The Rich Don’t Penny Pinch

Why What Looks Smart in the Moment is Often Dumb in the Long Run

Sean McClure
14 min readJul 31, 2021

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Penny Pinching Behavior

Penny pinching is something we see all the time. People do it when they’re deciding where to eat. They do it when they’re cutting coupons out of the flyer. They do it when they’re deciding who might make a good life partner, what clothes to bring on a camping trip, or which hotel to stay at. They do it when they’re stressing over their investments, when they’re deciding what school to attend and which company to work for. People do detailed-oriented work all the time. It’s a “system 2” kind of thinking to borrow Kahneman’s phrasing; the mind’s slower, analytical mode, where reason dominates.

Penny pinching sounds like a good thing to do. Especially for important life decisions like money, education and life partners. Now I’m not here to tell you we should never slow down and assess a situation closely, but rather that it’s easy to do this in situations where it’s not appropriate. The reason it’s often not appropriate is because we almost never have access to the amount and kind of information that would make penny pinching an effective life strategy.

Any time we look into the details of something we are making a big assumption about how information maps to the future. We are assuming information can be tallied up and summed into some final answer that best tells us what to do in a given situation. But this isn’t how information works in complex situations. Under complexity information does not move from input to output as a linear sum of its parts.

Information works in nonlinear and highly opaque ways. The way information gets used under complexity is multiplicative, where bits of information interact with other bits of information in ways we will never know. We know this because this is a fundamental property of complex systems and thus situations. The causal chain that links inputs to outputs cannot be known.

A consequence of this multiplicative complex interaction of information is that we cannot know how the information we have available today will play out in the long run. We cannot tally the information and run cost-benefit analysis for anything but the simplest of systems. Simple systems, by definition, condescend to let us know how information flows from beginning to end, but in complex systems this is not the case.

While getting into the information-theoretic reasons for opacity in complex systems is fascinating, it’s not what I’m here to discuss in this article. What I want to talk about here is how the type of behavior that makes us look smart in the moment (i.e. penny pinching) ends up not being smart in the long run. I gave some examples at the beginning; let’s look at a couple more to dig deeper.

Imagine you are in your car driving and you notice someone in another car, alone, wearing a mask. This is during the covid pandemic so seeing someone wearing a mask is not overly surprising. But then you stop and think wait a second, this person is alone and wearing a mask. Isn’t that odd? In fact it seems downright ridiculous. Why would anyone wear a mask in their car when they are alone?

If we are only taking into consideration the information that is immediately available then the situation does indeed seem pretty ridiculous. But if we stop and consider what might be the broader context we can imagine scenarios where wearing a mask alone makes a lot of sense. For example, if the person is driving to the supermarket where they will be required by law to wear a mask, then wearing a mask in the car en route to the market makes sense. After all, why fumble and fidget with a mask when you’re getting out of your vehicle or walking into the building? Doesn’t it makes more sense to just give yourself a blanket policy that says “I put my mask on whenever I leave the house, and don’t take it off until I get home.” That beats trying to keep track of who needs me to wear the mask, chances of dropping the mask, dirty hands touching the mask, losing the mask, etc.

I’m not trying to suggest here whether or not people should wear their masks in the car when by themselves. The point is, if we step back and consider what might be the broader context it becomes possible that the behavior is in fact not so stupid. In fact, it might be more stupid to not wear the mask in situations like being by yourself inside a car or walking by yourself on a trail. There are so many situations that could arise where by law you are going to have to put on the mask anyway, and having the habit of putting a mask on regardless makes all the possible scenarios a non-issue.

Another example might be washing your hands when you get home. Does it make more sense to ask yourself if you touched anything when you stepped outside? Maybe you were just grabbing something from the car. You recall using your keys to press the elevator buttons, and as for the car, well you’re the only one who touches the handle anyway. But maybe you touched something else? But viruses don’t last on surfaces that long. Or do they? What did the last study say? Does it makes sense to reason about the situation with all the available information you THINK you have, or does it make more sense to just wash your hands when you get in regardless. It should be obvious to most that the correct answer is just wash your hands, and the reason is that it’s a low cost decision that doesn’t cause you any harm.

Another example is water bottles and expiry dates. You can chase down all the studies you want about plastic potentially leaking into water, or you can just make a general rule that all food and drugs have expiry dates. It makes it a non-issue, avoids potential law suits, and costs almost nothing to implement. What’s smarter? Running a ton of naive analyses on potential water contamination with plastic bottles or just putting the expiry date on the bottle? Hopefully the answer there is obvious.

These examples might seem trivial but we do this all the time in real-life situations. We “penny-pinch” the information we think is available and sound fairly smart or even responsible doing do. The literal example of course is cutting out coupons from the flyer, attempting to save money. It sounds smart on the surface. If you are “money smart” then why not look for opportunities to spend less? After all, over time that should amount to potentially large savings, and may be critical when the time comes to make a big payment. But cutting out coupons and saving bits of money goes against what we know about how information maps to the future. What is more likely to happen via penny pinching is never putting ourselves in opportunity’s way. And that, of course, is a problem.

