I’m sure you’ve heard people referring to COVID-19 as a ‘Black Swan’ – something that no-one could have seen coming – but is that actually the case?

Terrible though it is, I don’t think it’s accurate to describe the current situation as a Black Swan because we’ve had to deal with highly contagious, deadly diseases before.

Calling this a ‘Black Swan’ is, therefore, a way to excuse a confused response: ‘how could we have prepared for something that no-one could see coming?’

However, genuine Black Swan events do exist and we need to understand these because the consequences can be significant. It’s also useful to know what we can and cannot do to prepare for Black Swans due to the uncertainty that these involve.

What’s a Black Swan?

In his books, Fooled by Randomness and The Black Swan, Nassim Nicholas Taleb describes a Black Swan as “an event with the following three attributes. First, it is an outlier… Second, it carries an extreme ‘impact’. Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact.”

His concept was new, but the phrase goes back to the Romans who used ‘black swan’ as a metaphor for something scarce. They didn’t believe that there were such things.

Taleb notes that although we now know that black swans exist in nature, we could still gather a lot of data on swans and only have seen white ones. Our data – which could be significant in volume – wouldn’t indicate that swans could be anything other than white. So, when a black swan shows up, “it is an outlier as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility.”

A similar thing occurs with a Black Swan event.

Your observations and experiences to that point have done nothing to alert you to what’s about to happen, nor that such an event could even occur. There’s no precedent.

So, the 9/11 attacks or the first instance of an AI-drive flash crash are arguably Black Swans. These events were both the first of their kind, significant outliers, and had extreme impacts. So there are Black Swans out there, the problem is we don’t know what they are.

But an overheated market crashing or a pandemic aren’t Black Swans: we have seen these in the past and have data. So even though your data suggests that these events are rare or unlikely, it’s wrong to say ‘we’ve never seen this before‘ and call these Black Swans. Instead, these are classic low probability / extreme impact risks.

How can we prepare for what we can’t anticipate?

But given that there are genuine Black Swans, how can we prepare when there’s so much uncertainty?

Trying to assess a risk where there are so many unknowns is next to impossible. Moreover, even if you have some idea of what might occur, the range of potential outcomes (the fuzziness) is so significant that any mitigation measures will either fail or could cause just as much disruption elsewhere.

Luckily, this isn’t as impossible a situation as it might seem. Even though we can’t assess the risk, we still have other tools we can use.

The first is probably the most common although we might not think so: insurance. If you cast your mind back to the A4T model for addressing risk (avoid, tolerate, treat, transfer, and terminate), this is where the third ‘T’ comes in. We transfer some of the risk via an insurance policy. That allows us to offset any losses (a.k.a reduce the impact) with the insurance payout if the event happens.

As an aside, this kind of risk offsetting goes back to the late 1600s / early 1700s, when ships’ cargoes were underwritten by syndicates of investors, the most famous and enduring being Lloyd’s of London. These syndicates were the birthplace of much of what has become professional risk management today. Read Berstein’s Against the Gods for an excellent account of these syndicates and risk and probability in general.

However, risk transfer isn’t the only option available to us.

Enter the contingency plan

We can also build contingency plans in the face of uncertainty if we take an effects-led approach.

Effects-led, means you’re less worried about the cause of a risk than the effect. You focus on reducing the effects on your objective, even though those effects could have been caused a range of different threats.

For example, if my supply chain is critical, I don’t need to know exactly what’s going to trigger a breakdown to understand that any disruption will be catastrophic.

Therefore, I can build a contingency plan to help me ride out an interruption, no matter the cause. That might mean that I need to work out:

• How to maintain a supply of goods in.
• How to manage the transfer of raw materials from my warehouse to the manufacturing site.
• What level of materials I need to have in stock to weather an interruption.
• How to maintain my distribution networks for goods out.

If I have contingency plans to address these challenges, I can deal with the effects of the disruption, irrespective of the cause. So whether the road is washed out by weather, cut off by protestors, or there’s a restriction on movement, the effect is the same and I have plans in place to respond.

And if something truly unexpected comes out of the blue but has the same effect on my supply chain – a real Black Swan – I’m still able to react.

Still maintain a lookout: you might still spot a Black Swan emerging

That’s not to say that I want to remain completely ignorant of what’s happening. I still want as much of a head’s up as possible because that’s going to let me be proactive, not reactive. I still want to establish a horizon-scanning program to keep on top of what’s going on, set ‘tripwires’ to alert me to critical changes, and identify decision points for my contingency plans.

However, even though I want to spot a threat as it’s emerging, I’m going to be more comfortable if I have these contingency plans in place first. And even if the threat is unknown, I’m still managing my risk because I’m addressing my vulnerability and the potential effects.

Therefore, although ‘Black Swan’ is most often used as lazy shorthand to say ‘it’s really bad,’ or to claim that ‘no-one could have seen coming,’ genuine Black Swans are out there. But the level of uncertainty that these entail makes some of our traditional risk management tools, particularly a threat-driven assessment, ineffective. In fact, we’re just as likely to trigger some unintended consequence if we try to develop mitigation for something that’s so unclear.

However, if we use an effects-led approach and build contingency plans, we will be better equipped to deal with a range of situations, those we can anticipate and those we can’t even imagine, the genuine Black Swans. And remember, this approach also helps with very low probability, extreme consequence events because you’re essentially asking ‘what if the worst-case did occur?’

Events like Enron, Deepwater Horizon, the crummy bonds that triggered the 2008 financial crisis, and viruses that jump the species gap remain extremely rare. But they aren’t unprecedented and still have devastating effects.

Meanwhile, there will be threats out there that we can’t anticipate that will catch us off guard.

So whether it’s to deal with a genuine Black Swan, the consequences of sloppy financial oversight, or a pandemic, if in doubt, build a contingency plan.

Andrew Sheves Bio

Andrew Sheves is a risk, crisis, and security manager with over 25 years of experience managing risk in the commercial sector and in government. He has provided risk, security, and crisis management support worldwide to clients ranging from Fortune Five oil and gas firms, pharmaceutical majors and banks to NGOs, schools and high net worth individuals. This has allowed him to work at every stage of the risk management cycle from the field to the boardroom. During this time, Andrew has been involved in the response to a range of major incidents including offshore blowout, terrorism, civil unrest, pipeline spill, cyber attack, coup d’etat, and kidnapping.