Is this a Risky Time - or an Uncertain Time?
A lot of the discussion we, and I’m sure you, have been having over the past 6 months has concerned decision making under uncertainty.
The topics vary but are interrelated
What will be the impact of zero interest rates?
What should we be saying to pension clients?
Will I be safe if the company reopens the office?
How do we invest in markets that appear to have lost touch with economic reality?
How will advice businesses cope in an environment of significant commercial and regulatory change?
Come to that, is the demand for personal financial advice growing or shrinking?
In the face of COVID-19, how much latitude should we allow to the economy to continue to function compared to doing everything to protect over 70 year olds? Is Gladys doing a better job than Dan?
Should we be expanding our firm at this time – low borrowing costs, more than usual numbers of available new staff members - or battening down the hatches, or carrying on as normal?
The selection above may seem jumbled and not connected sequentially because of course we don’t confront issues in a grouped or sequential way.
It’s useful to try to think about what characterises these problems and the myriad others we face every day. Are they decisions which are susceptible to quantification? Are they “Risks” in the way investors understand them – reflecting the events of the past and of which we can calculate some probabilities with more or less certainty? Or are they “Uncertainties” where the only thing we know is that quantification is more likely to be confusing than illuminating? President Obama explained that when told Osama bin Laden might be in a compound in Abbottabad, various members of the CIA were asked to provide estimates of probability of him being there and these ranged from 30 to 40% up to 90%. Quantification, far from helping, created confusion.
I learned about this way of distinguishing between Risk and Uncertainty in a podcast I was listening to at the gym. My preferred podcast for the gym is Econtalks[1] and I can’t recommend this highly enough. It’s a weekly conversation between Russ Roberts, formerly a Stanford economics professor, and the author of some recently published book or article. The topics vary enormously – recently on innovation, police killings, Mao’s Great Famine, government vs market provision.
A recent conversation was with Mervyn King, ex Governor of the Bank of England, and John Kay, a leading UK economist. Jointly they have written Radical Uncertainty, which tries to address how best to characterise these problems. They introduce the distinction between “Puzzles” and “Mysteries”. The book is primarily about the inherent failure of economic models to be useful in addressing social problems. The mistake is in assuming that the types of problem I mention above, can be answered through quantification. Mysteries are scenarios where a data set is only one of the elements to consider or where there is not a complete data set or can never be a complete data set. And to the extent they have a social dimension, the “correct answer” may vary with social and local factors like observance of government restrictions, climate, attention to detail, demographics, housing conditions, population density, variations in different peoples resistance to certain existing viruses etc. (Why is India’s mortality rate different to some other countries for example?)
Puzzles have a solution, and generally, one right answer. Computers are good at puzzles and from the list above, the question about the growth of the advice market – a fundamental one for most of us – is best characterised as a puzzle. It is susceptible to solution through a data driven approach, although the data is hard to obtain. Even if the data is characterised by uncertainty, we can at least arrive at a set of probabilities and a set of ranges for outcomes. Puzzles should be thought of as involving risk in the traditional, investment oriented, way. The probability of an outcome within a range.
But the others - even the first on the impact of zero interest rates – look more like mysteries. And mysteries need judgement. Unlike traditional logic which is backward looking, addressing these problems needs forward looking tools.
King and Kay say that an answer is usually best arrived at through abductive reasoning or “inference to the best explanation”. What is the simplest, or most likely cause of where we are now? But looking forward, can we model the outcome with any degree of certainty – probably not – or should we expect to tack and trim as events evolve?
Mysteries, whether social or commercial, have multiple dimensions and need judgement to resolve. And the best way to capture those dimensions, in my experience, is to ensure that multiple points of view are brought to bear through involving people whose judgement you trust.