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We’ve spent the last three months preparing our State of the Industry report.
Interviews. Surveys. Implementation stories.
At times, it looked a bit like this 👇
The full report will be available soon and we’re still welcoming new responses. So if you’d like to participate you can do so via this link (only takes 4 minutes): https://1lims.typeform.com/labstatesurvey
While reviewing the survey and interview data, we came across an insight we wanted to share with you right away.
Across conversations with lab automation experts, consultants, and lab leaders, one obvious pattern appeared:
The cost of implementing a LIMS is rarely just about the software.
When labs plan a LIMS project, they usually budget for:
Patrick Courtney, who co-leads a European working group on analytical laboratory robotics and AI for science, says that the technology is only a fraction of the total effort:
“Buying a LIMS is usually straightforward. Making it work inside your specific lab environment is where things get hard.”
In some cases, a lab might invest around €100K on new technology, but spend €200-300K on change management.
No, it’s not just employee training.
It includes:
In larger organizations, the more stakeholders involved, the harder change becomes.
Adoption depends less on features, and more on incentives, ownership, and internal champions.
Until your workflows, formats, and interfaces are standardized, every integration becomes custom work. It means:
That’s why Gerard Ipskamp, a lab digitalization consultant, advises taking a step back before speaking to vendors.
Make sure your processes are optimized, stable, and actually executed as described — not just on paper.
Mr. Ipskamp points out that many LIMS projects struggle because labs begin defining requirements with the vendor already in the room — and before they fully understand their own workflows.
Before adopting a LIMS, ask yourself:
⚫ Are our workflows standardized across departments?
For example: Do QA, production, and R&D follow the same sample intake steps? Is result approval handled the same way everywhere? Or does each department do it “slightly differently”?
⚫ Are barcode formats and data structures aligned?
For example: Do all instruments read the same barcode format? Are sample IDs structured consistently? Are units of measurement standardized (e.g., mg/kg vs ppm)?
⚫ Do we know where workarounds exist?
For example: Are technicians exporting CSV files into Excel? Are results manually copied between systems? Are there unofficial templates or shadow spreadsheets in use?
⚫ Do we know every system that needs to exchange data with the LIMS?
For example: How many instruments need to connect to the LIMS? Are they new or legacy devices? Do they support standard interfaces, or require custom connectors? Which other systems need data exchange (ERP, MES, reporting tools)?
Our full State of the Industry report will go deeper into where LIMS projects stall, and what the most successful labs do differently.
More soon. Stay tuned.
P.S. Want to dive deeper?
👉 What labs can learn (and can’t) from automation in other industries: A practical perspective on where industrial automation models apply, and where lab reality is different.
👉 LIMS software costs: how much should you expect to pay? We break down LIMS pricing and what drives system costs based on the example of 1LIMS.
👉 How to build a realistic path to a fully digital food and beverage lab: Together with METTLER TOLEDO, we created a practical whitepaper for labs planning digital transformation without wasted time or budget.
Happy & safe lab work!
❤️ Greetings,
1LIMS Team
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