How to Enhance Documentation Systems

Is your GMP system collapsing under the weight of its own paperwork? If documentation is slowing you down more than it’s protecting patients, you’re not alone. It started with a deviation. Just a 5-minute delay in a mixing step. By the time it was closed, the team had created: 📄 47 pages of documentation 📚 9 cross-referenced SOPs 🧾 3 levels of review 🧠 A “lessons learned” log… for a low-impacting issue ✅ Every line: accurate. ✅ Every reviewer: diligent. ✅ Every link: cited. So why did the site fail its FDA inspection 3 months later? ⚠️ Because investigators couldn’t find the signal through the noise. ⸻ Over-documentation ≠ good documentation It feels safe to “cover all bases,” but it can backfire: • Reviewer fatigue • Delayed investigations • System inconsistencies • Missed critical info ⸻ 🌍 Expectations vary by region: 🇺🇸 FDA wants “adequate,” “contemporaneous,” and “complete” , not everything. 🇪🇺 EMA under Annex 1 stresses control + traceability, but favors lean. 🇬🇧 MHRA prioritizes clarity and risk-driven documentation. 🇯🇵 PMDA often prefers detailed redundancy, but still value-driven. 💡 No regulator asks for everything. They ask for what matters. ⸻ 📌 5 ways to escape the over-doc trap: 1️⃣ Use Risk-Based Thinking Apply ICH Q9 to scale based on impact. 2️⃣ Tier Documentation Group by: • Critical-to-Quality • Regulatory-Mandated • Operational Reference 3️⃣ Involve End-Users Early Ask: “What helps?” and “What slows us down?” 4️⃣ Digitize with Intent Don’t digitize chaos. Design smart, searchable systems. 5️⃣ Define Your Philosophy Set a documentation mission. Review it yearly. ⸻ 📣 Bottom line: From ICH Q10 to FDA’s quality maturity model—the signal is clear: ✨ Documentation should enable decisions, not bury them. — 🗣️ Your turn: Have you seen documentation slow down compliance? What helped you fix it? Let’s trade ideas. Because in GMP… Clarity is compliance. ♻️ Repost to increase awareness of your teams. #GMP #QualityCulture #RiskBasedApproach #GMPDocumentation #ComplianceLeadership #ICHQ10 #FDA #EMA #MHRA #PMDA #DigitalQMS #Biotech #PharmaManufacturing #RightFirstTime #QualityByDesign

I scanned 2.8 GB of QMS documents in a week. Then, shared this uncomfortable truth with the QA director: More documentation ≠ a better quality management system. Most companies drown in paperwork that doesn’t actually improve quality. Want to fix that? Start here: 1️⃣ Kill redundant SOPs. Do you really need three SOPs saying the same thing Nope. Review processes and cut the fluff. 2️⃣ Make SOPs usable. Stop writing mini-novels. Focus on clarity and actionability—less “legalese,” more “get it done.” 3️⃣ Use risk-based thinking. Not everything needs a procedure. Focus on the high-impact stuff that actually matters. 4️⃣ Streamline approvals. Empower the right people to finalize documents. Endless review cycles = wasted time. 5️⃣ Go digital. Why deal with stacks of paper when workflows can live in a streamlined system? Go for a lightweight eQMS and automate what you can. The goal isn’t more documents—it’s lean, effective processes that drive compliance AND improvement. QA people have a great opportunity here to be creative, which is quite underrated. What would you add?

