Imagine two portfolio managers arriving at their desks on the same morning. They have comparable experience, access to the same information, and are looking at the same market. One has slept well and is coming off a strong run. The other has slept badly, has lost money over the past month, and is already tense before the market opens. At 9am, the same unexpected piece of information appears on both screens. We tend to think of what happens next as a problem of cognition. Who interprets the information correctly? Who follows their process? But there is a more interesting question: are these two people actually confronting the same decision? The information may be identical, but the systems interpreting it are not.
Much of what we do to improve decision-making concentrates on the quality of information and the conscious thought applied to it. We teach frameworks, identify biases and improve analytical processes. All of that matters, but it starts relatively late. Before we consciously deliberate over information, the brain is already trying to make sense of it. Understanding how it does that changes how we think about performance.
How the brain makes sense of the world
It is tempting to imagine perception as a relatively straightforward process: information comes in from the world, we perceive it, and then we decide what it means. The brain appears to do something more interesting. It has two fundamental strategies: prediction and efficiency.
The first is necessary because the world rarely provides complete information. Circumstances change quickly and we often have to act before all the evidence is available. As philosopher and cognitive scientist Andy Clark has described it, the brain uses what it has learned before to anticipate the causes of the information it receives. Those expectations help shape how incoming information is interpreted and are updated when the evidence does not fit. The brain, in this view, is less like a camera recording what has happened and more like a forecasting system trying to stay slightly ahead of events.
That brings us to the second: efficiency. The nervous system is dealing with vastly more information than we could ever examine consciously. It would be impossible — and spectacularly inefficient — to consciously examine every sensation, retrieve every potentially relevant memory, compare every new situation with everything we have encountered before, and deliberate over every possible response.
Much of this work therefore takes place outside conscious awareness. The brain filters, prioritizes and recognizes patterns. With experience, it becomes exceptionally good at this.
What once required effort can become automatic, and what once required analysis can become recognition. In that sense, non-conscious processing is not a curious side feature of the mind. This “adaptive intelligence” is part of what makes intelligent behaviour possible at all. The trade-off is that consciousness often receives the conclusion without having access to all the calculations that produced it.
Prediction and efficiency make expertise possible. A tennis player can begin moving before an opponent’s serve has been struck; an experienced physician can sense that a patient “doesn’t look right” before being able to explain why. A portfolio manager who has watched markets for twenty years does not see the same screen as someone on their first day.
The numbers may be identical, but the experienced investor brings a vast library of patterns against which the present can be compared, often without conscious deliberation. Gary Klein’s research on expert decision-making has shown how experience can turn deliberation into recognition: experts can recognise meaningful patterns before they can fully articulate what they have noticed.
But there is a catch. The models being used to interpret the present were built in the past. Recent losses can alter expectations. Success can change perceptions of risk. A pattern that was useful in one environment can persist when the environment has changed. Expertise therefore depends not only on what we have learned, but on recognising when what we have learned no longer fits. The important question is not simply what information is in front of us, but what is shaping our interpretation of it.
Physiology plays a role
The brain trying to predict what happens next in the market has another job: it has to keep its owner alive. While an investor is interpreting information on a screen, her brain is also regulating a living body. It is monitoring and adjusting temperature, cardiovascular activity, respiration and energy needs, while responding to signals such as hunger, fatigue and physiological arousal. Through interoception, the brain receives information about what is happening inside the body; through allostasis, it anticipates what the body is likely to need and regulates accordingly.
This means the physical condition of the body is not separate from the processes involved in making sense of what is happening around us. The brain is simultaneously processing information from the outside world, information from within the body and what it has learned from previous experience. Sleep, fatigue, physiological arousal, circadian timing and energy availability are therefore not simply background conditions that determine whether we feel good or bad. They form part of the context in which information is being processed. We tend to think their effect on performance comes relatively late: we see the situation accurately, become tired or stressed and then think less clearly. Certainly that can happen. Fatigue and physiological stress can affect attention, working memory and cognitive flexibility.
But there may be an earlier effect too. Physical state can influence what captures attention, what feels salient and how ambiguous information is interpreted.
Return to our two portfolio managers. One is well rested; the other is sleep-deprived and physiologically depleted. The same ambiguous information appears on both screens. They have access to the same facts and may have comparable expertise, but the biological conditions in which those facts are being processed are different. Different cues may capture their attention. Potential threats may carry different weight. The same uncertainty may be harder to tolerate.
We do not necessarily experience this as our physical state altering our interpretation of the world. We experience the world. The market looks more dangerous. The opportunity looks less compelling. The information hasn’t necessarily changed; the condition of the person interpreting it has.
Emotion as information
The relationship between physical state and decision-making becomes particularly interesting when we consider emotion. What we feel does not arise independently of the body. Emotion emerges from the brain’s ongoing attempt to make sense of what is happening, drawing on
information from the body, the situation we are in, what we have experienced before and what we expect to happen next. A racing heart, for example, does not come with a label explaining what it means. In one context it may accompany excitement; in another, anxiety or fear. The physical signal matters, but so does the meaning the brain makes of it.
