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Around 70% of transformation initiatives fail to achieve their intended goals, often because organizations underestimate the human side of change.¹​

Modern research moves fast, but most lab systems haven’t kept up. Many teams still rely on a patchwork of spreadsheets, legacy databases, and paper records to manage experiments, samples, and results. These hybrid processes may feel familiar, but the truth is, they slow collaboration, obscure data, and make it hard to scale new discoveries.

Recognizing the need for change is one thing. Making that change successfully is another. For many scientists and lab managers, the idea of replacing long-established workflows feels daunting, especially when research can’t simply pause for a system rollout.

That’s why effective change management is now one of the most critical success factors in digital transformation. When organizations embrace change management, it builds alignment, trust, and readiness, so scientists feel supported, not disrupted. In practice, change management is the structured process of guiding people through new ways of working, helping them understand, adopt, and sustain change. It’s about aligning leadership, communication, and everyday workflows, so digital transformation actually sticks.

This post looks at how research labs can navigate change with confidence. Drawing on real-world lessons from years of experience supporting digital transformation across the life sciences, it provides a practical framework for preparing your people, processes, and platforms for success.

The hidden costs of hybrid research management

When “good enough” stops being good enough

The typical modern lab runs on a hybrid model: a mix of spreadsheets, paper notebooks, shared drives, and partial software solutions stitched together over time. Each tool might serve its purpose, but together they create a patchwork that’s fragile, inconsistent, and hard to maintain. Most research teams know their current systems could work better, but few realize just how much those small inefficiencies add up.

These hybrids often evolve organically, not strategically. A new spreadsheet here, a manual tracker there, each one solving an immediate need but introducing another point of failure. What starts as flexibility quickly turns into friction. Data becomes siloed. Version control breaks down. And scientists end up spending more time finding information than generating it.

The cost of manual workarounds

The more manual workarounds they invent, the more dependent the lab becomes on individual memory and goodwill. When staff change roles or leave, vital knowledge disappears with them. Over time, this dependency creates not just operational inefficiency but genuine institutional risk.

Every disconnected process leaves a blind spot: for example, training logs that are stored separately from protocols, inventory spreadsheets that don’t match what’s on the shelf, or results that live only on one researcher’s hard drive. None of these gaps seem serious in isolation, but together they quietly erode productivity and scientific confidence.

Reproducibility at risk

Besides wasting time, fragmented workflows also undermine data integrity and reproducibility. When experimental records are split across formats and systems, it’s nearly impossible to reconstruct a complete, verifiable picture of what happened. In regulated or collaborative environments, that lack of traceability can delay publications, compromise partnerships, or raise questions during audits.

It’s a problem hiding in plain sight: a lab might feel efficient day to day, yet still struggle to defend its work when it matters most.

A system problem, not a people problem

When scientists fall back on spreadsheets or paper, it’s rarely resistance to technology but rather a sign that the tools around them don’t match how they actually work. Hybrid systems put the burden of integration on people instead of infrastructure. Change management starts by reversing that equation: building systems that adapt to scientists, not the other way around.

That’s why modernization is about designing connected processes that make great science easier to do, record, and trust. Not necessarily by forcing new tools and technologies into a lab. These challenges are symptoms of systems built around tools, not people. To move forward, labs need to understand why change feels so difficult, and what it takes to make it last.

Why research labs resist digital change

Change is rational, until it’s personal

Change in research settings isn’t abstract; it touches every notebook, workflow, and habit that scientists depend on. For many, those habits have been built and refined over years of experience. Replacing them overnight can feel unsettling, even when everyone agrees it’s for the better.

Change becomes personal the moment it reaches the bench. Scientists worry about losing momentum. Lab managers worry about disruption and downtime. Leadership worries about cost and return on investment. When those concerns go unaddressed, progress stalls, not because the technology isn’t ready, but because people aren’t.

The comfort of the familiar

Hybrid systems persist because they work “well enough”. A shared drive might not be ideal, but everyone knows where things are. A spreadsheet might be fragile, but it’s familiar. For scientists working under time pressure, familiarity feels safer than transformation.

