In chapter 4 I use this scale of certainty from conviction to doubt as one axis of a turbulence matrix that helps to visualise an organisation’s relative position by considering the degree of internal harmony and the degree of confidence management has in its understanding of external events.
Turbulence can also be characterised as degrees of unstable complexity. Think about it in terms of an equation. Our social and economic systems are extremely complex and an equation that models them, were it possible to do so without substantial simplification, would be large and enormously intricate with many variables. If only a few of these variables change rapidly and continuously the equation may not yield a stable solution and the output will appear turbulent.
Although we tend to regard turbulence as being an abnormal condition it is, in reality, the default state. It is order that is unnatural. If left unmanaged all organised things appear to revert to a state of disorder [1] and nothing known to the physical sciences arises spontaneously from disorder into some complex functional form.
However, biological and social systems seem different. They appear to evolve from simple beginnings into very complex structures. The paradox is that while the system as a whole appears to follow a path of self-organisation in the direction of increasing complexity, the substructures and individual units within them follow the path of change from order to disorder.
While unfolding of history may, from a distance, appear to be a persistent trend of progress towards greater complexity, closer examination reveals that it is punctuated by turbulent accelerations and reversals. States and empires emerge, grow, decline and collapse as do technologies, institutions and companies.
Stability is seemingly the special case state in which the decay of one component is balanced by the emergence of another. Turbulent change occurs only when the direction of change of a majority of components becomes similar.
Control through management activity is directed at both the system level, through government and regulatory intervention, and at the substructure level of individual constituent institutions. But there are times when the macro conditions are shaped in such a way that they compel many of the constituent institutions to adopt parallel trajectories that point to either boom or bust and lead to the unintended volatile change we experience as turbulence.
These forces are transmitted through the behaviour of people acting as social beings. But our natural state is not to live in such complex highly structured groups serviced by equally complicated contrived support systems. It is claimed by some that our ‘state of nature’ [2] is disordered, competitive, aggressive and bloody and that it is probably the change to living in small tribal groups that offered sufficient security and division of labour to ensure a life above that of subsistence. But the stability of these coalitions appears to become less reliable as their membership increases.
Today, in the developed economies, we regard even such subsistence conditions of life to be barbaric and, if we are forced to imagine what life would be like in such a world, we recoil with fear and horror. We have become used to the benefits that appear to be a dividend of our progressively more complex society.
But, like technology, our economic systems are artificial. The significant difference being that, unlike technology, they were not designed from first principles but are emergent, often in unpredictable ways, and periodically they evolve into a situation that proves to be unsustainable. A so-called bifurcation point.
It is never possible to retrace the path that led to this tipping point and return to the stability of the preceding period. The Greek philosopher Heraclitus [3] explained it succinctly by stating:
“You could not step twice into the same river; for other waters are ever flowing on to you.” [4]
Adjustments in our economic system occur naturally, albeit suddenly, as the established certainties dissolve to bring turmoil when the system flips from progress to regress. The rate of change within the system accelerates and the turbulence that arises when the system approaches its maximum operating level brings instability as regular control processes, on which we have come to rely, become less effective.
Faced with an uncomfortably rapid rate of change, management usually attempts to respond by speeding up their analysis and decision-making processes. But this can lead to information overload. To keep pace, as more data is demanded, the information gathered must be processed faster than existing systems, including our brains, have been designed to operate and therefore, as time is of the essence, analysis is undertaken either partially or badly or both.
The result is a slowing of the process of rational decision-making at the moment it needs to accelerate. To compensate estimate, guess and intuition may feature more dominantly leading to poor decisions taken under pressure and implemented without conviction.
Turbulence can arise in several ways. It may be felt generally or it may just affect a single company. Some of the more obvious causes of turbulence are:
(i) General economic turbulence resulting from the formation and dramatic ending of a bubble of inflated asset prices in one major segment of the economy.
(ii) A recession, when many sectors of a national economy or several linked economies regress simultaneously.
Some unexpected external event such as war, revolution, a terrorist attack, a natural disaster or a dramatic increase in the price of a strategic commodity such as oil.
Wars tend to create disorder for longer periods than terrorist attacks. The latter impose significant changes on behaviour but it is interesting how quickly the community adapts.
Similarly, natural disasters, such as the Asian Tsunami of 2004, have an immediate and massively negative impact that increases with proximity but, while creating great loss of life and physical damage, they tend not to lead to substantial structural changes at the macro level. The world that emerges from the rebuild is recognisable as similar to that which preceded the event.
The oil price shock of 1973 is a good case history of the turmoil that can follow the unexpected increase in the price of a key commodity. The world adjusted to the new cost level but the transition to a new point of stability was neither rapid nor comfortable.
Economic turbulence can be sector specific. But if the sector is substantial or significantly interconnected with the rest of the economy, as in the case of oil in 1973, then the turmoil can rapidly migrate as the shock waves radiate outwards.
Arguably the best example is the near collapse of the world banking system in 2008. Imprudent risk management by some financial institutions created an unstable bubble in the price of US real estate, which imploded leading to the virtual cessation of global interbank lending, the collapse of banks due to illiquidity and the stalling of capital flows on which the world economy relies.
Other causes of turbulence are organisation specific. Examples are product recalls (thalidomide), substantial class actions (the tobacco and asbestos industries are notable examples), enduring industrial disputes (Skychefs), plant closures or failures (Union Carbide at Bophal), and liquidity problems (Enron, Long-Term Capital Management).
A far as the general economy is concerned each of these cases represents a single, easily identifiable problem on which resources can be focussed. To simplify, for the economy as a whole it is an equation with one variable.
Organisations move through a lifespan (which I discuss at length in chapter 3). At certain points the nature of their business must change. For example, the phase of infancy characterised by lack of scale progresses to growth, during which the business expands at a rate that cannot be supported by the systems and assets employed previously. The change from infancy to growth is turbulent because it requires the rapid abandonment of the procedures on which the business has relied and the risky acquisition of systems that are unfamiliar in anticipation of a future scale that remains uncertain.