Communication and control

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Previous sections of this paper have highlighted the difficulties of attempting to manage complex, open systems using methods which are derived from the control of closed, mechanical systems.  The branch of systems theory that is possibly the most developed attempt to apply whole systems thinking to business organisations is ‘cybernetics’, sometimes defined as ‘the science of effective management’.  Cybernetics is an inter-disciplinary approach that studies the flow of information within systems, particularly how feedback is used by systems as a means of self-regulation.  The same principles, or natural laws, are found as corresponding patterns in biological and engineering control systems - a more formal definition for cybernetics is the ‘science of communication and control in the animal and the machine’. 

Cybernetics redefines what we mean by control; how it is exercised and its limits.  In place of command-and-control methods, where managers attempt to constrain or limit the actions of lower-level systems, the control of complex systems is focused on obtaining a desired outcome.  Control becomes an indirect function which takes into account the whole system, including aspects such as leadership and direction, training, tools and techniques, and incentives for cooperation and performance.  The role of management is to create an environment that fosters desired outcomes and makes maximum use of lower-level regulators – it is less about specifying the precise means to an end and more about establishing and clarifying the end goal itself. 

The vast number of variables and interactions in a complex system means that its properties and behaviour can never be fully known or predicted with hard, objective certainty.  For this reason, managers rely on models or concepts which they have developed over time as simplified representations of real-world situations.  Management models may be tacit or explicit; they may be informal, guiding principles or formal rules.  Decision-making cannot outperform the quality of the model on which it is based - see inset - but without comparison against a better model, managers are unable to assess the adequacy of the models they possess.  Faced with a situation that is ultimately unknowable, system thinking methods emphasise the need for managers to develop and constantly improve models - discovering what works and acting on this knowledge.  In other words, control depends upon a constant cycle of experimentation and learning - refer opposite page.

Kofman’s model (1992), describes the learning process as an OADI cycle, which is described on the opposite page.  In Kolb’s four-stage learning cycle (1984), ‘concrete experiences' provide a basis for 'observations and reflections', which are assimilated and distilled into 'abstract concepts', leading to actions, which are then 'actively tested' creating new experiences.  John Boyd’s OODA Loop - Observe, Orient, Decide, Act - has been widely adopted in US business and military strategy; its message is that organisations which move through this cycle faster than their opponents will eventually win.  Each of these models has parallels with Deming’s PDCA cycle, but whilst the PDCA cycle is a tactical model designed for manufacturing operations, the others are designed to deal with strategic complexity.  Nevertheless, the key stage of the process in each model corresponds to Act, where data is synthesised into a model which informs the subsequent planning or decision-making stage.
 

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