But comfort can be costly. Each manual process that saves time today compounds risk tomorrow. As new data types, regulatory expectations, and collaborators enter the picture, the cracks widen, until managing information becomes a project in itself.

The human factor in success

According to McKinsey, transformations are nearly four times more likely to succeed when organizations define clear roles and hold leaders accountable for managing the change.² The difference lies in the people strategy: when leaders communicate the “why,” involve influential team members early, and celebrate small wins, adoption follows naturally.

Transformation succeeds when scientists feel ownership of it, not when it’s handed down to them. That’s where structured change management comes in. Whether supported by a partner like SciSure or led internally, the principles are the same and they begin with building a culture that’s ready for change.

7 steps for building a change-ready research culture

Turning intention into adoption takes structure. These seven steps outline the habits and behaviors that make digital change stick in real research environments.

1. Lead with a shared “why”

Scientists change how they work when the reason is clear and owned by them. Frame the transformation in scientific terms: better traceability, faster collaboration, stronger reproducibility. Not as an IT project. McKinsey's research found that even transformations declared successful capture, on average, only about two-thirds (67%) of their potential financial value, while all other companies capture just 37%.³ Their work also points to the people side as decisive: workforce-led implementations proved five times more sustainable than those driven from the top.⁴

2. Put influential scientists at the center

Change moves fastest when respected peers help design and champion it. Research shows transformations are four times more likely to succeed when influential employees are involved early and visibly.⁵ Identify those voices, invite them into configuration and pilot design, and let them demo wins to their colleagues.

3.  Treat adoption as a discipline, not an afterthought

Change management is a structured way to help people move from old habits to new systems with the same rigor as a scientific process. Define ownership, milestones, and feedback loops early, then measure and refine. McKinsey found that defining clear roles, so people at every level know what they are responsible for after the change, makes organizations 3.8 times more likely to succeed in a transformation.⁶  

4. Communicate to build trust, not just awareness

Change fails when communication stops at announcements. Scientists need clarity on what is changing, why it matters, and how it affects their work. The data backs this up: McKinsey found that when an organization clearly communicates the desired outcome before a new solution launches, it is 3.5 times more likely to report a successful transformation. The same research found roughly half of organizations succeeded when the rollout timeline was communicated clearly, compared with only 16 percent when it was not.⁷

‍5. Design training around real work

Scientists learn best when training feels relevant to their daily routines. Replace generic tutorials with short, role-specific sessions built around actual lab tasks: creating a protocol, logging a sample, or updating inventory. Context builds confidence faster than theory. The payoff from doing this thoroughly is steep. In McKinsey's research on skill-building programs, organizations that applied all nine of the practices it identifies as critical reported a near-certain success rate, compared with about those that applied only two or three.⁸

6. Pilot, prove, then scale

Start with a scoped pilot (for example, an electronic lab notebook plus inventory in one team), capture measurable wins, and expand. McKinsey found that organizations are three times more likely to report a successful transformation when they use piloting and rapid prototyping to surface the new skills people will actually need, because real use reveals gaps that planning alone misses.⁹

7. Measure what matters, and review often

Define a small set of adoption metrics that scientists care about (for example, time to find data, percentage of protocols with full lineage, sample handoff time). Schedule frequent, lightweight reviews and act on the findings. Restraint matters here: McKinsey found that most transformation programs try to track too many metrics, and fewer than 30 percent of the ones organizations claim to follow are actually used during the project.¹⁰

Practical pathways: How SciSure eases the transition

Digital transformation is a progression. SciSure’s approach to change management breaks the journey into three connected phases that let laboratories modernize steadily, maintain momentum, and prove value at every step. Each phase builds confidence by focusing on people first, then process, then technology.

Phase 1: Prepare and align

Change starts long before a new system goes live. SciSure’s implementation team works alongside scientists, lab managers, and leadership to understand how work really gets done and what “success” means for that specific environment.

In this phase, SciSure helps labs:

• Map existing workflows and identify bottlenecks that slow collaboration or traceability.

• Define clear success metrics that matter to both scientists and leadership (e.g., data retrieval time, version-control accuracy).

• Build a shared vision of change and select “champions” from within the research team.

