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.
Ontonix has recently launched the Black Swan Protection System. 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 and 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 based on the current Complexity Map and without the need to resort to lengthy Monte Carlo Simulation. In addition to the worst-case scenario, the most likely one and the most favourable ones are also determined.
An example of the type of scenarios that the tool generates are shown below.
Applications 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 and to be prepared to face it and to have an idea of the potential consequences, no matter how catastrophic.
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See more posts from Jacek Marczyk (Ontonixqcm) at ontonixqcm.blog