Occurrence versus Emergence
19/Mar/19 19:20
Even after many years of work in the areas of strategy and risk -- from financial services to energy and most recently at Britten Coyne Partners and The Index Investor -- I am still amazed at how most people's notion of "risk" is subconsciously linked to the probability that a discrete event will occur within a defined period of time (usually the next 12 months).
The root causes of this phenomenon are undoubtedly complex, but no doubt include our exposure to statistics courses and insurance concepts, like definable hazards whose potential negative impact can be mitigated (for a price) by transferring them to others.
Our evolutionary past is also to blame. Long before writing and mathematics appeared, we used stories to explain the past and anticipate the future -- and stories are usually focused on people and events with emotional power that cause us to retain them (and the lessons they contain) in our individual and collective memory.
Yet one of the great lessons of history is that it usually isn't the occurrence of events that sinks companies and countries. To be sure, they are often cited as the proximate cause of failure. But in reality, these events mark the end of a much longer process, involving interacting trends, decisions, and randomness, from which new threats emerge, evolve, and sometimes reach a critical threshold that produce events that cause catastrophic failures.
Put differently, it is the continuous variables in a system that should attract our interest, not just the discrete ones; we should focus on emergence, not just occurrence. In turn, this requires that we adopt new mental models that seek to understand and adapt to uncertainty, not just risk -- that are focused on estimating the remaining time before a critical system threshold is reached, and not just the probability that an event will occur.
In truth, these concepts are actually related, even though we often fail to see them as such. Consider, for example, a simple system model that does not evolve over time, in which there is a 5% probability each year that a given event of magnitude X will occur. What we usually fail to consider is how that probability increases as the time horizon lengthens. Over five years, there is a 23% chance the event will occur; over 10 years, a 40% chance, and over 20, a 64% chance.
In practice, however, the challenge is usually much greater, because the complex socio-technical systems that produce emergent threats and catastrophic events are themselves constantly evolving. Most of the time, we operate in the realm of true uncertainty, not risk, and the mental models we use to make sense of the world too often fail to recognize this critical distinction.
The lesson of this short story is this: If our goal is to avoid catastrophic failures, we must constantly struggle to repress our natural tendency to focus only on the probability of discrete events occurring within the next year, and instead pay much more attention to the continuous interaction of forces within our world that give rise to the emergent threats which pose the greatest danger to the survival and success of both organizations and investment strategies.
The root causes of this phenomenon are undoubtedly complex, but no doubt include our exposure to statistics courses and insurance concepts, like definable hazards whose potential negative impact can be mitigated (for a price) by transferring them to others.
Our evolutionary past is also to blame. Long before writing and mathematics appeared, we used stories to explain the past and anticipate the future -- and stories are usually focused on people and events with emotional power that cause us to retain them (and the lessons they contain) in our individual and collective memory.
Yet one of the great lessons of history is that it usually isn't the occurrence of events that sinks companies and countries. To be sure, they are often cited as the proximate cause of failure. But in reality, these events mark the end of a much longer process, involving interacting trends, decisions, and randomness, from which new threats emerge, evolve, and sometimes reach a critical threshold that produce events that cause catastrophic failures.
Put differently, it is the continuous variables in a system that should attract our interest, not just the discrete ones; we should focus on emergence, not just occurrence. In turn, this requires that we adopt new mental models that seek to understand and adapt to uncertainty, not just risk -- that are focused on estimating the remaining time before a critical system threshold is reached, and not just the probability that an event will occur.
In truth, these concepts are actually related, even though we often fail to see them as such. Consider, for example, a simple system model that does not evolve over time, in which there is a 5% probability each year that a given event of magnitude X will occur. What we usually fail to consider is how that probability increases as the time horizon lengthens. Over five years, there is a 23% chance the event will occur; over 10 years, a 40% chance, and over 20, a 64% chance.
In practice, however, the challenge is usually much greater, because the complex socio-technical systems that produce emergent threats and catastrophic events are themselves constantly evolving. Most of the time, we operate in the realm of true uncertainty, not risk, and the mental models we use to make sense of the world too often fail to recognize this critical distinction.
The lesson of this short story is this: If our goal is to avoid catastrophic failures, we must constantly struggle to repress our natural tendency to focus only on the probability of discrete events occurring within the next year, and instead pay much more attention to the continuous interaction of forces within our world that give rise to the emergent threats which pose the greatest danger to the survival and success of both organizations and investment strategies.
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