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Frameworks need numbers

The coronavirus has brought into sharp focus the need for frameworks. Frameworks are tried and trusted models for dealing with a situation. We use them in business all the time because they eliminate risk and uncertainty. Risk and uncertainty are central to dealing with the coronavirus.

The other thing we know about frameworks is that there is nothing new under the sun. In one way or another they have been around forever but they get retitled and some are pushed forward as a new solution. I was reminded of this the other day when reading about a book published in 1921 by the American economist Frank Knight. It is called Risk, Uncertainty And Profit. Knight argues that when we look to the future there are many things we don’t know. The future is very uncertain (except death and taxes of course). Risk on the other hand is measurable. When we get on a plane (as we used to do) we know that the risk is minimal. There are lots of data on flying hours and accidents that tell us that it is the safest way to travel.

So it is in business. We may alter the price of our products knowing from previous price changes what the result will be. Risk is mitigated by experience based on numbers – even if the numbers are fairly vague. As Henri Poincaré says in The Foundations Of Science, 1913, “It is far better to foresee even without certainty than not to foresee at all”.

However, when we look into the future with regard to a subject with which we have no previous experience, there is considerable uncertainty. We cannot measure the risk and so our actions are based on judgements – perhaps even gambles.

This is what has happened with coronavirus. Governments have no experience in dealing with such an event and so their initial actions were judgemental. Take for example the situation in the UK where the first action that was recommended and pushed to the extreme, was washing hands. Washing hands is a good idea but there was little mention of social distancing, the need to wear face masks, or to eliminate unnecessary journeys. When the numbers of infections and deaths emerged, risk became measurable and the management of the situation became more specific. We were then told the importance of “r”, the number of people one person with the disease is likely to affect others. Once that "r" number falls below 1, we know that the disease will ultimately die out. In this way, social distancing, a key determinant of r, becomes the prisk factor. Risk becomes measurable and actions can be taken with more confidence.

Numbers are crucial in most frameworks. They are vital in managing the coronavirus. It is why experts often pronounce that the solution to the problem is test, test, test. However, numbers only present themselves after a while. In many situations we have to determine a course of action before we have any numbers. This was the case with coronavirus in the UK and the US in February of this year. There were frameworks available but they were not always used – or at least they didn’t seem to be.

The frameworks I have in mind here are the experiences of those who have gone before us. China provided the earliest framework as they were the first to suffer the disease. Maybe Western governments felt unable to quickly lock down parts or all regions of their countries in the way that China did. And then Italy was hit big time. Italy followed the China model by quickly locking down Lombardy and soon afterwards a countrywide lockdown followed. The UK and the US could see this happening and yet it took them some time to react. Governments are paranoid about being seen to be doing the right thing. Other countries such as Germany didn’t go into complete lockdown at the same time as us, giving governments an incentive to hold on and see what happens to the numbers. As we know, the biggest mistake can be to leave actions too long in which case the cost and the remedy is much more severe.

Having thought about the frameworks provided by other countries, it is important to mention the outliers. Outliers are countries that are doing things differently and, who knows, they could be right. Sweden is such an example in that it has rejected a stringent policy of social distancing and economic lockdown. The copycat logic of lockdown adopted by most national governments looks as if it is the right approach. However, the scenario hasn’t yet played out. We don’t know to what extent the balancing act of looking after the immediate health of a nation will have on the long-term economic health of that nation. The consequences of the lockdown could cause such economic devastation that long-term health is exacerbated.

We return to the importance of frameworks and in particular the importance of numbers within those frameworks. If we know where the hotspots of the disease are, we can deal with them more readily. If we know through testing how many people have built immunity to the disease, we know whether it will wax or wane. If we know which groups of people are particularly vulnerable to the disease, we can protect them. Uncertainty results from lack of data. Risk can be measured if we have the numbers. Frameworks need numbers.

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