When “Efficiency” Becomes a Religion: Why the More Efficient Your Company Is, the More Dangerous It Can Be
Hello everyone, I’m your financial journalist friend. Today, we’re going to discuss a very insightful article from Havenlon Labs. This article doesn’t talk about specific stock price movements or analyze the financial reports of any particular company; instead, it raises a question that sends shivers down the spines of every worker and manager: Why do today’s businesses seem to treat “efficiency” as an unquestionable doctrine?
In simple terms, the core argument of the article is this: Efficiency was originally a tool, but now it has become an end in itself. When a company focuses on achieving extreme speed and cost-cutting by eliminating things that seem like waste, such as safety measures, buffers, and manual checks, it doesn’t become stronger; it becomes extremely vulnerable. Especially in the age of AI, this kind of “frictionless” efficiency can amplify mistakes at lightning speed, with no one to put the brakes on.
To make this easier to understand, I’ll break down the article into five key points and explain them in plain language.
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1. The Order Is Reversed: First, Ask “What to Do,” Then “How to Do It”
In normal business logic, there is a sequence to things:
- The First Question (Purpose): What problem do we need to solve? What value do we want to provide to our customers?
- The Second Question (Method): How can we accomplish this with the least amount of money and in the shortest amount of time?
Efficiency should be a tool used to answer the second question.
However, many companies have reversed this order. They no longer ask why a certain process exists; instead, they ask why it can’t be done faster, or why resources aren’t being fully utilized.
It’s like going to a restaurant for a meal:
- Normal Logic: I want a good meal (purpose), so the chef slowly cooks the soup (method).
- Efficiency-First Logic: Chef, why haven’t you served the food yet? Can you compress the cooking time to one minute? If not, is it because you’re not efficient enough?
When “efficiency” becomes the sole criterion for everything else—quality, safety, even the time people need to think—those aspects have to “prove their worth” to efficiency. You have to justify: “Why am I so slow? Why do I need to take a break? Why do I need to check?” If you can’t provide a clear explanation, you’re considered inefficient and are likely to be eliminated.
Conclusion: When efficiency becomes a “religion” rather than a tool, it no longer needs to be proven right; it becomes the judge that evaluates all other values.
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2. The Closed-Loop Trap: When Something Goes Wrong, the Blame Falls on “Inadequate Execution”
Any absolutized value has one characteristic: it doesn’t allow for questioning.
In companies that prioritize efficiency, if an accident occurs due to the pursuit of speed (such as a server crash, data loss, or employee error), management usually doesn’t reflect on whether there’s something wrong with the goal of efficiency itself. Their reaction is often: “It seems our automation isn’t thorough enough, our processes aren’t optimized enough, or we don’t have enough people.”
This creates a terrifying closed loop:
1. To improve efficiency, redundant processes are cut out.
2. The system becomes more vulnerable, leading to small problems.
3. To solve these problems, more “inefficient” steps are eliminated in pursuit of further optimization.
4. The system becomes even more fragile, accumulating greater risks.
It’s like a racing car with its seatbelts, airbags, and brakes removed. If it crashes, the driver doesn’t say, “There’s a design flaw in the car”; instead, they say, “My driving skills aren’t good enough; next time I’ll drive more carefully.”
Conclusion: When an organization loses the ability to question the efficiency goal itself, risks grow quietly with each optimization, until they finally explode.
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3. The Dashboard Deception: Green Numbers Mask Structural Crises
Modern businesses have many “rituals” such as KPIs, OKRs, weekly reports, quarterly reviews, and colorful data dashboards. These tools are supposed to help managers see the reality. But over time, they end up defining reality:
- As long as the dashboard shows green numbers, everyone thinks everything is fine.
- As long as growth rates are rising, internal issues can be ignored for now.
- If server utilization goes from 40% to 95%, everyone celebrates good management.
But there’s a big misconception: High utilization doesn’t equal high safety.
For example:
- 40% Utilization: It’s like having two buckets of water at home, using only one most of the time. If the pipe bursts, you still have a backup, so life isn’t affected. This is “redundancy,” which may seem wasteful but provides a sense of security.