"Can I be brutally honest?" The pharma exec I was talking to over Zoom nodded. "Your writers are taking work home at night just to keep up. You're burning $12,500 monthly on unnecessary reviews. Plus, your teams are losing 250 hours each month to document revisions." Awkward silence. Then, something unexpected. A smile crept up the sides of his face, and he said, "I appreciate that kind of honesty." Backstory: He’d been burned by writing consultants before who didn’t dig deep enough and offered surface-level “grammar” workshops. "Go on," he said. So I told him about Mei, a senior writer in his organization who hadn't had dinner with her family in weeks because documents kept getting stuck in endless revision cycles. And I mentioned Raj, a reviewer who felt guilty about rushing through approvals because the backlog was overwhelming. The deeper we dug, the clearer it became:   - Writers desperately wanted to produce better documents but were drowning in a long review cycle and overwhelmed with contradictory comments - Reviewers felt pressured to approve quickly, without time for meaningful feedback   - Quality teams needed better tools but were stuck with outdated templates, poorly written SOPs, no style guide, etc.  "What's the solution?" he asked. I explained to him that writing and reviewing should be viewed as an ecosystem. When everyone has the same understanding of standards and goals, it’s much easier to produce effective documentation. And that critical thinking is the foundational piece of effective writing and reviewing. That means considering: - Who will be reading the document - What they’ll do with the document - & figuring out how to ensure that every word, sentence, and paragraph work to drive the desired conclusion. Then, we built a system that worked for everyone:   - Templates that actually guide, not just format   - Review processes with clear expectations   - Standards that both writers and reviewers understand  Three months later, Mei had dinner with her family on a Tuesday night for the first time in years. Raj started giving the kind of feedback that actually improved documents. The quality team became partners in the process, not the begrudging grammar police. Because when you build on critical thinking... When your writers have clear direction...   When your reviewers have a proper process...   When your team has frameworks that actually work for their use cases... That's when quality documentation becomes part of your culture, not a bottleneck in your pipeline.

We often talk about technical debt in software teams, but have you ever considered 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗱𝗲𝗯𝘁? 👀 It’s the hidden cost of undocumented or inaccessible know-how in a growing company. In my experience, teams feel this pain daily, even if they don't have a name for it. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗗𝗲𝗯𝘁? Knowledge debt is the backlog of important information that hasn’t been documented or shared widely. At first, a little tribal knowledge might seem harmless—everyone just asks Alice for deployment steps or Bob for tricky client questions. But that ends when Alice is on vacation or Bob leaves. Just like technical debt, knowledge debt accumulates "interest." Every time we postpone writing a how-to guide or skip recording the "why" behind a decision, we create knowledge debt by borrowing against future productivity. Rushing a project without docs is like a short term hack in code—it works for now but leaves everyone struggling later. 𝗧𝗵𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗗𝗲𝗯𝘁 ❌ 𝗪𝗮𝘀𝘁𝗲𝗱 𝘁𝗶𝗺𝗲 𝘀𝗲𝗮𝗿𝗰𝗵𝗶𝗻𝗴: We lose around 1.8 hours a day searching for info—nearly a full day per week even for a small team! ❌ 𝗢𝗻𝗯𝗼𝗮𝗿𝗱𝗶𝗻𝗴 𝗰𝘂𝗿𝘃𝗲: Relying on “ask Joe” for information slows down onboarding, estimated to cost companies millions in lost productivity. ❌ 𝗗𝗲𝗹𝗮𝘆𝗲𝗱 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀: When information is hard to find, decisions come to a stall. 68% of companies face project delays from missing info. ❌ 𝗥𝗲𝗶𝗻𝘃𝗲𝗻𝘁𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗵𝗲𝗲𝗹: Nearly 59% of R&D and product teams later discover the expertise or project they recreated already existed within their company. ❌ 𝗙𝗿𝘂𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝗰𝗵𝘂𝗿𝗻: 81% of employees feel frustrated when they can’t access the info needed to do their jobs, which can erode morale and push talent to leave. 𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗗𝗲𝗯𝘁 𝗶𝗻𝘁𝗼 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗖𝗮𝗽𝗶𝘁𝗮𝗹 ✅ 𝗖𝘂𝗹𝘁𝗶𝘃𝗮𝘁𝗲 𝗮 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝘂𝗹𝘁𝘂𝗿𝗲: Use internal wikis or docs and lead by example—record key decisions and insights. ✅ 𝗕𝗿𝗲𝗮𝗸 𝗱𝗼𝘄𝗻 𝘀𝗶𝗹𝗼𝘀: Host brownbag sessions, circulate newsletters, and rotate team members across projects to share knowledge. ✅ 𝗠𝗲𝗻𝘁𝗼𝗿𝘀𝗵𝗶𝗽: Pair newcomers with veterans to transfer implicit undocumented knowledge. ✅ 𝗧𝗿𝗲𝗮𝘁 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗮𝘀 𝗮𝗻 𝗮𝘀𝘀𝗲𝘁: Designate “knowledge champions” or host Documentation Days to regularly “pay down” your debt. This pays off not only with the team, but also with the coming of AI agents who can utilize this knowledge to reliably and accurately get things done. ✅ 𝗠𝗮𝗸𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝘀𝗲𝗮𝗿𝗰𝗵𝗮𝗯𝗹𝗲: Invest in tools that unify scattered information. Paying off knowledge debt turns a liability into an asset. When your team's know-how is documented and accessible, you build 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗖𝗮𝗽𝗶𝘁𝗮𝗹! New hires get up to speed faster, teams feel unblocked to do their best work, and learnings compound across projects.