• Configure the platform around actual scientific processes and terminology, ensuring familiarity from day one.

Outcome: Early alignment and trust. People feel heard, and the roadmap reflects reality.

Phase 2: Implement with confidence

Rather than a disruptive “big-bang” rollout, SciSure uses a focused pilot to demonstrate value quickly and gather feedback before wider deployment. Training and configuration happen in parallel so users learn in context and progress feels incremental, not overwhelming.

During this phase, the SciSure team:

• Launches a contained pilot (e.g., ELN + inventory) with measurable performance indicators.

• Embeds training directly into workflows so scientists learn by doing, not by sitting through generic sessions.

• Integrates existing instruments, databases, and third-party tools to maintain continuity and reduce friction.

• Establishes short feedback cycles so adjustments are made in real time, not after adoption stalls.

Outcome: Quick, visible wins that build confidence and create internal advocates for change.

Phase 3: Sustain and evolve

Once the platform is in daily use, SciSure focuses on strengthening adoption, measuring outcomes, and extending capability through new modules and integrations. This phase emphasizes:

• Regular adoption and performance reviews using live dashboards and engagement analytics.

• Iterative updates informed by user feedback and evolving lab needs.

• Expansion into additional capabilities, such as workflow automation, compliance tracking, or deeper analytics once the foundational workflows are stable.

• Ongoing support from SciSure’s customer-success team to maintain digital maturity and share best practices across sites.

Outcome: Continuous improvement, measurable ROI, and a culture that views change as part of scientific progress, not an interruption to it.

By guiding labs through these phases, SciSure transforms digital adoption from a disruptive overhaul into a controlled evolution. Scientists stay focused on their work, leadership sees real-time progress, and the entire organization gains the visibility and confidence needed to keep science moving forward.

Learn More: Institut Pasteur: A digital transformation with SciSure

Treating change like a scientific process

Digital transformation is an experiment in how people work together. Like any experiment, success depends on preparation, observation, and iteration. Change management provides that framework. It gives teams a structured way to test new processes, learn from results, and refine them until they stick.

For research organizations, that mindset shift is everything. When scientists, lab managers, and leadership approach change with the same discipline they bring to their science, adoption stops feeling like a project and starts feeling like progress.

At SciSure, we’ve seen that transformation firsthand. The labs that succeed are the ones that make change part of their scientific method: measured, repeatable, and constantly improving.

Because in the end, managing change isn’t about replacing what works. It’s about creating the conditions where better science can happen every day.

Ready to modernize your lab with confidence? Talk to our team and explore how SciSure can support your digital transformation: at your pace, on your terms, and with scientists at the center of every step. Contact us to start your change journey today.

FAQs: Common questions about change management

What does change management actually mean in a research setting?

In research, change management means helping scientists and lab teams adopt new digital ways of working without disrupting experiments. It’s about guiding people through the shift with clear goals, communication, and training so new systems enhance science rather than interrupt it.

Why do so many digital transformations in labs fail?

Most failures stem from human, not technical, issues. Labs underestimate the time and structure needed to help people adapt. Without a shared “why,” visible leadership support, and hands-on training, adoption falters, even if the technology works perfectly.

How can labs minimize disruption during digital transformation?

Start small and build confidence. Run a pilot on a single workflow, measure success, and expand gradually. Communicate frequently, act on feedback, and celebrate small wins. Incremental change builds momentum far faster than large, top-down rollouts.

What role do scientists play in successful change management?

Scientists are central to success. They’re the ones who understand how research really happens, so involving them in design, testing, and feedback ensures systems fit real lab life. When scientists see that digital tools reflect their needs, adoption happens naturally.

What’s the long-term benefit of structured change management?

Labs that treat change as a managed process, not a one-off project, see measurable gains: fewer data silos, faster collaboration, and stronger reproducibility. Over time, that consistency compounds, creating a lab culture that views change as a normal part of scientific progress.

Running a safe, efficient research program comes down to two things: how well you use your resources, and how well you use your time. When both of those live in paper binders, scattered spreadsheets, and people's heads, you spend your day fighting the job instead of doing it. That's why so many universities, research institutes, and companies have moved their EHS (Environmental Health and Safety) data into software that digitizes and centralizes it.