Opportunity and Path Selection

The thing about information and complexity is that we don’t have access to the amount or type of information that allows us to make penny pinching kinds of decisions. Instead, we have approximate, high-level, abstract signals from the environment that guide us towards an objective. We find certain tasks fun, we become attracted to certain situations, we feel uneasy about others. We feel inclined to go visit somewhere or someone. These feelings are not ghosts with no substance they are evolutionary strategies to solve problems when information is scarce. Feelings are ephemeral and ill-defined precisely because they operate at the highest levels of abstraction, and enable convergence to good solutions. Feelings don’t pretend to have access to information that is not available. The same cannot be said for analytical, logical thinking.

The reason penny pinching behavior doesn’t map to successful outcomes is because it can’t solve genuinely complex problems. It cannot see past extremely short prediction horizons. Life is immensely complex, and involves countless pieces that interact in ways we can never know. This strong interdependence between life’s inputs are what renders analytical thinking impotent under complexity. Analytical thinking requires pieces that visibly connect in a logical fashion, such that the causal chain between input and output is apparent. In the complex regime such causal chains cannot be uncovered. This isn’t an opinion; this is a fundamental property of genuinely complex things.

Here’s the point. Those who don’t embrace uncertainty are failing to attempt multiple paths to solve a problem; a critical ingredient in any approach that hopes to make complex problems tractable. In any regime where no causal chain can be uncovered the solutions are not available without random sampling. Only through rapid, ad-hoc sampling of the space of possibilities do complex problems become tractable. This is the realm of deep epistemic uncertainty, where we MUST apply trial-and-error and course correction to converge on solutions that produce valuable outputs.

Penny pinching behavior is the opposite of random sampling. Penny-pinchers become fixed on their analyses, tempted by their precision. It’s intoxicating to hear one’s own analysis of a situation. Our innate fear of the unknown makes us feel good about the narrative. We need control. But such control is illusory. It only exists in our minds, not in reality. The narrative we use to satiate our fears about the future are still just that; stories.

This is why non-penny-pinching behavior works. The approximate, near-random behavior of successful people in complex domains should now be less surprising. It is precisely inline with how genuinely complex problems get solved. We need to move through life in a very approximate, surface-level fashion because if we pretend to have access to more information than we do there are dire consequences. It’s not merely that focusing on the details don’t work, it’s that they are massively detrimental since they prevent you from sampling enough possibilities. Penny pinching freezes one into a path that will not work unless they are extremely lucky, which of course isn’t reproducible anyway.

And so a core reason why those who penny pinch fail to see longer-term success is they remain frozen in their intoxicating yet grossly incorrect narratives about how to best plan for the future. They don’t put themselves in opportunity’s way, which means they do not attempt enough paths. They don’t sample the possibility space to converge on a solution; instead they choose sounding smart and being comfortable, which rarely if ever pays off.

Losing it All

There is another property to real-world situations that tells us not only that things don’t accumulate as sums, but that whatever has been accumulated can be lost in an instant. Perhaps the most famous recent example is businesses losing their shirt to the Covid pandemic, particularly small ones who lost much of what they had overnight (many larger businesses only survived through bailouts). Another example is Bitcoin. The extreme volatility of bitcoin has people excited for a number of months as the numbers climb, only to have all gains-to-date wiped out in a very short time period.

What about nature? Do we see natural systems lose everything in a moment? Well in most system we don’t, and the reason should be fairly obvious. Nature doesn’t penny pinch. In fact we see the opposite phenomenon; we see redundancy everywhere. Take for example the human heart. If you look at an intricate image of coronary circulation you will see something that looks like an awful amount of redundancy. It looks like the exact opposite of efficiency; what appears to be a massive amount of waste. We see the same pattern repeating again-and-again, channels of circulation going every which way instead of a direct path towards its destination. What’s with the mess?

But of course, this is on purpose. After all, this is nature.

Redundancy is how nature operates on simpler rules. If you try to account for every contingency you end up with over-engineered solutions that break. Unlike many of today’s outdated business models, successful systems are *not* lean, they are redundant. I would argue few of today’s engineers (and some scientists) get this. Nature uses redundancy because it “knows” (via evolution) that there is an inevitability to failure. While catastrophes are rare they are also inexorable. Critically, they wipe out whatever has been accumulated to-date.

Penny pinching is the opposite of redundancy. It tries to only do what is absolutely necessary, assuming that such behavior will map to better outcomes in the future. Just as businesses who keep tight efficiencies on their processes exist as extremely fragile entities who can go bust at any moment, so too do penny pinchers, who expose themselves to extreme fragility. Penny pinching doesn’t have any “buffer capital” and so it’s only a matter of time that everything saved to date is wiped out in a single event.

And of course this is what we see all the time. We all should be able to relate to this. We try to put in place plans, recipes, efficiencies, processes that tally up the available information and turn it into a strategy going forward. And what happens? Catastrophic failure. A health crisis, a job loss, a friend in need, a broken vehicle part, etc. Something inevitably pops up, and in that rare yet impactful moment wipes out everything that was saved up to that point.