🌟 Best Practices in Salesforce Documentation 🌟 Clear, consistent, and up-to-date documentation is one of the most underrated secrets behind successful Salesforce implementations. Whether you’re working solo or as part of a team, great documentation empowers everyone to build smarter, fix faster, and onboard easier. Here’s how to get it right: 🔹 Start With the Basics Be Consistent: Use the same structure, language, and formatting across all documentation. This makes it easy for anyone to jump in and understand your work. Keep It Simple: Avoid excessive jargon. Write like you're explaining it to a smart teammate who’s new to the org. 🔹 Use Visuals and Metadata Wisely Add Diagrams and Screenshots: A simple flowchart or a well-placed screenshot can explain more than a page of text. Descriptive Field Names and Help Text: Include why a field exists, how it's used, and what it impacts. These small notes can save hours later. 🔹 Stay Agile, Not Rigid Document As You Go: The best time to write documentation is when you're in the middle of the work. Don’t wait until later—it rarely happens. Version Control: Track changes to keep a clear audit trail. Even simple naming like v1.2_final_FINAL (okay, maybe cleaner than that) helps avoid confusion. 🔹 Build Organizational Knowledge Create a Metadata Dictionary: Keep a living list of key objects, fields, and relationships in your org. This makes reporting, automation, and debugging faster and easier. Map Business Processes: Tools like Salesforce UPN or Lucidchart can help turn complex logic into digestible visual stories for both technical and non-technical stakeholders. 🔹 Think Long-Term Change Logs: Note what was changed, why, and by whom. You'll thank yourself later. Architectural Decision Logs: For major implementations, document why a particular design was chosen over others. It saves time when scaling or troubleshooting. 🔹 Use Salesforce’s Built-In Tools Leverage Notes, Knowledge Articles, and Chatter Groups to store and share documentation where your team already works. 🔹 Stay Ready for AI AI tools (like Agentforce for developers) thrive on clean metadata and documentation. Well-documented orgs will have a head start as AI takes a bigger role in development and support. 🔹 Make It a Team Effort Encourage feedback and contributions from your team. Documentation improves when it's a shared responsibility, not a solo task. Include key docs in training and onboarding so new team members hit the ground running. 📌 Pro Tip: Don’t try to document everything at once. Focus on areas with the most change or confusion. Over time, your documentation will become a powerful, living knowledge base.