The shift is now mainstream: in one 2025 industry analysis, more than three-quarters of compliance leaders said digital EHS technology is the only scalable way to keep up with the inspections, certifications, and audit trails they have to manage across sites. Tasks get done faster. Gaps in the safety program become obvious. And your researchers get to focus on research, because there's finally one place to look instead of ten.

Below are 10 reasons to make the switch backed by industry research, and by two universities that did exactly this to slash their two-week reports to ten minutes.

Why Should You Digitize & Centralize Your EHS Data?

The short answer: a single, real-time system shows you your risks the moment they appear, makes audits painless, and frees your team from hours of manual reporting. Here are the 10 reasons that matter most.

1. You'll actually understand your risks.

Unseen risk is expensive: the National Safety Council counted 103 million workdays lost to work injuries in the U.S. Likewise, the total cost of work injuries in 2023 came to $176.5 billion. The bulk of these are preventable: real-time data is how you catch those risks early. You know the minute a researcher's training lapses or a new chemical lands in one of your labs, so you can respond before it becomes a problem.

2. Your reports get fast and accurate.

When laboratory information lives in ten places, every report is a scavenger hunt. Put it in one system and you can pull an up-to-date radiological inventory or inspection report in minutes.

3. You can handle audits without the panic.

‍What happens when an auditor asks about training, lab hazards, equipment, or assets? Without a central system, a request like that can stall your team for days, or you might not find the information at all. With everything in one place, you're always ready.

4. You can find exactly what you need.

Which of your labs handle particularly hazardous substances? Has everyone been trained for the equipment they use? A central database lets you answer in seconds, without digging around or interrupting a single researcher.

5. Your institutional knowledge stays put.

When EHS staff leave, the safety knowledge stuck in their heads and their personal spreadsheets tends to leave with them. A central system keeps it: what one person knew is now something everyone on the team can reach.

6. Your data is protected.

Paper gets lost, burned, or soaked by a leaky pipe. Spreadsheets aren't much safer; they might get overwritten by a colleague, accidentally deleted, or lost to a crashed laptop. Software with nightly backups and disaster recovery survives all of that (and a spilled cup of coffee).

7. You spend your budget where it counts.

As your inspections, activities, and findings collect in one place, you can more easily spot trends and gaps. This helps you put your people and your funding where they'll make the biggest difference.

8. You can reach the right people instantly.

Good software lets you communicate inside the system, so you can send a targeted note to everyone with animal contact, or a chemical-safety reminder to specific lab groups. Replies stay on the record and in one place, instead of buried in your inbox.

9. You give everyone their time back.

Researchers and safety staff lose hours to filling out forms, compiling reports, and chasing down overdue items. This is exactly the admin-heavy, error-prone work that automation and AI are taking over: Verdantix expects AI-enabled EHS software to be standard by 2026. You'll see the proof in the two universities below, where reports that took days now take minutes.

10. You cut costs.

Workplace injuries are expensive, and most are preventable. The National Safety Council put the total cost of U.S. work injuries at $176.5 billion in 2023, and Liberty Mutual's 2025 Workplace Safety Index found employers pay more than $1 billion a week in direct workers' compensation costs for serious non-fatal injuries. Catching hazards before they turn into incidents is where the savings come from, and that starts with seeing them.

What Digitized EHS Data Looks Like In A Real Lab

After implementing SciSure, two university EHS teams went from scattered paper, spreadsheets, and guesswork to one real-time system, and the payoff showed up fastest in reporting: jobs that used to take days now take minutes. Here's what changed, in their own numbers.

At San Diego State University, EHS director Jennifer Ramil couldn't say how many lab spaces the university had, who worked in them, or what they were handling. The records technically existed in a facilities system, but as she put it, the information was "out of date yesterday."

At Boston College, EHS director Gail Hall had spent years cycling through paper binders, an Excel spreadsheet, and home-grown software. The problem, in her words, was "records here and records there." The goal was to centralize everything and link people to their labs, their hazards, and the right training.

Here's what digitizing their EHS data with the SciSure platform did for them.