- 95% Utilization: It’s like having only one bucket of water left, and if the pipe bursts or guests suddenly arrive, you’re in trouble.
In industries like aviation, finance, and data centers, redundancy is like insurance. It may seem unnecessary and costly, but it’s the last line of defense against disasters.
Conclusion: When all the numbers look good, it’s often the most dangerous time, because the real world doesn’t stop happening just because your dashboard shows green.
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4. The Inversion of the Burden of Proof: Those Who Want to Go Slower Must Prove Themselves
This is the most striking point in the article.
In the language of efficiencyism, terms like “redundancy,” “waiting,” “manual checks,” and “low utilization” are inherently negative, seen as signs of management failure.
As a result, there’s an asymmetrical power structure:
- If an engineer suggests adding a manual check to prevent errors, they have to explain the reasons. The manager will ask, “How much will this cost? How much speed will it slow down? Is there a more automated solution?”
- If the manager decides to remove that check and go with automation, they don’t have to explain, as it aligns with the ideals of progress and efficiency.
This leads to a situation where those who oppose efficiency have to bear the burden of proof. Risks don’t come from a single major mistake; they come from hundreds of small, seemingly reasonable optimizations:
- One less check, no problem.
- A little less inventory, no problem.
- One less manual review, no problem.
Each step passes review and makes the system more efficient. But when these optimizations are accumulated, a system that was once resilient and risk-resistant becomes one that’s extremely efficient but also extremely fragile. It’s like pressing a spring to its limit; it looks strong, but a little more pressure and it breaks.
Conclusion: The most dangerous thing is not speed itself, but the fact that no one can defend slower approaches. When “slowness” is considered a flaw, the system loses its ability to correct itself and buffer against risks.
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5. The Ultimate Challenge of the AI Era: Who Has the Power to Put the Brakes?
Finally, the article looks at the hottest topic of our time: AI. For the past century, humans have been striving to eliminate friction:
- Taylorism eliminated wasted movements.
- Assembly lines eliminated waiting times.
- The internet eliminated transaction delays.
- AI agents are eliminating execution delays.
In the past, even approved actions required human understanding, operation, and confirmation. People might hesitate, asking, “Is this really necessary?” This “friction” served as a natural filter, catching many mistakes.
Now, AI agents are tireless, never complain, and respond in milliseconds. They can perform hundreds of actions in a day.
- Past Risks: A person might make 10 mistakes a day, most of which are caught before they cause problems.
- Current Risks: An AI agent can perform 100,000 actions a day, and even if the error rate is 0.01%, 10 mistakes will still occur. And these mistakes are amplified immediately.
The biggest risk with AI isn’t that it’s not smart enough, but that it’s too fast. In the past, mistakes took time to spread, giving you time to react. Now, mistakes can affect reality instantly.
So, in the future, companies need to distinguish between “automation” and “manual processes” based on whether the actions are reversible or irreversible:
- Reversible: Mistakes can be corrected; these can be fully automated.
- Irreversible: Money can be transferred, drugs can be administered, data can be deleted, machines can be started. These actions must have some form of “friction” (safety mechanisms).
Conclusion: We may need to reinvent “friction” in some aspects. For example, double-checks in bank transfers, circuit breakers in the financial market, and dual-authorizations for critical operations are forms of friction that provide safety.
These “troublesome” elements are not inefficiencies; they are safety valves.
In the AI era, the most important question is no longer “how to make the system smarter,” but: When a highly intelligent, automated system is running, who has the power to stop it? This power can’t rely solely on individual caution (since people can also be tired or make mistakes); it must come from structural design—a separate, independent mechanism responsible for saying “no.”
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Conclusion
This article isn’t advocating against efficiency or returning to a less efficient past. It’s a reminder that efficiency is a tool, not an end goal. A mature organization’s most important ability is not to know how to be faster, but to know when to stop being fast.
In an era where AI makes everything seamless, we need to be wary of things that seem like waste but actually protect the system. The most dangerous moment for a system is not when it’s chaotic, but when it runs smoothly, without any resistance, and no one dares to say “stop.”
Efficiency has become a religion because we’ve forgotten that it’s just a tool.