“Even with all the data and good intentions in the world, there will always be some fluctuation”
If there’s one thing that’s certain in life, it’s uncertainty. And although we keep beating this proverbial horse of a concept, I promise it’s only because the horse is incredibly important and diverse in what it can teach us.
In microeconomics, there’s a foundational type of uncertainty that every business needs to address: How many people are going to buy how many of what, at what point in time?
This uncertainty makes decision-making tricky. How many inputs do you need to buy? How much do you produce? How much do you ship to Country A compared to Country B, or Store 1 compared to Store 2?
In a world of perfect economic efficiency, you’d have all this information, and there’d be no waste. Everything would balance out just right – the Goldilocks of supply and demand; not too much, and not too little.
You’ll find that this equilibrium, and our desire for it, is intuitive. Imagine you own a grocery store that sells strawberries. If you order more strawberries than your customers will buy, they’ll go bad and you’ll have to throw them away. This isn’t only a waste of food but a waste of money – you lose on all the strawberries you bought and couldn’t sell.
But if you don’t order enough strawberries, that means missed opportunities – you could’ve sold more strawberries to more customers and made more money. Moreover, customers might get annoyed at the shortage and decide to frequent your competitors instead.
It’s clear why you’d ideally like to have perfect information – it means just the right amount of strawberries, leading to your optimal outcome as a business.
Of course, in implementation, this isn’t just about strawberries. Companies hire consultants and have entire operations and analytics departments to streamline their business processes and minimize shortages or surpluses at any given point.
It may not be the sexiest thing in the world, but you can imagine that even small efficiency gains, when spread out over the expanse of a company like Amazon or Walmart, can lead to monumental outcome differences.
For this reason, we’d be forgiven for thinking that this Goldilocks equilibrium is the end-all-be-all we should strive for. But, as we like to say in economics, the real world is more complicated than that.
Even with all the data and good intentions in the world, there will always be some fluctuation. In reality, it’s impossible to prevent a little surplus here or a little shortage there, no matter how clever you are or how much data you have.
If nothing else, remember that people aren’t always predictable. And even if that unpredictability balances out on average, it probably won’t balance out perfectly every time – that’s why we add the caveat of ‘on average.’
The problem is that sometimes, surpluses and shortages have an incredibly high cost.
Imagine two countries going to war – Country A and Country B.
All of Country A’s generals get together and decide they need exactly 10,000 troops, 200 tanks, and 50 ships to ensure victory. Based on their intelligence of Country B’s capabilities, this should be exactly sufficient to win the war.
Rationality and economic efficiency would dictate that they prepare exactly 10,000 troops, 200 tanks, and 50 ships. Anything beyond is simply incurring unnecessary costs.
But of course, this is a terrible idea. If anything goes wrong – a battalion gets stuck, a delay in training exercises, an underestimation of Country B’s forces – the war is lost. A shortage of troops and equipment will lead to a catastrophic result.
As we know from our article on the ‘False Confidence of Precision’ – when it comes to predictions, we can be precise, but we can’t guarantee that our precision is accurate.
As such, if the cost of missing the mark is high, it’s absolutely rational to build a buffer around your estimates. The higher the cost of being wrong, the bigger the buffer.
Perhaps it’s no surprise that countries build up and deploy militaries in a way that might seem overdone. If the cost of underestimating is sufficiently large, it’s much better to err on the side of too much than to risk even a minute possibility of too little.
This is rational – there are costs associated with surpluses, sure. But there are also costs associated with shortages. And we know that we can’t perfectly predict our Goldilocks equilibrium, so we may always end up with either one or the other.
Depending on the relative cost of either a surplus or a shortage, individuals, companies, and countries will manage their risk accordingly. They’ll create buffers to insulate themselves against the worst outcomes, based on the perceived probabilities and risks associated with these outcomes.
So, what is takeaway from our strawberry surpluses and wartime strategies? It’s not that the Goldilocks principle of perfect equilibrium is wrong, or that efficiency is a bad goal. Rather, it’s an acknowledgment that in our unpredictable world, perfect efficiency is often just a fairytale.
Information is never perfect, and there will always be costs. The key is to look at the potential costs on both sides of the equation and build buffers to insulate yourself against the outcomes you find most troublesome. It’s about finding that sweet spot between running a tight ship and having a life jacket, just in case.
So next time you’re faced with a decision, big or small, consider where you might need a buffer. It might not be as satisfying as finding that ‘just right’ porridge, but it could save you from a run-in with some disgruntled bears.
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