Reporting dropped from days to minutes

The clearest win was time. At Boston College, a report listing every lab group and its PIs (Principal Investigators) used to take all day. Now it takes 5 minutes. A list of everyone working with a specific hazard wasn't even possible before, and now takes about 15 minutes.

San Diego State's numbers are just as stark:

• A report of users overdue for a course used to take an hour. Now it's 3 minutes.
• A full training compliance report used to take 2.5 hours. Now it's 3 minutes.
• That same compliance report, formatted for a department head, used to take two weeks. Now it's about 10 minutes.
• Looking up one person's training records used to take several hours. Now it's 1 minute.

Training compliance climbed & stayed there

At San Diego State, training compliance rose from 56% to over 80%, and the team grew from 8 courses and roughly 500 completed records a year to 16 courses and more than 4,600 records.

Likewise, Boston College reports up to 97% compliance, and its Training LMS (Learning Management System) let the team drop an outside consultant they had been paying for biosafety training and audits.

Identifying who's due for a course, then writing and sending the reminder? At San Diego State that used to take days. Now, in Jennifer's words, it's "automated."

Guesswork turned into real-time visibility

San Diego State went from not knowing how many labs it had to reporting, with confidence, that 100% of the spaces where chemicals are used had been inspected. That visibility changed behaviour too: Jennifer's PIs started taking an active role in managing their own labs, which she called "worth its weight in gold."

At Boston College, pulling scattered records into one place finally let the team connect every person to their lab, their hazards, and their required training.

Both teams traded "I'm not sure" for "here's the answer."

The data made the case for more resources

At Boston College, the information the team could finally extract from SciSure showed senior administration the need for more people, and the university approved two new Lab Safety Specialists. Once leadership could actually see the hazards across campus, the staffing argument made itself. That same visibility lets EHS spot trends and justify budgets with evidence, instead of asking for resources on a hunch.

How SciSure helps you digitize your lab's EHS data

SciSure brings your chemical inventory, safety data sheets, hazardous waste, biosafety, inspections, incidents, equipment, and training into one connected system, so your EHS data is real-time, searchable, and audit-ready instead of scattered across binders and spreadsheets.

SciSure is a Scientific Management Platform (formed from the merger of eLabNext and SciShield) that covers the ELN (Electronic Lab Notebook), LIMS (Laboratory Information Management System) for sample and inventory tracking, and Health & Safety (EHS) in one place. For your EHS team specifically, that means:

• One source of truth.
  Chemicals, hazards, training, inspections, and incidents live together, so you stop hunting across systems for an answer.
• Real-time answers.
  You see a lapsed certification or a newly added chemical the moment it happens, not weeks later.
• Audit readiness by default.
  When an auditor asks, the report is minutes away, not days.
• Time back.
  Your safety staff and your researchers get hours of their week returned, the way Boston College and San Diego State did.

Digitizing and centralizing your lab's EHS data helps you run a safer, more efficient research program with a return you can actually measure. But hey, don't take our word for it:

And if you want to see what your own reporting could look like at 5 minutes instead of all day, book a demo or talk to a SciSure specialist.

If you’re working at a lab, your risk of having an accident is highest when you’re in the middle of a routine task; even more so if you’re handling hazardous chemicals. This is why going over basic lab safety procedures with your staff is a priority, no matter their level of experience or how straightforward your processes are. Here’s a practical chemical lab safety guide based on the most recently updated environment, health, and safety guidelines to get you started.

Lab safety in chemistry: Why it matters

With a solid chemistry lab safety procedure set up, you can identify, reduce, and control hazards where chemicals are used, stored, or produced. Chemical labs present hazards that need layered controls: chemical exposure, burns, fire and explosions, slips and falls, extreme temperatures, radiation, electrical hazards, and pressurized systems. Without proper precautions, those hazards turn into injuries, illnesses, lawsuits, medical costs, regulatory penalties, and lost time. According to OSHA estimates, workers suffer more than 190,000 illnesses and 50,000 deaths each year tied to chemical exposures. The agency also notes that these figures are likely an undercount, since some illnesses take years to surface.

