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What are the contrasting mental models?

Meg Wheatley in her classic book Leadership and the New Science believes that the correct scientific metaphor for management should be taken from Quantum rather than Newtonian physics. One of the key differences is a focus on holism rather than parts. Systems are understood as whole systems, and attention is given to relationships within those systems (the root meaning of the word ‘system’ derives from the Greek synhistanai (‘to place together’). To understand things systemically literally means to put them in context, to establish the nature of their relationships. “When we view systems from this perspective,” notes Wheatley, “we enter an entirely new landscape of connections, of phenomena that cannot be reduced to simple cause and effect, or explained by studying parts as isolated contributors. We move to a land where it becomes critical to sense the constant workings of dynamic processes, and then to notice how these processes materialize as visible behaviours and forms.”

Contrasting mental models

If you accept the ‘complex system’ view of economies and organizations, then it is a short step to realizing that our mental models of how organizations work and managers manage need to change. Figure 5.0 illustrates how our organizational mental models directly influence our management mental models.

Mental models

Organization as an obedient machine

The organization-as-an-obedient-machine model takes leaders down the pathway of shareholder value maximization, short-term targets (and ‘fixing’ the results); central planning, coordination and control; economies of scale, and reactive change including the constant restructuring and reorganizing of the organization’s parts.

The core assumption is that everything is controllable if an organization can be broken down into its constituent parts and the right steering mechanisms and metrics used to ensure that each part achieves its optimum performance (each part is likely to have its own target and measures independent of others). If there is a problem with any part, a range of ‘tools’ can be used to ‘fix’ or ‘reengineer’ the problem.  But focusing on each separate part is likely to lead to dysfunctional behaviour as one unit tries to improve its performance at the expense of another (this is known as ‘sub-optimization’).

This machine-like model represents the current “management cockpit” view of leadership – a sort of twenty-first century computer game in which a few leaders at the centre control the actions of hundreds of front line managers by monitoring variances against a plan in ‘real-time’.  Flashing ‘traffic lights’ and ‘happy’ or ‘miserable’ faces appear on variance reports to tell remote leaders when action needs to be taken. In this model, measurement replaces management. The aim is to design judgment out of the system. Many leaders see this vision as the ultimate goal of technology – a sort of IT and accounting holy grail.

But there is deep cynicism about these approaches based on machine-like assumptions. It is increasingly tough (and expensive) to keep strategies, structures and systems in constant alignment in an unpredictable and changing world. Change is invariably reactive and disruptive and endless restructuring, reorganizing and reengineering programs come and go with, in most cases, temporary relief but little longer-term effect. Employees are small cogs in this giant organizational wheel of fortune. The result is that leaders consistently fail to connect with their people and thus miss the opportunity of harnessing a potentially huge store of ‘free’ knowledge and creativity.

Organization as an adaptive system

The alternative view is that organizations are adaptive systems and this mental model takes us down a different pathway. The goal is to adapt and endure; the focus is on fixing the whole system rather than its parts; teams are capable of self-organization and self-regulation; and change as a natural, adaptive process.

As Steve Morlidge explains, there is more than rhetoric to support this point of view. Systems theory tells us that the traditional, mechanical, model cannot be effective, except in a very stable environment.  Ross Ashby’s Law of Requisite Variety, formulated in the 1950’s, sets out the necessary relationship between the complexity of the environment, the flexibility of a control system and the specificity of the goals imposed on the system. The more complex the environment, and the ‘tighter’ the targets, the more flexibility the control system must have:  ‘only variety can absorb variety’. Failure to provide ‘requisite variety’ will result in instability (boom and bust) and ultimately system failure. The only way out is to ‘game the system’; artificially injecting flexibility into the system by other means (in other words, by cheating). Given a complex environment, this law tells us, the only way that complex organisations can be successfully controlled is through exploiting the capacity of a system for self organization and self regulation. In other words, we need to adopt an organic model.


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