So it’s important to understand what this means. It’s not just that all the accumulated wealth, by any definition we use of “wealth”, is lost. It means that the nitpicking, planning, penny pinching behavior that preceded the loss was pointless. None of that made secure the revenue, the business, the friendship, the family, the opportunity. The so-called efficient use of information and resources is something that only exists at the shortest temporal scales; move beyond that and there’s a very good chance it will be lost.

Redundancy isn’t just about having backups. From an informational standpoint it’s about the same pattern we discussed in the last section; nature builds for contingency by ensuring multiple attempts can be made to solve the problem. There are far more opportunities to arrive at the right solution when faced with a challenge from our environment when we have many possible paths to attempt. The intricacies of the human heart is just another example in nature of a redundant problem-solving system.

Behavior Preceding Richness

Where people get it wrong is they assume that only the “poor” (by any definition) penny pinch because they have to. But I argue that non-penny-pinching behavior PRECEDES the successful outcomes of people. In other words, when you see someone successful in life that seems to care less about saving money, finding efficiencies, weighing pros and cons, it’s not because their success precludes the need to worry about these things. Rather it’s because they were like this before their success. People who take the broader context, operate at the surface, embrace trial-and-error, and are steeped in redundancy have more success in life. These individuals don’t pretend to know how things map to the future. They understand intuitively that the amount and type of information needed to make analytical decisions is not available in complex situations.

Next time you notice someone moving through life successfully, note their behavior. Are they penny pinching at every turn, trying to squeeze out every possible advantage, tallying up every piece of information and running cost-benefit analyses? OR are they operating at a higher level, using heuristics and general patterns to make decisions? Are they able to move forward using scant data about a situation? Do they seem to create more than one might think possible on a tight deadline? Do they seem to “waste” time and resources on things that don’t look productive? Do they appear less stressed when things go south? Do they seem to appreciate something bigger than the present moment? My guess is you will notice the latter set of behaviors.

The human search for narrative makes it too easy to assume some people are just smarter or more capable. But in reality they have behaviors that work better under complexity. It’s not some inherent intelligence or privileged place in life. Such excuses make it too easy to not understand what’s going on. An honest look at what’s happening looks at how complex problems get solved. It takes into account how information maps to future scenarios. What becomes obvious when doing so is how some people are embracing their natural, evolutionary ability to solve tough problems and operate with very little available information. This of course is how our ancestors survived for millions of years.

Operating at the Surface

So what do we do about it? How do we get away from penny pinching behavior? This comes down to accepting that we do not have direct access to the kind of information that makes decision making effective, despite living in an “information economy.” Accessing vast amounts of data via the internet is not the same as being able to extract wisdom from it. And that’s because genuine wisdom occurs via a synthesis of information. Without an ability to blend the information into an emergent understanding we only have raw inputs, not valuable outputs.

This is why technologies like machine learning (ML) work the way they do. They are not pieces of software that merely ingest data and run through rules-based programming in order to produce an output. In fact, this is exactly what they are not. ML works because it creates approximate models to produce its output. It pays attention only to high-level signals and feedback and attempts to reproduce that output, or find high-level similarities between pieces of information. Machine learning is the antithesis of rules-based, analytical style analysis.

The reason I use ML as an example is because it’s a technology that came about to solve problems that traditional, rules-based software could not; genuinely complex problems. But this article isn’t about ML. This is about any information processing construct capable of making complex problems tractable. While ML only achieves this in the most narrow of ways, genuine intelligence like the human mind does this exceedingly well. It is how we have adapted to solve real-world problems.

And so what we should do is learn to pay attention only to the highest level signals; aim and move. The highest levels of abstraction from our environment that suggest a course of action. This is, of course, the role emotions play in problem solving. Our education system has hardwired us to think of problem solving in the mechanistic, logical fashion. This works for simplistic, laboratory-style problems where you want to extract and isolate in order to define something. But in the real world, components don’t dictate behavior, interaction does; interaction that creates fundamental opacity. We simply don’t have the ability to see how inputs are causally connected to outputs. Period.

So forget penny pinching, logical tallying of information. Stop weighing what you think are the pros and cons. Stop cutting out coupons, pining over where to eat, running your potential life partner through a checklist, stressing over what clothes to bring on the camping trip, spending more than 10 minutes reading hotel reviews, or paying too close attention to your investments that move via the vagaries of the market. This kind of behavior won’t produce good outcomes in the long run. You need to sample a vast number possibilities. You need to place yourself in opportunity’s way. You need to take-on the willingness to be redundant, messy, inefficient, approximate, ill-defined and emotional. The reason is not to shun logic or eschew analytical thinking. These have their place. The reason is to leverage what nature has given you; a mental and physical arsenal to deal with highly-complex situations that lack direct access to information. To make tractable the kind of high-dimensional problems that arise in our personal and professional lives.

To do so is to be genuinely smart.



Sean McClure

Founder Kedion, Ph.D. Computational Chem, builds AI software, studies complexity, host of NonTrivial podcast.