What is Complexity

Complexity is one of the most over used and yet misunderstood terms in business and strategy conversations. At its heart, complexity is concerned with the underlying cause and effect behind interactions between actors, events and entities; and whether this cause and effect can be determined. In the context of strategy, if cause and effect  can be determined, then accurate predictions about the result of certain strategic actions can be made, resulting in better execution success rates. But if it can’t be determined, then there is uncertainty about which strategic actions are necessary and which will actually work. Once strategic actions are chosen, there remains the real risk that the strategic actions chosen will turn out to be incorrect, leading to significant waste, opportunity cost, lost competitiveness and potential risk to the survival of the organisation. The technical definition of complexity comes from complexity science, which studies the fundamental nature of complex systems. It focuses on the effects of non-linearity, or non-linear dynamics, on the behavior of such systems. Non-linearity is the property that the magnitude of an effect or output is not linearly related to the cause or input; making advance cause and effect determination, and thus accurate predictions, very difficult or nearly impossible. 

The effects of Accurate and Inaccurate Predictions: The Global Financial Crisis

The 2007 Global Financial Crisis provides a good example of the opportunities and risks in accurate and inaccurate predictions. Most organisations did not truly or deeply understand the true cause and effect relationship behind the interactions between the actors, events, entities and subsystems of the global financial system. But, believing their understanding of the cause and effect was accurate, they proceeded to make predictions and assumptions based on the flawed belief that their business environment would be much the same as it had always been. They subsequently made strategic decisions and investment decisions based on their predictions. Their understanding of cause and effect, and thus their predictions, were grossly inaccurate. As a result, when the real cause and effect played itself out, the financial crisis came as a surprise event; and a big one at that. The resultant lack of access to new credit, clawing back of approved credit facilities, growth in payment defaults and decline in purchases dried up working capital and forced many organisations to abandon most of their strategic initiatives to free up resources for working capital. Some organisations simply couldn’t free up the required resources in time and this led to insolvency and their eventual demise. Others were able to jettison major projects to adapt in time but incurred such significant losses that they emerged as skeletons of their former selves. Yet others thrived in the changed environment and were able to catapult themselves to new heights through acquisitions of competitors or by winning over competitors’ customers. Had the cause and effect behind the interactions between the financial system’s actors, entities, events and subsystems been truly known beforehand, more organisations would have been able to predict the financial crisis and many would have formed strategies to thrive during the crisis. For example, firms such as Bridgewater and Associates and JP Morgan had a better understanding of the cause and effect behind the financial system and either accurately predicted the financial crisis (in the case of Bridgewater and Associates) or understood the uncertainty in predictions and had in place adaptable strategic positions (in the case of JP Morgan).