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Forbes
6 days ago
- Business
- Forbes
How Technologies Can Help You Stay Compliant With SDS Regulations
COO at SapientPro. AI expert building scalable tools like an SDS platform with smart search, alerts&workflows adaptable across industries. Last year, in enterprises across 28 European countries, over one-third of safety data sheets (SDS) were non-compliant with legal requirements due to data gaps and inaccurate entries. One of the main reasons is the increasing number of SDS that conflict with safety regulation standards. In the following, I'll break down some smart tactics to respond to these challenges. Common Pain Points In Daily SDS Management SDS files contain full information on the chemicals used in pharmaceuticals, food production, oil and gas, logistics and beyond. As those industries expand and safety regulations update, traditional file management is being pushed to its limit. Companies rely on these SDS files, which span everything from PDFs, scans, region-specific templates and multilanguage copies—rarely sharing a common structure. Right-to-left scripts such as Hebrew or Arabic can complicate the translation process. Regional compliance tweaks drive standards further apart. To solve this, some companies are turning to automated solutions that use artificial intelligence (AI) and machine learning (ML) to analyze and restructure the documents. These tools can convert each file into a standardized format, making the data easier to work with. Even though the Global Harmonized System (GHS) was meant to simplify and unify chemical safety paperwork, in practice it has made SDS creation and maintenance more complicated. Rapid rule changes at national and U.N. levels result in firms struggling to keep current. Other standards to contend with include: • The Hazard Communication Standard (HCS) from the Occupational Safety and Health Administration (OSHA) in the U.S. • REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) in the EU • Workplace Hazardous Materials Information System (WHMIS) in Canada Always-on AI services can help spot stale data, highlight gaps and show live status dashboards per product. Overall, you want a system that indexes in any language and applies standards-locked templates with automatically generated locale-specific SDS. Research and development (R&D), health, safety and environment (HSE) and logistics teams each tend to store their own copies of SDS, often without shared access or version tracking. Also, many jurisdictions mandate that SDS be stored domestically. Dropping them in a global public cloud can expose enterprises to data loss and penalties. To avoid this, companies can deploy on-premises hardware, use a private cloud hosted within the country or adopt a hybrid model—storing sensitive data locally while sending less critical files to public cloud providers. Adding tailored access controls further strengthens compliance and security. Furthermore, different systems—like enterprise resource planning (ERP) for vendor updates, laboratory information management systems (LIMS) for testing and product lifecycle management (PLM) for lab checks—often manage their own SDS separately. This can lead to disconnected records that can quickly fall out of sync, risking non-compliance. Costs Of Ignoring SDS Standards Monetary hits are just one fallout for firms that overlook SDS rules: OSHA still ranks hazard communication failures, including incomplete or absent SDS, among its 10 most-cited violations. In 2025, each serious offense can cost up to $16,550. But inspections often uncover multiple issues, driving total fines potentially into six figures. Companies may also face lawsuits, suspended licenses and long-term brand damage. In 2021, an Alabama chemical plant accident claimed two lives and poisoned a third employee. Officials later confirmed that the company had neither monitored air contaminant levels nor trained staff on handling risks. OSHA responded with a fine of $232,000 for 10 violations. Absent or faulty SDS documentation delays shipments and triggers product pullbacks. This, in turn, translates into costly rework for companies, piling up reproduction expenses, logistics, penalties and refunds. Сase-Based Strategies To Solve SDS Challenges The following examples show how companies in different industries addressed these issues by rethinking workflows and aligning documentation practices with regulatory demands. While each context is unique, the underlying strategies offer insights that other organizations can adapt. I worked with a Swiss medical company to tackle a number of SDS pain points: outdated files, language barriers and scattered access across partner sites. When it comes to an issue like this, I've found three clear moves that can help turn scattered safety sheets into a working system: 1. Inventory your files. List storage spots, duplicates and search faults; use the findings to shape a clean SDS library. 2. Expose term clashes. For multimarket firms, track where terms drift across tongues and pin down the biggest misalignments. 