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#9 John Kay, Radical Uncertainty

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#9 John Kay, Radical Uncertainty
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Professor John Kay on his new book co-authored with Mervyn King, Radical Uncertainty.

In this Fund Shack private equity podcast hosted by Ross Butler, we explore the intricate realm of decision-making in the face of radical uncertainty.

Our guest, Professor John Kay, co-author of the book “Radical Uncertainty” with Mervyn King, provides valuable insights into this challenging subject.

Radical uncertainty is the concept that in certain situations, there is no clear answer or predictable outcome to decisions. Conventional problem-solving techniques prove inadequate in such circumstances.

Professor Kay notes that problem reasoning, while useful for games like cards, falls short when it comes to grasping complex issues. During the 17th century, there emerged attempts to extend these ideas to diverse domains. The initial extension of radical uncertainty was seen in mortality tables, akin to Unitarian mathematics.

This application made sense since the determinants of human longevity, while not precisely akin to physics, were reasonably understood and remained relatively consistent over time.As time went on, these principles were applied to other domains. Weather forecasting, for instance, started to embrace uncertainty. While you might hear forecasts like “a 40% chance of rain tomorrow,” the explanation can be quite convoluted. In essence, this means that on 40% of occasions where experienced meteorologists make such predictions, it actually rains. Modern weather forecasting models, though criticized for their reliability, perform well in the short term, typically up to 35 days.

The challenge arises because the underlying factors driving weather patterns change over time, making long-term predictions difficult.

Models play a crucial role in understanding and managing uncertainty. However, it’s important to recognize their limitations. Often, models are used to justify decisions already made, rather than serving as impartial tools.

Manipulating a model to produce a desired outcome is a common issue in finance, politics, and business.The financial crisis of 2008 highlighted the pitfalls of relying too heavily on models for risk management. For instance, the models used by banks were based on a data set where banks hadn’t gone bankrupt. Predicting bank failures using such a model proved unreliable.

Professor Kay observes that culture plays a significant role in decision-making, especially in financial institutions. There’s a pervasive belief that decisions must be backed by unassailable data and logic. However, when dealing with highly complex scenarios, this approach can be limiting. Those who dared to question the prevailing narrative before the 2008 crisis often found themselves sidelined or discredited.This cultural element extends beyond finance into various sectors, contributing to a broader lack of trust in experts.

Experts, too, often feel compelled to offer methodologically explainable recommendations rather than embracing the inherent uncertainty in complex situations.In an environment fraught with radical uncertainty, practical decision-making requires a balance between faith in one’s judgment and experience and a structured approach.

Private equity, for instance, involves creating business plans that project financial outcomes five years into the future. While these projections rarely materialize as planned, the exercise of constructing such plans can help organize one’s thinking about the market, costs, and necessary resources. The key is not to view these projections as predictions but as tools for better understanding the business landscape.A reference narrative is a story one tells oneself when dealing with uncertainty. It’s the mental framework for navigating unknown terrain. When encountering uncertainty, people often default to a reference narrative, which represents a scenario where things go relatively smoothly. Risks, then, are elements that could derail this reference narrative.

In private equity, Professor Kay advocates the construction of a reference narrative, which helps identify critical factors and potential risks. The goal is not to predict the future but to ensure that the narrative remains robust and resilient to potential disruptions.

Economics, at its core, should be about addressing practical problems. Yet, the discipline has veered toward methodological approaches rather than solving real-world issues. The shift away from the original intent of economics has led to a lack of trust in experts and a failure to appreciate radical uncertainty.

Navigating radical uncertainty in decision-making requires acknowledging its presence and embracing a structured yet adaptable approach. Models have their place, but they should be viewed as tools, not ultimate authorities. Developing a reference narrative and assessing its resilience to risks is essential. In economics and beyond, recognising and addressing radical uncertainty is crucial for making informed decisions in a complex and ever-changing world.