Addressing Production Line Problems Prior to Automation

Don’t Automate Complexity... Simplify and Error-Proof Instead When problems arise, it’s tempting to think automation is the magic fix. But automating a broken or complex process just means you’re speeding up the production of errors. The smarter approach? Simplify the process and error-proof it (Poka Yoke) before thinking about automation. Here’s why simplification often beats automation and how you can apply it. Why You Should Simplify Before Automating: 1️⃣ Faster, Cheaper Improvements Simplifying a process through standardization and removing unnecessary steps often solves problems more quickly and at a lower cost than automation. 2️⃣ Avoid Automating Waste If your process is full of waste (like waiting, overprocessing, or rework), automating it only speeds up inefficiency. Fix the process first, then think about automation. 3️⃣ Built-In Error Proofing With Poka Yoke solutions (like jigs, fixtures, or guides), you can design processes to prevent errors from happening in the first place—without needing expensive sensors or software. 4️⃣ Flexibility and Adaptability Simplified processes are easier to adjust and improve, while automated systems can be rigid and costly to change once implemented. How to Simplify and Error-Proof a Process: 🔍 Map the Current Workflow: Identify unnecessary steps, bottlenecks, and areas prone to errors. ✂️ Eliminate Waste: Remove any steps that don’t add value to the product or service. 📋 Standardize Work: Create clear, repeatable instructions that everyone can follow. 🔧 Introduce Poka Yoke: Physical Error-Proofing: Use jigs, fixtures, or alignment guides to prevent incorrect assembly. Visual Cues: Use color-coded labels or visual templates to guide operators. Sensors or Alarms: Only when needed, use low-cost technology to detect errors in real time. Example of Simplification and Poka Yoke in Action: A warehouse team was dealing with frequent errors when picking products for orders. Instead of implementing a costly automated picking system, they: 1. Introduced a color-coded bin system (Poka Yoke) to help operators select the correct items. 2. Simplified the picking route to reduce unnecessary walking and waiting time. Result: Picking errors dropped by 80%, and productivity increased by 15%—all without expensive automation. When to Consider Automation: Once the process is simplified and stabilized with minimal variation, automation can enhance speed and efficiency. But it should support an optimized process, not mask its problems.

The problem: undocumented steps. The consequence: a useless machine. The solution: map, measure, interview, THEN automate. True story: A client wanted to automate their packaging line. Seemed straightforward enough. We started digging. Turns out, their manual process had 7 undocumented steps. Steps they'd "always done" but never formalized. If we hadn’t dug for this information and simply automated the written, functional requirements, the client wouldn’t have received a machine that met their needs. Lesson learned: You can't automate what you don't understand. Before you dive into automation: • Map out every step of your current process • Time each task • Note all the "little things" your team does • Talk to the operators, maintenance, and engineers about nontypical parts and situations. It's tedious. But it's critical. Why? Because automation amplifies everything including inefficiencies. Get clear on your process first. Then automate.

You can’t automate confusion. Every few months, someone proudly tells me: “We’re investing in automation to fix our efficiency problems.” Sounds great. Until you realize they’re about to automate… a mess. Here’s the thing most execs forget: Automation accelerates everything Good or bad. If your process is unclear, your automation will just make mistakes faster. I’ve walked into plants with shiny new robots feeding broken scheduling logic. AGVs stopping every 12 meters because no one re‑mapped the aisles. MES dashboards lighting up with real‑time nonsense. Millions invested. Zero improvement. Why? Because they automated symptom, not cause. Before you automate, ask brutally simple questions: Do we know what “good flow” actually looks like? Are sequences stable? Are materials and data structured to feed automation instead of fight it? If the answer is maybe, automation isn’t your next step, Clarity is. One of our clients delayed an automation project six months. Used that time to fix planning logic and simplify product changeovers. When the robots finally arrived… output doubled in four weeks. Not because of the machines But because the system finally made sense. Automation works when humans understand the problem it’s solving. Otherwise, you’re just teaching robots to chase the same chaos. _______________________ ♺ Reshare this, your VP Ops & division VP need to hear this. ► Want more no‑BS manufacturing and Supply Chain stories? Join my newsletter: https://lnkd.in/dMGaUj4p

Don’t waste your time and money until you’ve figured out where your time and money are being spent. Everyone wants better efficiency, smarter automation, and AI-powered workflows. But here’s the problem, most companies don’t actually understand their processes. They know the big stuff—work comes in, work goes out, people get paid. But what happens in between? Where are the bottlenecks? Where is work getting duplicated? Where are employees compensating for broken or absent systems? Before you invest in automation, AI, or any kind of process improvement, you need to do one thing first: Map your processes. Yes, it’s boring. Yes, it takes time. But it’s one of the most crucial steps you can take. Without a solid understanding of your processes you’re just daydreaming about making improvements. Document every step—from order to fulfillment, from data entry to decision-making. Find the inefficiencies—where are people manually fixing broken processes? Identify what should be optimized before it’s automated. Because if you automate or optimize a bad process, all you’ve done is make bad results happen faster. And often times you may learn that what you thought you needed to automate shouldn’t be the priority. The companies that win with automation, AI, and process improvements aren’t just buying new tools—they’re mastering their processes first.

Before automating any process, ask yourself: Is the process itself effective? One of the most common mistakes in digital transformation is automating a broken or inefficient process. Automation doesn’t fix flaws — it amplifies them. That’s why process analysis must come before digitization. Revisit the objective. Remove unnecessary steps. Involve stakeholders. Then — and only then — think about automation. True transformation starts with asking the hard questions, not with buying the latest tool. Have you ever seen automation make things worse instead of better? #DigitalTransformation #ProcessImprovement #BusinessAutomation #SmartAutomation #ITStrategy

My first article! Fix the Process Before You Automate It: A Lesson Learned. In the world of distribution and logistics, automation is the current talk. The promise of faster throughput, reduced labor costs, and fewer mistakes is appealing. But after more than 25 years in the field, I have learned this: Automating a flawed process does not solve the problem. It amplifies it, making your problems even bigger and more present. Many big corporations have spent millions or even billions into it, to then revert back or feel the pain of lesser efficiencies. From receiving to picking to shipping, each step depends on the quality of the prior step. If your processes are over complicated or outdated, adding automation will not help. I have seen facilities install very advanced automation and conveyor systems only to discover that their true challenges came from unclear workflows, poor inventory management or unrealistic expectations. Technology is not a solution by itself. If it is built on top of broken processes, it will reinforce those problems rather than fix them. In many cases, automation creates a false sense of progress. What is really needed is a better foundation. Fixing the process means getting back to basics and simplifying. That includes walking the floor, asking the right questions, observing how work is done, and listening to the people who do it every day. These improvements build the solid ground that automation needs to succeed. When a process is stable and efficient, adding automation becomes easier and more effective. It also reduces the risk of failure and improves the return on investment. And trust me, the odds of an automation project failing are very real. I often remind teams to forget about the symptoms and go digging for the root causes of inefficiencies. Automation performs best when it supports a clear and well-designed process. Without that clarity, even the most advanced systems will fall short. Before moving forward with new equipment or systems, take a moment to reflect. Ask yourself if your current processes are working as well as they could be. If the answer is no, then the next investment should be in understanding and improving how your operation functions. That is where lasting and meaningful change begins. #automation #distribution #warehouse #processes