By Kevin Ghiasi, VP of Global Alliances & AI Platform Strategy
I’ve spent years working directly with large pharmaceutical and life sciences organizations and their scientific equipment environments. This is the one question I keep getting:
What’s good utilization?
Is 20% bad? Is 40% good? Should an instrument be running 70% of the time? My answer today is very different from what it would have been several years ago.
Years of lab asset utilization monitoring have taught me there isn’t one number. And one of the biggest mistakes we can make in R&D is assuming higher utilization automatically means better utilization. A utilization rate is a signal, and what it’s telling you depends on what the instrument is for.
Why Doesn’t R&D Equipment Run Like a Production Line?
I’ve learned repeatedly from working with scientists, laboratory teams, modality managers, and the people responsible for these equipment portfolios that R&D is episodic.
Research isn’t a production line. Your steps look more like:
- Design an experiment
- Prepare samples
- Run equipment
- Analyze results
- Change the experiment
- Do it all again
I’ve seen very significant peaks in equipment use, but they aren’t sustained. That matters. Two instruments can post the same 12% annual average while one runs steadily all year and the other spikes over 50% during a single campaign. An instrument sitting at 20% utilization isn’t necessarily underutilized, and another running above 50% isn’t necessarily optimized.
That 50%+ instrument may be telling you that the scientists don’t have enough flexibility for maintenance, repeat testing, priority work, or unexpected demand.
How Does Company Size Change What Good Asset Utilization Looks Like?
Smaller companies taught me something else: If you’re a smaller biotech and you have one $250,000 analytical instrument, you’re going to use the heck out of it. You have to.
A global pharmaceutical company with thousands of instruments has a completely different problem. Some of its capacity is heavily used, some is specialized, some provides redundancy, and some supported programs that have changed. And sometimes equipment in one part of the company is sitting unused while another part of the company is preparing to buy more.
That’s where this gets interesting.
What Should Lab Asset Utilization Monitoring Tell You?
My utilization ranges are simple:
| Below 5% | Very Low |
| 5-15% | Low |
| 15-30% | Moderate |
| 30-50% | High |
| Above 50% | Very High |
Those aren’t grades. They’re signals telling me what question to ask next, and that’s how we built the utilization logic into Elemental Machines’ Analytical Equipment Analyzer (AEA)*, an agent on the Elemental Alloy™ Agentic AI Platform.
What Does Zero Utilization Mean?
Zero is zero. If I’ve measured an instrument correctly, have sufficient coverage, and it has no recorded activity over a meaningful period, I want to know why.
I’m not saying get rid of it. Maybe it’s critical backup equipment. Maybe there’s a specialized assay. Maybe a program starting next quarter needs it.
Fine. Document that so people are aware and continue with the analysis.
Do You Already Own the Capacity You’re About to Buy?
Here’s the scenario that gets me excited.
One building wants three new mass spectrometers, while another part of the organization has comparable equipment showing zero use. Before spending another $500,000 or $1 million, wouldn’t you want to know whether you already own the capacity?
Maybe you can’t move it. Maybe the methods aren’t compatible, the configuration isn’t right, or qualification makes it impractical.
Ask the question anyway.
What Should Pharma R&D Optimize Instead?
I’ve spent enough time inside large pharmaceutical equipment environments to believe this is where the industry has a tremendous opportunity. And it has very little to do with squeezing another five percentage points of utilization out of every instrument, creating prettier dashboards, or trying to make R&D behave like manufacturing:
- Find the right equipment
- Put it in the right place
- Preserve the capacity scientists need
- Stop buying capacity you may already own
That’s what equipment utilization means to me now, and it’s a big part of why we built AEA to treat lab asset utilization monitoring as the first step in a capacity decision.
*Patent pending
FAQs
There isn’t a single target. R&D demand comes in peaks around experiments and programs, so a rate works best as a prompt for review. Elemental Machines groups measured utilization into five bands, from Very Low (below 5%) to Very High (above 50%), each tied to a different question.
No. Sustained use above 50% can signal a capacity constraint, leaving scientists too little room for maintenance, repeat testing, and priority work.
Utilization is active hours divided by available hours in the same period. The window you choose determines the answer. Twenty run hours is 11.9% of a 168-hour calendar week and 50% of a 40-hour staffed week.
Only after review. Verified zero use puts an asset in a priority review group. Owners then document whether it provides backup, supports a specialized assay, or if it is needed for future work. They also check whether it could meet a need elsewhere before anyone buys new equipment.
Element-U sensors capture instrument activity. AEA applies the utilization bands to that measured data and reviews it alongside demand peaks and idle periods.