3. Put roles in charge. Add role‑based access with version history so every tweak ties to the right standard: GHS or regional. Another manufacturer I worked with had 600-plus SDS documents scattered across multiple construction sites. They needed a single repository, standard formatting and role-based access. Rolling out SDS full service hinged on three basics: a clear inventory of all sheets, unifying the file formats and the implementation of role‑driven entry rights. Replicating this model elsewhere means building a central console, plugging in extra languages where needed and creating a rights system that can grow with your business. A pesticide manufacturer I worked with operates in 50 countries and ships to 150. Because of its reach, the company struggled to make SDS compliance rock-solid. Every jurisdiction rewrote the rulebook, labels appeared in half a dozen languages and no central admin held the reins. As a result, the SDS library was left unruly; copies multiplied, records fell out of sync and audits became a guessing game. We solved it with a sync-in-place system tied to standard operating procedures. Order was restored through shared templates, real‑time refreshes and airtight logs. For small businesses, the logic scales down, too: one access point, template uniformity, tracked edits and rights‑based access. The Cornerstone Of SDS Leadership According to McKinsey, companies in tightly regulated industries should adopt a forward-looking approach, future-proofing their workflows against the risk of SDS non-compliance. This means not only reacting to current standards but actively building systems that can adapt to new regulations, technologies and markets. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
Forbes
21-07-2025
- Business
- Forbes
Why Every Business Needs An AI Adoption Roadmap
Janet Lam is an AI solutions expert and the founder of Building Blocks Business Planning, helping businesses thrive through innovation. AI isn't just for tech giants anymore. From dental offices to logistics companies, businesses of all kinds are starting to use AI—not to replace people, but to support them. It's becoming a helpful assistant that takes care of repetitive work, boosts productivity and gives teams more space to focus on what really matters. That said, diving into AI without a plan can be frustrating. The tools can feel overwhelming, and leaders often worry about cost, complexity or how their teams will react. But here's the thing: adopting AI doesn't need to be extreme. It can start small. With the right mindset and a solid plan, it can be surprisingly manageable—and valuable. Here's how to think about AI adoption in a way that makes sense for your business and your people. What It Really Means To Be An 'AI-First' Company Being 'AI-first' isn't about using the most cutting-edge technology or trying every tool on the market. It's about being intentional. It means looking at your operations and asking: Where could AI actually help us work better? This approach starts at the foundation. AI-first companies design workflows with AI in mind from the beginning, not as something to tack on later. And they don't all have in-house tech teams or massive budgets. They look for the areas where AI can make a real difference—like speeding up manual tasks, helping with lead management or generating quick content drafts. The goal isn't to turn everything over to AI. It's to use it to give your team more time to focus on higher-impact work. AI Adoption Isn't The Same As Digital Transformation It's tempting to lump AI into the broader category of digital transformation, but they're not quite the same. Digital transformation often means moving things from paper to digital or getting set up in the cloud. It's about catching up. AI adoption, on the other hand, is more forward-looking. It's about building systems that don't just store information—they act on it. They learn, adapt and help make decisions in real time. That opens the door to new ways of working that go beyond just being more efficient. It's about becoming smarter, faster and more responsive. Why You Need A Roadmap One of the biggest mistakes I see businesses make is jumping into AI by picking a tool they've heard about and trying to force it into their workflow. When it doesn't fit, adoption stalls. Teams get frustrated. The whole effort loses momentum. What works better is starting with a roadmap. A clear, realistic plan that lines up with your team, your systems and your business goals. It doesn't have to be fancy or long. But it does need to be grounded in how your business actually works. A Practical AI Roadmap In Four Steps Look at what's slowing your team down. Maybe creating content takes too much time or your team is buried in repetitive customer questions. These are often great places to start. Don't try to tackle everything at once. Start with something focused—like using AI to summarize internal meeting notes, generate first drafts of reports or automate lead follow-ups. Test the tool on a small scale. See what's working and what isn't. Ask your team how they're using it and where it helps—or doesn't. If the pilot works, expand carefully. Don't get distracted by every shiny new tool. Stay focused on what's delivering actual results for your team. Keep It People-Centered The best AI projects I've seen are the ones that don't lose sight of the human side. It's not just about onboarding people into new software—it's about showing them how AI can make their day-to-day better. When teams see that AI is helping them spend less time on repetitive tasks and more time doing the work that matters, they're more likely to embrace it. It's not about replacing them. It's about helping them do their jobs more effectively. Final Thoughts AI is moving fast, but that doesn't mean businesses need to chase every trend. A roadmap helps you take a more thoughtful approach: test what works, build around your team and grow with purpose. The companies making real progress aren't doing everything at once. They're making smart, well-timed decisions. And more often than not, the ones that seek the right guidance early on tend to avoid missteps and build momentum more quickly. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?