🛠️ In my last post, I shared 7 reasons why data documentation is still so hard. Now let’s talk solutions: Here’s how leading data teams are solving each challenge today: 1. It’s no one’s core responsibility → Make documentation part of the workflow. Don’t allow dbt model PRs to merge without a model description. Treat documentation like tests—required for production. 2. Data is always changing → Use automated lineage and change detection. Get alerted when upstream tables or columns change. Use AI to auto-update or review the new docs. 3. Manual documentation doesn’t scale → Leverage AI to generate table and column descriptions. Start with smart defaults based on naming patterns and SQL logic. Let humans review and refine. 4. Your tools are fragmented → Adopt a centralized metadata platform. One place that connects your warehouse, dbt, BI tools, Airflow, ... so you can see the full picture. 5. Documentation is hard to find → Bring docs to where people work. Show table descriptions in query editors. Surface lineage in BI tools. Make metadata searchable in Slack. Metadata platform can help bringing documentation to tools that users are already working with. For example, Select Star has chrome extensions, Slack apps, and MCP server, that will display the relevant information within the apps. 6. No feedback loop → Track usage and engagement. See which docs are viewed or ignored. See which data assets are being viewed. Let users comment or flag stale content. 7. Lack of ownership → Assign data owners by table, dashboard, or metric. Use metadata tools to operationalize the data stewardship. Notify owners to review/update docs, when questions get asked, when things go out of date. Good documentation is no longer about extra work. With AI and metadata automation, it can be integrated into how your team already works. This is exactly what we’re building at Select Star—drop me a message if you want a look. Anything I missed? Also happy to elaborate more on any of the points.

Hate how boring and time-consuming documentation feels? Yeah, same. But here’s the thing: the more you avoid it, the more you hurt your future self and miss opportunities to showcase your skills properly. So if you want to make documentation less painful (and actually useful), here are 6 tips I use with my clients to make it faster, clearer, and more impactful: 1. Start with an overview What’s the purpose of your project? What problem did it solve? Just 3–4 lines to set the stage. Make it easy for anyone to understand why it matters. 2. Walk through your process Break down the steps: How did you collect the data? How did you clean, analyze, or model it? What tools or methods did you use? This shows how you think and how you solve real-world problems. 3. Add visuals A clean chart > a wall of text. Use graphs, screenshots, and diagrams to bring your work to life. (And bonus: you’ll understand it faster when you come back later.) 4. Show your problem-solving What roadblocks did you hit? How did you fix them? Don’t hide your struggles, highlight them. This is where your value really shines. 5. Summarize your results What did you find? Why does it matter? What’s next? Answer these three questions clearly and your audience will instantly get the impact of your work. 6.  Use a structure that makes sense Try this flow: Introduction → Objectives → Methods → Results → Conclusion → Future Work Simple. Clean. Effective. P.S: After every milestone, take 5 minutes to update your notes, screenshots, or results. Turn it into a habit. ➕ Follow Jaret André for more data job search, and portfolio tips 🔔 Hit the bell icon to get strategies that actually move the needle.

1/You won’t remember what you did. Not next week. Not next month. Write. It. Down. It will save your future self hours—days. 2/ Documentation seems like a waste of time. Until you stare at a directory named results_final_final2_revised. And ask, “What even is this?” 3/ Bioinformatics is messy. You run 15 commands. One of them works. You move on. But in 6 months, you'll need to re-run it. And you won't remember which one. 4/ Build the habit: Keep a README for every project One per data folder: where it came from, when, how Write every working command right after it works 5/ Yes, right after it works. Not "I'll do it later." Later becomes never. Your shell history won’t save you forever. 6/ Seven years ago, I documented how I processed enhancer-promoter interactions. Still usable. Still makes sense. https://lnkd.in/e4nBvBCb 7/ Nine years ago, I wrote down my scRRBS (single-cell DNA methylation) processing pipeline. Still helping me today. https://lnkd.in/eHTNb4pQ 8/ You don’t need to write essays. Just enough that a confused version of you can follow along. And trust me, they will be confused. 9/ Use comments in your code. Use markdown for notes. Use Jupyter or Quarto for literate workflows. Don’t leave your brain in your shell history. 10/ Why document? Reproducibility Debugging Collaboration Sanity Growth Your README is your lab notebook. 11/ You think you’ll remember. You won’t. You think it’s clear now. It won’t be. You think it’s just a small hack. It’ll become the foundation of your next pipeline. 12/ Key takeaways: Document as you go, not after A good README is future-proofing Your notes are your superpower Even if no one else reads them, you will 13/ Final word: Documentation isn’t a burden. It’s a record of your thinking. It’s your bioinformatics memoir. And yes—it’s part of the science. I hope you've found this post helpful. Follow me for more. Subscribe to my FREE newsletter chatomics to learn bioinformatics https://lnkd.in/erw83Svn

