I spent a day at a company’s flagship diagnostics lab in the US recently. On earnings calls, "automation" and "central labs at scale” are frequent buzzwords, so it was intriguing to see inside this vast 150,000ft² operation of highly choreographed logistics and robotics, which runs 24/7 and processes over 100,000 patient samples daily.

Key takeaways

• The lab has scale and complexity that is genuinely hard to replicate.

• Automation is embedded in the core workflow and is not just a marketing term.

• Culture and people are more important than many would realise in a company that looks ‘commoditised’ from the outside.

The physical scale and footprint

The lab is large enough that visitors are shown a drone shot to ensure they don’t get lost. It’s housed in a renovated paint factory, but a shiny new extension has been added, as part of a seven-year capital expansion project, and a separate warehouse.

The company serves a huge geographic region and employs over 800 people, including MDs and PhDs. Its services range from routine blood tests to specialist oncology and infectious disease work.

On top of standard state certifications, the site is ISO 15189 accredited – a voluntary, higher bar for lab quality systems. This is not just regulatory decoration but a layer of process discipline in a high-volume environment.

Supporting the lab are approximately 700 couriers who make 300,000 pickups daily across the region. There are also 600 patient service centres that feed into a network of smaller “branch labs”, which consolidate samples before sending them to the lab overnight.

As an investor, it’s clear that this is a scale game. Seeing the actual mechanics makes it tangible.

How a sample moves through the system

Walking through the lab, I watched patients’ blood samples move from collection to result and storage. Particularly intriguing was watching newly-arrived samples being unloaded onto conveyor belts and fed into automated loaders. This is where the lab shows its technological sophistication. Instead of technicians handling each sample, an automated system takes over. Samples are split into smaller portions for different types of tests, including immunoassay, thyroid, and oncology markers. The system tracks how much of each sample is used and what remains.

Once sorted, instrument-ready racks of samples are routed to different areas of the lab where machines run tests. For most patients, results flow directly from these machines to computers to a hospital or clinic, without any human intervention.

The lab runs this process around the clock; about 40% of staff work night shifts, which is the heaviest processing window as branch shipments arrive.

This is where economics show up: once the fixed cost and infrastructure are in place, “the next test” on an existing sample is extremely high margin.

Driving better outcomes

Automation and scale deliver real benefits beyond just processing more samples. Samples are handled in a systematic way, with machines doing the splitting and routing, and thus there are fewer opportunities for human error. Samples don’t get mislabeled. Mistakes in volume measurements are eliminated.

Error and incident metrics, such as lost specimens and accidents, are tracked carefully, and over time, data has shown meaningful improvements. This can be compared to smaller hospital labs where there are more manual steps and room for error, as well as lower automation and staff who tend to be more generalist. At this lab it’s the opposite: a high fixed cost but very low marginal cost per additional test, with lower error rates.

This creates a real competitive advantage and is a big piece of the moat: lower error rates plus faster turnaround means better economics in my view.

Culture and workforce: not just robots

Here’s where the story gets interesting. One might think "automation" means the lab has replaced people with machines. That’s not what’s happened. 800 people are employed because there’s still plenty of work – just different work.

There is actually a shortage of lab technologists across the US, so the lab is investing in training. It works with local colleges and universities to develop talent pipelines and runs its own training programme.

Importantly, leadership is thoughtful about culture in what is a 24/7 operation. There are specialist roles, work-life flexibility is emphasised, and there are visible employee resource groups and cultural events. Turnover at the company is reportedly below industry average, which is significant in a sector facing widespread staffing challenges.

Management’s philosophy is clear: automate repetitive, unpleasant, low-skilled tasks, then move people toward higher-value work, such as troubleshooting, quality control, and complex areas that require judgment. It’s not about replacing people; it’s about enabling them to do more interesting work while machines handle the drudgery.

“Next-Gen” lab tech

The tour wasn’t just conveyor belts. Pockets of “next layer” tech were visible in AI-assisted slide reading and an increasing use of software and decision support that can pull clinical data from EHRs, suggest appropriate tests based on comorbidities and guidelines, and help doctors avoid under- and over-testing.

Again, this isn’t just cool tech – it’s a way to drive more tests per accession (richer menus for the same patient) and lock in integration with hospital systems, making the lab harder to displace.

What this means as an investor

My views on this company visit:

• Scale creates real competitive advantages: the combination of volume, automation, and logistics isn’t easy to replicate, and economics get better with each marginal test, once infrastructure is in place.

• Automation is more about quality and throughput than headcount cuts: lower error rates, faster results, and the ability to grow without proportionally adding staff is where the margin leverage comes from.

• Test intensity is visible in how the lab runs: the workflow is set up to easily add more tests from the same sample (e.g. a lipid patient also getting apoB, Lp(a), additional markers). That’s the “tests per accession” story, operationalised.

• People and culture matter enormously: building this kind of operation isn’t just about installing equipment; it’s about retaining skilled technicians in a challenging 24/7 environment through thoughtful management and career development.

Reading the quarterly earnings presentation might suggest this is just operational detail. Walking through the lab makes clear that the operating model – scale, automation, and people working together – is the actual strategy.