In today’s turbulent world, punctuated by destabilizing events of increasing intensity and frequency, it is vital to know what a worst-case scenario is and which factors are critical. What were considered low-probability events in the past must be countered today on an almost daily basis. However, in the context of high complexity, when turbulence and thousands of interdependent factors combine, decision making and risk management become extremely difficult. While it is impossible to make predictions, one still needs to make decisions, devise strategies and move forward and attempt at least some basic risk management, but with very little knowledge of what those risks may actually be.
What is of greatest concern are the so-called Black Swans – extremely rare events but with huge consequences – which are obviously very difficult to anticipate. Today, Black Swans preoccupy not only investors or corporations, but also regulators and governments. Given their peculiar characteristics, it is practically impossible to predict them and therefore to counter their devastating events. However, protective measures may still be taken, providing one has an idea of what the worst-case scenario might be in a given context.
The Black Swan Protection System has been launched recently. The tool generates automatically a multitude of feasible future scenarios and identifies the most unfavourable ones from a resilience, complexity and sustainability point of view. Scenarios are generated based on user-defined probability of an unlikely event occurring in any of the variables that describe the system. The tool generates Black Swan-type events and helps users to define strategies to mitigate risk in circumstances that are very unlikely and potentially catastrophic. Indispensable for governments, managers, or decision-makers in a Crisis Management context, the tool exposes worst-case scenarios and identifies the factors that cause them.
The severity of a Black Swan is defined by the probability of occurrence in terms of multiples of standard deviations. A three-sigma event, for example, occurs with a probability of 0.27% while a six-sigma event with a probability of 0.00000002%. With this information provided by the user, the system generates multiple scenarios without the need to resort to lengthy Monte Carlo Simulation.
The worst-case scenario is defined as the one with the highest complexity and lowest resilience (lowest sustainability). Applications of the Black Swan Protection System are numerous:
- Crisis Management
- Finance, economics
- Strategy management
- Social engineering
- Critical infrastructure protection
The bottom line is that based on your data, we are able to identify scenarios that define your worst nightmare. Somebody’s Black Swan may not be of concern to you. It is important to be aware of what your worst-case scenario may be, to be prepared to face it and to have an idea of the potential consequences, no matter how catastrophic.
We have applied the tool to identify possible worst-case scenarios at global level, i.e., for the whole World. We have generated 3-sigma scenarios, i.e., situations that have a probability of occurrence of 0.27%. In other words, the probability that these scenarios will actually materialize is just under 0.3%.
Based on the data used for the analysis (data regarding global emergencies), the World today exhibits a resilience of around 71%. It is not excessively low but at the same time it is nothing to celebrate. The Resilience Map is illustrated below.
The Complexity and Resilience Profile, shown below, ranks the various parameters in terms of their impact on resilience and complexity. One may conclude, for example, that today the emergencies that have the highest impact on the World’s resilience are: State collapse, Antibiotic-resistant bacteria, Interstate conflict, or global governance failure. Complexity – which reflects the effort necessary to comprehend and govern the system – is just over 30 Mbits.
That is the situation today. The two possible and worrying future scenarios are as follows. The first one is the most complex scenario. The corresponding Resilience Map is illustrated below. Complexity is about 10% higher than that of today, at 33.6 Mbits, while resilience drops by 9% to 62%.
Man-made environmental catastrophes are at the top of critical parameters, as well as critical infrastructure breakdown, or weapons of mass destruction, as illustrated on the Complexity and Resilience Profile.
But the really bad scenario is the one shown below: complexity is at 33.5 Mbits and resilience is at 49%, almost 20% lower than today. This means the situation will be over 10% more complex and 30% more fragile. In other words, the world can, potentially, be more complex to handle and much more vulnerable than today.
The Complexity and Resilience Profile, shown below, shows that the critical parameters in this hypothetical but possible scenario are: critical information and infrastructure breakdown, man-made natural catastrophes, cyber attacks or failure of financial mechanisms or institutions.
The interesting thing is that the system has not identified pandemics or climate change as driving factors of vulnerability (risk) but has instead indicated more tangible issues such as critical infrastructure and information breakdown or cyberattacks. Even the decline of the US dollar or mismanaged urbanization are seen to be more critical.
However, the goal of this article is not to provide an in-depth analysis but rather to show the potential of new technologies in understanding better the intricate dynamics and hidden risks in highly complex systems and contexts. Evidently, applications can be both civilian as well as military, or in fields such as investments and portfolio and wealth management. The kind of information that can be provided is of strategic relevance and certainly well-suited to today’s highly uncertain and volatile world.