Master of Puppets – who really controls the laboratory?

Paweł Piotrowski
Feb 19
5 min read

(about automation, savings, and the boundary between control and convenience)

Automation was meant to set us free. From variability. From manual errors. From the unpredictability of the process. It was supposed to bring standardisation, repeatability, and—especially in times of tight budgets—clear savings. Yet today, more and more laboratories find themselves in a paradoxical position. On the one hand, they are fighting to reduce the cost per individual test. On the other hand, they are investing in the most technologically advanced platforms, which in the long term significantly increase the operating costs of the facility.

And the question arises: Is automation our tool? Or are we becoming part of its business model?

Savings versus modernity

In presentations, everything looks simple:

✔ Higher throughput

✔ Fewer manual errors

✔ Lower variability

✔ Better standardisation

It all sounds rational, yet the problem is that modernity is often not synonymous with savings. Modern solutions very often mean:

A closed reagent ecosystem,
Dedicated packaging and reagents,
No possibility of using alternative materials,
Limited protocol flexibility,
High switching costs to another platform.

At the purchasing stage, everything seems rational. In a 3–5 year perspective, it turns out that the operational budget is increasingly burdened by running costs, absurd service expenses, and the pricing policy of a single supplier. Automation was supposed to stabilise the process. It does not always stabilise the finances.

The illusion of control

Automation provides a sense of security. “The system is validated.” “The protocol is optimised.” “Human error has been eliminated.” This is supposed to be reassuring—but does it really mean we control the process? Increasingly, when reviewing antibody offers, I encounter the question: “Is it validated for this or that platform?”

And then another question arises: What happened to internal validation? Have we forgotten how to perform it? A manufacturer’s validation does not release the laboratory from responsibility for its own process—especially in an environment where platforms are dynamic, changing, updated, and working conditions differ between centres. If even original, dedicated antibodies can produce suboptimal results in a specific laboratory, can we truly trust without reflection that validated means perfect under all conditions?

In closed platforms, more and more often:

Only specific reagent packaging can be used,
Parameters cannot be freely modified,
Alternative solutions cannot be introduced without risking loss of warranty,
The user has limited influence over key workflow elements.

From the manufacturer’s perspective, this is safety and standardisation. From the laboratory’s perspective, it is a limitation of autonomy and development. Control of the process shifts from the user to the system. Moreover, the system manufacturer does not bear responsibility for the clinical result. Responsibility always remains with the laboratory. And when control becomes limited, one thing remains: TRUST. The only question is whether, in diagnostics, trust can replace validation.

Brand as a substitute for data

Comparative analyses of automated systems show that high brand recognition does not always translate into a clear qualitative advantage. In some assays, agreement—even within a single platform—can be significantly lower than we would expect from a gold standard. Quality is not given once and for all. It is not a certificate assigned to a logo. It is a process that requires continuous verification.

In economics, there is a phenomenon known as the brand premium. A strong market position reduces competitive pressure. And less pressure often means a slower pace of change and improvement.

Not because someone is acting in bad faith. But because market mechanisms allow it. If a system is perceived as the standard, users question it less frequently. And the fewer the questions, the fewer the incentives for development. Then it is worth asking:

Who, hand on heart, has recently analysed the results of independent studies concerning a “trusted” supplier?

Who has compared the actual quality of results obtained on devices from a “well-known company” with alternative platforms?

Not marketing brochures. Not sales presentations. Independent data. Do we regularly verify:

reproducibility between laboratories?
inter-platform agreement?
long-term stability of results?

Or do we assume that since a system is popular and present in most facilities, its quality is constant and unquestionable? In medicine, that is dangerous. Because trust cannot replace data. And a brand cannot replace control.

The cost that is not visible in the tender process

Automation makes sense when it truly:

✔ improves diagnostic quality

✔ reduces variability

✔ stabilises results

✔ lowers the total cost in the long term

But the cost of a system is not just the price of the device. The purchase price is only the beginning of the story. The real cost starts later.

It includes:

The cost of dedicated reagents,
The cost of consumables,
The cost of service and downtime,
The cost of lost flexibility,
The cost of dependence on a single supplier,
The cost of losing negotiating power.

In a tender, you see the price. You do not see the total cost of ownership. You do not see the cost of exiting the system. You do not see the barrier to change. You do not see the risk that in a few years every price increase will be a unilateral decision. A facility that unreflectively strives for the most modern solution may, after a few years, find itself in a situation where:

Every price increase directly impacts the budget,
Changing the system becomes economically unrealistic,
The development of new tests is limited by platform compatibility,
Innovation becomes impossible without the manufacturer’s approval.

At that point, automation becomes a dependency. And dependency in medicine—especially financial and technological dependency—always comes at a cost. Because the system that was meant to provide an advantage may become a limitation. And the automation that was supposed to be support may turn out to be a muzzle.

Is it worth it? Yes. In many cases, automation is necessary:

With a growing number of tests.
With staff shortages.
With the need for standardisation and quality control.

But only when:

We understand the process we are automating,
We analyse the total cost of ownership,
We have real control over the parameters,
We verify quality based on data, not reputation.