Here's the part that should bother you most: nearly all of these incidents are preventable. Studies of chemistry lab accidents consistently show that injuries come from skipping basic precautions, not from inherently high-risk experiments. The death of Sheri Sangji, a UCLA researcher in 2009, after a pyrophoric chemical ignited her clothing, is still one of the most cited cases. More importantly, this accident was entirely preventable with proper training, supervision, and PPE enforcement.

For organizations running multiple labs, the challenge goes beyond individual behavior. Safety has to be systematic: documented, trained, tracked, and enforced the same way across every site, every department, and every new hire. When the safety infrastructure is fragmented or informal, the organization inherits the risk of its weakest link.

In my experience, the labs that get this right treat safety as a culture, not a policy. A lab with a strong safety culture, one that emphasizes personal and community responsibility rather than just compliance, will always be better at spotting risks and preventing accidents than a lab that just has the right rules written down somewhere.

14 Chemistry Lab Safety Guidelines every team should follow

These guidelines address the most common ways people get hurt in chemistry labs. Each one is grounded in OSHA requirements, institutional best practices, and the day-to-day reality of working with hazardous materials.

1. Wear safety glasses at all times

Eye protection is required whenever you're in the lab, not just during active experiments. Chemical splashes, broken glass, and projectile fragments can happen at any moment. The American Academy of Ophthalmology, citing BLS data, reports that nearly 20,000 workplace eye injuries happen each year, often costing the worker at least one missed day. Likewise, Prevent Blindness estimates that around 90% of them are preventable with proper eyewear. Safety glasses should meet ANSI Z87.1 standards, and splash-resistant goggles should be used when working with corrosive liquids or running reactions with splash risk.

2. Wear protective clothing that actually fits

Protect your skin from chemical contact with a lab coat, closed-toe shoes, and long pants. Avoid loose sleeves, dangling jewelry, and open-toed footwear. When working with corrosive, flammable, or cryogenic materials, you may need additional personal protective equipment (PPE) including chemical-resistant gloves, a face shield, or a flame-resistant lab coat.

• Glove selection matters.  
  Not all gloves resist all chemicals. Check the glove manufacturer's chemical compatibility chart before you choose, because the wrong glove can give you a false sense of protection while a chemical permeates through it.

• Fit matters as much as type.  
  PPE only protects you if it fits. Gloves and goggles are often sized around an average that doesn't suit everyone, which means ill-fitting PPE causes accidents of its own. Make sure everyone on the team can try different sizes and pick what's safe and comfortable for them.

When selecting PPE, make sure to double-check the specific hazards in your Chemical Hygiene Plan. Compliance is patchier than most people assume: a UCLA Center for Laboratory Safety survey found that self-reported use of eye protection was just 61% in academic labs, versus 83% in industry.

As I always tell teams: PPE should never be selected without first doing a risk assessment to determine what equipment you need and what level of protection the task calls for.

3. Never eat, drink, smoke, or vape in the lab

Food and drink in the lab create a direct route for chemical ingestion through contaminated surfaces, hands, or airborne particles. This applies even in areas that look clean. Smoking and vaping add ignition risk near flammable materials and solvents.

4. Know where your emergency equipment is

In an emergency, every second counts, and hunting for equipment you should already know how to find can turn a manageable incident into a serious injury. Before you start any work, make sure you know the locations of:

• Fire extinguishers,  

• Fire blankets,  

• Safety showers,  

• Eyewash stations,  

• First aid kits,  

• and spill response materials

Your lab should make sure emergency equipment is inspected regularly, accessible without obstruction, and documented in their safety management system. San Diego State University found that digitizing their EHS operations gave them real-time visibility into lab spaces, equipment, and training compliance, which they simply didn't have when relying on paper.

5. Use fume hoods for hazardous chemical work

Fume hoods are engineered controls that protect you from inhaling toxic, volatile, or irritating chemicals. Do any work involving hazardous vapors, gases, or aerosols inside a properly functioning fume hood. Check the airflow before you start, keep the sash at the recommended height, and don't store chemicals inside the hood unless it's specifically designated for that.