Now imagine an investor who has spent weeks researching a company. During the final meeting before increasing her position, she suddenly feels uneasy. Something doesn’t feel right. The feeling is conscious; the processes that produced it may not be. Perhaps twenty-five years of experience have allowed her to detect an inconsistency that has not yet reached conscious articulation. Perhaps something about the situation resembles an investment that ended badly. Perhaps she is exhausted, or several recent losses have made her more sensitive to threat. Perhaps several of these are contributing at once.
This is what makes emotion so interesting for decision-making. The feeling may contain information, but it does not tell us where that information came from. Antonio Damasio’s work challenged the idea that emotion and bodily state sit in opposition to rational thought, showing that when systems involved in emotion are disrupted, decision-making can become impaired rather than more rational. Emotion is not simply interference that needs to be removed before good thinking can begin. But neither should it automatically be treated as an accurate reading of the world.
The useful question is therefore not simply, “Should I trust this feeling?” but, “What is this feeling information about?” What exactly am I feeling? Why now? What might I have noticed without consciously registering it? What previous experience might be shaping my response? What is happening in my body? The aim is not to decide whether emotion is good or bad, rational or irrational, but to become more curious about the information from which it has emerged.
This is central to the work we do at Rethink with investors and other high-performing decision-makers. The objective is not emotional suppression but greater emotional granularity: becoming better at identifying what we feel so that the information within the experience can be examined rather than automatically acted upon or dismissed.
Susan David’s description of emotions as “data, not directives” captures this well. Emotional awareness is not a softer adjunct to rigorous decision-making. It can give us a window into processes influencing judgment that conscious analysis alone cannot directly observe.
Capability is not the same as access
All of this points to a distinction that is easy to miss when we think about performance. What someone is capable of and what they can access in a particular moment are not necessarily the same thing. A senior investor does not lose twenty years of experience after several difficult weeks. An athlete does not suddenly lose a skill when the stakes increase. The capability is still there. What can change is the condition in which that capability has to be expressed. Fatigue, physiological stress, emotional state and cognitive load can affect attention, working memory, flexibility and regulation, changing how effectively someone can bring what they know to bear on the situation in front of them
This matters because when performance deteriorates, we often respond by trying to build more capability: more preparation, more analysis, another framework, another skill. Sometimes that is exactly what is needed. But sometimes the problem is not what the person knows or can do. It is their access to capabilities they already possess. We spend enormous effort building capability. We should be equally interested in the conditions that determine access to it.
What counts as a performance variable?
Once we take this seriously, the boundaries around what counts as relevant to performance begin to expand. Sleep, exercise, nutrition and recovery are increasingly recognised as important, but they are often still treated as things that support cognition: sleep so you can concentrate, exercise so you have more energy. Cognition remains at the centre and health sits somewhere around the edges.
Take something as seemingly unrelated to judgment as light. Imagine an investor who wakes before sunrise for calls with Asia, spends most of the day indoors, works late and regularly crosses time zones. His body does not know that the clock in his hotel room says it is time to sleep. It is responding to biological and environmental signals, including light. Light entering the eye does more than allow him to see; it provides information to systems involved in circadian regulation, influencing sleep-wake timing, alertness and other physiological rhythms.
If his judgment became inconsistent, we might examine his analytical process, workload, motivation or resilience. We would be much less likely to ask whether the environment in which he is asking himself to perform is working with or against his biology. Yet if the quality of judgment depends partly on the condition of the system producing it, these are not peripheral questions. They are performance questions.
Performance over time
There is a difference between asking how someone performs in one important moment and asking how they continue to perform over a career. In the moment, we might ask what is influencing the system now: What have I learned from previous experience? What physical condition am I in? What am I feeling, and what might that feeling be information about? Can I access and deploy the capabilities I need?
Over time, the question changes. What am I repeatedly doing to the system from which I ask myself to perform? Sleep, recovery, physical health and the environments in which we work matter not simply because they determine whether we perform well tomorrow morning, but because sustained performance depends on preserving the health and adaptability of the system over time.
Adaptability matters because the system is continually learning. What happens today becomes part of what the brain brings to tomorrow. Experience makes expertise possible, but it can also make old models harder to abandon. Sustained performance therefore requires more than accumulating expertise or extracting the highest possible output from ourselves. It requires maintaining a system capable of learning, recovering and updating when the world no longer behaves as expected.
For decades, the study of high performance and decision making has understandably focused on outputs: judgment, execution, resilience, discipline and results. Increasingly, we also need to understand the system producing them. The question is not simply how to make better decisions. It is how to build and maintain a system capable of making them repeatedly, under changing conditions, over time. We can improve what decision-makers know. We can give them better data, better frameworks and better processes. But every one of those capabilities is ultimately expressed through a living, predictive system whose history, expectations, emotions and physiological condition are already influencing what feels important, what looks threatening and what appears to be true.
If we want to understand sustained performance – and how people make better decisions over time – we need to understand the system behind the decision-maker.