the mirror rather than at the mirror.

The notion of the learning organisation and the notion of double-loop learning rather than single-loop learning (Argyris and Schon, 1978) is a good approach in considering whole systems. An example of single-loop learning is when values, goals, plans and policies are operationalized rather than questioned. Double-loop learning is to take these organisational givens and scrutinizing them critically. Synergy concerns double-loop learning at the level of the ‘whole’ whereas cybernetics considers the interrelationships between the components of the whole but not focusing on one specific aspect or component. In this sense, it is a means to the end of double or even triple loop learning. Synergetics and cybernetics provide a framework through which complexity can be explored through a double/triple loop approach to organisational learning. These concepts will be explored in the following sections.

A characteristic of complexity is that it is unlikely that the issues or problems underpinning it are likely to be fully resolved. In this sense, it shares these characteristics with those of wicked problems, which we explore in a different section.

Whole Systems as a maze

The concept of precessional effect (PE), defined by Buckminster Fuller as the effect of bodies in motion on other bodies in motion and then applying the all-important why question holds some promise. PE is more commonly known in natural science. The easiest example to explain is Mother Earth, which is in regular orbit around the sun, tilted at an angle of 90 degrees. It has followed this orbit for many millions of years and we can thus predict with almost absolute certainty that it will continue to orbit the sun on this axis once every 365 days. Put this into a laboratory setting, and it will inevitably be proved beyond (almost) total doubt (and we could not wish to hazard a guess as to how many 9s appear after the decimal point of 99.).

Why almost?

Consider a rogue meteorite that is heading to planet Earth and enters our atmosphere at anything between 25k and 160k miles per hour. Dependent upon the size of a meteorite, once it hits the earth, our planet is very likely to be knocked off its axis with catastrophic results. Physical science protects us to a degree in that an early warning is much more likely than it was at the time of the dinosaurs! This cosmic intervention is an example of a precessional effect in the natural world. Small changes in the wider environment can have a significant and, in some cases, devastating effect in the longer term. It is here that we need to consider chaos theory

Whole Systems Wordcloud

Chaos/complexity theory originates in nature; nature is complex and the only thing that we can know with any certainty is its unpredictability! It is a theory that could only have emerged from the second half of the twentieth century, given the advances in computational opportunities at the very beginning of the digital age. Although highly complex as a theory in its own right, it can be simply described as a mathematical sub-discipline that studies complex systems. A good introduction is provided in ‘chaos theory for beginners: an introduction’.

Although chaotic, there are underlying patterns, repetitions, feedback loops and self-organisation that can be identified. Examples of problems that chaos theory has helped in understanding are the earth’s weather system, the behaviour of water boiling on a stove and the migratory patterns of birds. Chaos is everywhere. It surrounds us as human beings living on our planet and as leaders in facing adaptive challenges.

The concept of chaos theory and PE has real promise in understanding why leaders who create systems can also destroy them. Let us now consider this within the context of social science generally, and leadership more specifically. Fuller argued that PE is also a human response and, just as it would be easy to knock a spinning top of its axis by a slight touch of the finger, so it is easy for humans to knock social events off their axis.

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