6. Practice thorough hand hygiene

Wash your hands before and after working in the lab, before eating or drinking outside it, and after removing gloves. Good hand hygiene protects you and your colleagues from chemical transfer and cross-contamination. Use soap and water, not hand sanitizer, which doesn't remove chemical residue effectively.

7. Don't work alone with hazardous chemicals

Avoid working with hazardous chemicals or high-risk processes when you're alone in the lab. If something goes wrong during a high-hazard procedure, you want someone nearby who can recognize the problem and respond or call for help if you can't.

This is also where a written protocol reaches its limit. A procedure that tells people how to identify and assess hazards is no substitute for keen attention and active supervision by a knowledgeable lab manager or principal scientist. Recognizing a hazard and judging how serious it is at the moment is a skill that takes attention, practice, and mentoring to develop. In fact, a UCLA survey of researchers found that accidents and injuries were notably lower in labs where the lead scientist was actively engaged in safety, not just in labs that had the rules written down.

8. Never mouth-pipette

Using mouth suction to fill a pipette is a dangerous, outdated practice that risks ingestion or inhalation of hazardous materials, biological contaminants, or radioactive substances. Always use a mechanical pipetting device. This one applies universally, no matter what you're handling.

9. Handle glassware and sharp objects with care

Never force glass tubing through a cork or rubber stopper. It can shatter under pressure and cause severe cuts. Use proper lubrication (glycerin or water) when inserting glass into stoppers, protect your hands with a towel, use a gentle twisting motion, and fire-polish all cut edges before use.

The same care applies to needles, blades, and broken glass. Handle them deliberately, never recap or bend needles by hand, and dispose of them in a designated sharps container rather than a regular waste bin. Sharps injuries are easy to underestimate. In hospital settings alone, the CDC estimates about 385,000 needlestick and sharps injuries among healthcare workers each year, and at least half go unreported.

10. Always add acid to water

Adding water to concentrated acid sets off a violent exothermic reaction that can splash concentrated acid onto skin, eyes, and clothing. Always add acid to water, slowly and with constant stirring. This applies to all strong acids, including sulfuric, hydrochloric, and nitric.

11. Use designated waste containers

Dispose of chemical waste in properly labeled, designated containers. Never pour chemicals down the drain unless your waste management program explicitly authorizes it. Segregate waste by compatibility (acids, bases, halogenated solvents, non-halogenated solvents) and keep containers sealed when not in active use. Proper chemical waste disposal is both a safety practice and a regulatory requirement under EPA and state environmental rules.

12. Securely replace chemical containers after use

As soon as you've taken what you need, replace every cap, lid, and stopper. Open containers let volatile liquids evaporate, release toxic vapors, and absorb moisture from the air, all of which can create hazardous conditions or degrade the chemical. It also prevents spills during transport or storage.

13. Secure compressed gas cylinders at all times

Compressed gas cylinders are heavy and stored under very high pressure, which makes an unsecured one genuinely dangerous. If it tips and the valve shears off, the cylinder can rupture or take off like a projectile. A typical cylinder stands about 4 feet tall, weighs 75 to 80 pounds, and can be pressurized to roughly 2,200 psi (for reference, a car tire sits around 30 to 35 psi).

The BLS recorded 10 deaths and roughly 3,900 injuries tied to pressurized containers in 2016 alone. Strap or chain every cylinder to a wall or bench, keep the valve cap on when a cylinder isn't in use, and move them with a proper cylinder cart, never by rolling or dragging.

14. Report all accidents and incidents immediately

Every accident, injury, near-miss, or unsafe condition should go to your supervisor immediately, no matter how minor it seems. Incident reporting isn't just a compliance box; it's the foundation of a learning safety culture. Organizations that track and analyze incidents can spot patterns, fix root causes, and prevent the next one.

For organizations managing safety across multiple labs or sites, centralized reporting is essential. When reports are scattered across emails, paper forms, or local spreadsheets, the patterns become invisible, and corrective actions are hard to track.