I stopped writing documentation for humans. My Cursor workflow became 10x more efficient overnight. Here's what I discovered after months of treating Cursor like a real development partner instead of fancy autocomplete. Heres The Problem Everyone's Missing Most developers are still stuck in the old paradigm. They're trying to make their documentation work for both AI and humans, and it's creating this weird hybrid that serves neither well. I was doing the same thing. Random prompting, hoping Cursor would magically understand what I wanted, then getting frustrated when it didn't deliver. This Week I've Realized We need TWO completely different documentation systems: AI-readable docs - Pure context priming for Cursor Human-readable docs - Traditional format for team collaboration Think about it - why are we forcing AI to parse documentation written for human comprehension when we could give it exactly what it needs to understand our codebase? Heres My New Documentation Strategy Im Test Running For Cursor (AI-readable): Structured context files that prime the entire project Feature specs in AI-digestible format Development patterns and style guides optimized for LLM consumption Business logic broken down into clear, contextual chunks For Humans (traditional): Standard README files User-facing documentation Team onboarding materials Project overviews This Is What I've Found So Far Since implementing this dual approach, my Cursor sessions are dramatically more productive. Instead of explaining context in every prompt, Cursor already understands my project structure, coding patterns, and business requirements. The AI documentation primes the entire conversation. The human documentation stays clean and focused on what humans actually need. We're entering an era where AI-first development workflows require AI-first documentation strategies. Fighting this reality just creates inefficiency for everyone. The teams that figure this out early are going to have a massive competitive advantage in development speed and code quality.

Question of the week: You've been tasked with systemising the business and making it more simple & scaleable. Where do you start? Here's where I'd start as a Chief of Staff: ✍🏻 Documentation, documentation, documentation, of *all* common processes in the business. ‼️ This is *the* most underrated task when you're moving fast and breaking things, esp. in growth-stage startups. Why is this so important? 3 reasons: 1. Onboarding new employees --- When you're scaling quickly, hiring + onboarding can take a significant amount of time. You're not scaleable, but your processes are. A 10 minute Loom played 6-7x is already an hour saved. 2. When 💩 hits the fan --- The website is down for 8 hours. You hear from hundreds of angry clients threatening to cancel. Everyone in the company suddenly needs to learn how to respond to support tickets and refund/discount payments. 3. When investors start sniffin' around for due diligence for funding rounds + exits --- Having solid documentation is one of the easiest ways to de-risk the investment from an operations side. Here's how I'd do it off the bat: 1️⃣ Quick Loom outlining every process that isn't documented or current 2️⃣ Then I'd have AI write a quick outline / article 3️⃣ I'd put both of these (links to Loom AND the text article) in the company's existing project management / documentation system. 4️⃣ Announce where it can be found, added and edited. Make it easily accessible to everyone and low-lift. 5️⃣ This can mean anything from submitting expense reports to pulling a marketing analytics dashboard to responding to support tickets. I typically do this as I'm onboarding myself to avoid double work. 💃🏻 Hope this helps! What other questions do y'all want answered? Feel free to ask in the comments or DM me 😊 -- Found this content helpful? Repost ♻️ or follow Elise Kennedy for more Chief of Staff content!