Why do companies try to automate the wrong processes first?

Automation is no longer a competitive advantage, but a baseline expectation. Even so, many automation projects fail for reasons that are not obvious at first.

For most companies, the question is not whether they introduce it, but what exactly they automate and when.

This is exactly where the real difficulties begin.

One of the most common automation mistakes is that companies do not improve well-functioning, transparent processes, but try to accelerate operations that are already distorted. At first glance, this seems like a logical step: if something is slow or requires too many resources, we automate it.

In reality, however, this is one of the fastest ways for an automation project to move in the wrong business direction, even before it is able to create real value.

Operations do not collapse, they just begin to distort

In most organizations, there is no single point where everything suddenly breaks. The system appears to be functioning. Tasks are completed, and customers are served.

Still, there is a point where something begins to change.

Not visibly, but almost imperceptibly. More and more manual checks appear, more and more alignment happens around the same things, and more and more situations occur where something has to be resent, clarified, or simply reviewed once again.

This becomes especially visible where multiple systems and actors are connected, for example in a call center's customer handling or in logistics order processing.

At the same time, more and more time is spent on coordination, and less and less remains for actual decisions.

This is not the kind of issue that becomes immediately visible. It is much more a slow distortion that over time begins to affect the entire system.

And this is exactly the point where most organizations begin to move in the wrong direction without noticing it.

The misunderstood problem: is the system really slow?

When these symptoms appear, the leadership reaction is almost always the same. Something has to be done about the slowness, and a conclusion is reached very quickly: this needs automation.

This is completely understandable at first. Slow operation is frustrating, manual work is costly, and after a while it does indeed become a limitation to growth.

However, this diagnosis leads in the wrong direction.

Because in most cases, the problem is not that the system is slow, but that it is not clear how it actually works.

And this is a completely different type of problem.

What you automate, you amplify

Automation does not fix problems. It amplifies them instead.

If a process is clean, it truly makes it more efficient. But if it is flawed from the start, it does not correct it, but makes it faster and often less visible.

This is the point that many organizations only understand afterwards.

When errors do not decrease, but appear faster. When more and more exceptions have to be handled, more and more manual control has to be rebuilt, and at the same time the system becomes less and less transparent even for those who use it every day.

This is when the sentence appears that almost everyone knows:

"This is not what we expected from automation."

What actually makes a process bad?

A process does not become bad because it contains many manual steps. This in itself is not yet a problem.

The real issue begins when it is not clear who is responsible for what, when it is not clearly defined when a task is considered complete, and when information becomes distorted at multiple points before it reaches the right place.

In such cases, decisions are often not made where they should be, but later, in a different context, or based on incomplete information. The system increasingly starts to rely on exceptions rather than clearly defined rules.

At this point, the process is no longer simply inefficient, but becomes unpredictable.

And even more importantly, these problems are not technological in nature. This is exactly why they cannot be solved by technology alone.

A typical situation where the system gets faster, but operations get worse

Imagine an operation where a task passes through multiple systems and multiple people. At each step something happens: data is transferred, a check takes place, a decision is made, and then the process continues.

The goal of automation in this case is clear. Fewer manual steps, faster throughput, lower resource requirement.

The automation is implemented, and at first glance it works. The process does indeed become faster.

However, at the same time something else also happens.

Errors do not decrease, but move through the system faster. They are detected at fewer points, so they appear later and with greater impact. Handling exceptions becomes more difficult, and the team has less and less visibility into what is happening in the background.

After a while, the question is no longer whether the operation became faster, but how much control remained.

The result is not a more efficient system, but an operation that deteriorates faster than before.

Why do companies keep falling into this again and again?

Because automation is a comfortable answer.

It produces results quickly, it is visible, and it is easy to measure. In the short term, it creates the feeling that the organization is moving forward and that real progress is happening.

However, there is one thing it does not force: real organizational decisions.

Rethinking a process, on the other hand, is a completely different kind of task. It brings structural problems to the surface, generates conflicts, clarifies responsibilities, and often requires changes at the operational level.

This is difficult, and often explicitly uncomfortable.

Automation, by contrast, appears as progress, even when in reality it does not solve anything.

The real order most companies skip

A functioning automation does not begin with technology, but with understanding the operation.

This is not a theoretical step, but a very concrete process. It means that we clearly see what is happening in the system, understand where and why information becomes distorted, and are able to separate the steps that do not actually create value.

At the same time, it becomes clear what we truly want to optimize, and what is merely a consequence of the current operation.

Only at this point does automation make sense.

In every other case, automation is not a solution, but an error that the system itself begins to reproduce.

The question that decides everything

Before an organization begins to automate, it is worth asking one single question.

If we make this faster now, will things actually become better, or will the same errors simply appear sooner?

This difference often does not depend on technology, but on how well we understand our own operation.

If there is no clear answer to this question, then automation is not yet the next step.

The real role of automation

Automation is not valuable because it replaces work, but because it makes better operation possible.

However, better systems cannot be built on bad foundations. If the process is not clean, it cannot be fixed with technology, it can only be made faster.

So in the end, the real question is not what tool we use, but how well we understand our own operation, and whether we are willing to truly face it.

And this is the step most organizations ultimately skip.