The Chemical Hygiene Plan: Your lab's safety foundation

A Chemical Hygiene Plan (CHP) is a documented program required by OSHA's Laboratory Standard (29 CFR 1910.1450) that lays out the procedures, safe work practices, and protective measures an organization uses to protect employees from chemical hazards. Here’s what yours should address:

• PPE requirements specifying what protection is needed for different chemical classes and operations

• Hazard identification including how Safety Data Sheets (SDS) are maintained, accessed, and kept current

• Standard operating procedures for specific chemical categories, including particularly hazardous substances (carcinogens, reproductive toxins, acutely toxic chemicals)

• Spill response protocols covering containment, cleanup, decontamination, and reporting for different chemical types and quantities

• Waste disposal procedures aligned with EPA regulations and institutional waste programs

• Training requirements specifying what's required before lab access, how often refreshers happen, and how completion is documented

• Medical consultation provisions for employees who may have been exposed to hazardous chemicals

• Record-keeping standards for maintaining audit-ready safety records

The Chemical Hygiene Plan isn't a static document. Review it annually, and update it whenever new chemicals, processes, or regulatory requirements come in. For organizations with multiple labs, keeping CHP standards consistent across sites is what prevents the compliance gaps that appear when each lab quietly develops its own way of doing things.

Building a safety culture that scales

The 14 guidelines above protect individual researchers. But for organizations running dozens or hundreds of labs, safety must work as institutional infrastructure, not just personal discipline.

Training compliance at scale

Everyone who enters a lab should get documented safety training before they begin, with refreshers at regular intervals. But tracking that across an entire organization, especially one with high turnover from students, postdocs, and rotating staff, becomes impossible with spreadsheets and paper. San Diego State University digitized their EHS workflows to fix exactly this. Before, the team had no reliable way to connect researchers to the labs they worked in or the training they needed. After centralizing training management, they went from 8 courses and 500 completion records a year to 16 courses with over 4,600 records, while lifting overall training compliance from 56% to more than 80%.

Chemical inventory visibility

Organizations working with hazardous chemicals need real-time visibility into what's present, where it's stored, and in what quantities, across every lab and every building. That information is critical for emergency response, fire code compliance, Tier II reporting, and Maximum Allowable Quantity (MAQ) management.

When chemical inventory lives in spreadsheets or local databases, it goes stale and inconsistent, and it's inaccessible to the people who need it most: first responders, EHS officers, and leadership. The Engine, MIT's Tough Tech accelerator, grew from 10 to 50 resident laboratory companies and found that digitizing chemical inventory cut the time needed to find hazard information from several hours to under five minutes.

Inspection and audit readiness

Regulatory inspections happen on their own schedule. The organizations that prepare reactively, scrambling to assemble documentation when an audit is announced, are the ones most likely to have gaps. Safety infrastructure should generate audit-ready records continuously, as a byproduct of normal operations, not as a special project. That means inspection checklists, training records, chemical inventories, incident reports, and corrective action logs should all live in one connected system where they're always current and always accessible.

Connecting safety to research operations

In a lot of organizations, EHS runs in a completely separate system from the research it's meant to protect. Chemical inventories in one tool, training records in another, experiment documentation in a third, incident reports in email. That fragmentation makes it hard to see how safety connects to the daily work of science.

Modern platforms unify the two. SciSure's Scientific Management Platform connects chemical inventory management, training, inspections, and safety compliance with ELN, LIMS, and sample management in one environment, so safety is built into how science gets done rather than bolted on as a separate administrative chore.

Safety is infrastructure, not just behavior

Lab safety usually gets framed as a set of personal habits: wear your goggles, wash your hands, report incidents. Those habits matter. But for a research organization, safety is also an institutional capability that needs documentation, training systems, chemical oversight, and consistent governance across every lab and every site.

The 14 guidelines here are the behavioral foundation. A well-maintained Chemical Hygiene Plan is the procedural framework. And the right digital infrastructure is what makes sure both actually get implemented, tracked, and enforced as the organization grows.

When safety is treated as infrastructure rather than individual willpower, organizations don't just avoid accidents. They earn the operational confidence to grow, collaborate, and push their science forward without cutting corners.

Ready to strengthen your organization's safety infrastructure? Talk to a specialist about how SciSure connects EHS, chemical management, and training with your research operations.