Manufacturing Consulting Services

The majority of Industrial AI isn’t going into some futuristic, fully autonomous factory. It’s going into: • Catching defects • Keeping lines running • Fixing machines before they break That’s it. Over half the use cases are sitting right there in quality, production, and maintenance. What I found more interesting wasn’t the top of the list… it was the movement. 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐑&𝐃 𝐮𝐩 𝐚𝐥𝐦𝐨𝐬𝐭 𝟑𝐱. 😮 AI is starting to show up before anything hits the floor. Not just improving execution… influencing how things are designed, tested, and brought into production. This means different conversations and different people involved. And then there’s the part that made me laugh a bit…“Other” dropped by 70%. 🤣 Fewer side projects. More focus on the parts of the business that run every day. Also worth noting…You don’t see a category here that screams GenAI. Most of this is: • Vision • Time-series data • Operational models The kind of AI that doesn’t demo well… but does show up in results. My biggest takeaway from this chart: Companies are putting AI where: • The problem already hurts • The data already exists • The outcome actually matters to the business Not everywhere. Just where it counts. I wrote a deeper breakdown of what the latest Industrial AI data and trends reveal based on the huge amount of research conducted by IoT Analytics in their 399-page 2025 Industrial AI Report. 𝐅𝐮𝐥𝐥 𝐀𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/e2-GJZYJ ******************************************* • Visit www.jeffwinterinsights.com for access to all my content and to stay current on Industry 4.0 and other cool tech trends • Ring the 🔔 for notifications!

All planning is NOT the same. This infographic shows demand vs supply vs capacity planning: Main Objective ↳ Demand: forecast customer demand ↳ Supply: plan how to meet forecasted demand ↳ Capacity: ensure resources can meet the supply plan Type of Planning ↳ Demand: unconstrained ↳ Supply: constrained by materials, suppliers, production ↳ Capacity: constrained by labor, equipment, shifts, plant availability When in the S&OP Cycle ↳ Demand: demand review ↳ Supply: supply review ↳ Capacity: supply review Input ↳ Demand: sales data, market trends, promotions, historical demand ↳ Supply: demand forecast, inventory levels, supply constraints ↳ Capacity: supply plan, production rates, shift schedules, resource calendars Output ↳ Demand: forecasted demand  ↳ Supply: supply plan including procurement and production schedules ↳ Capacity: capacity plan (available vs. required capacity by period) Key Deliverable to S&OP ↳ Demand: aligned consensus forecast ↳ Supply: feasible supply plan ↳ Capacity: confirmation of capacity readiness or gaps Metrics ↳ Demand: forecast accuracy (MAPE, WMAPE), bias ↳ Supply: OTIF, inventory turns, service level ↳ Capacity: capacity utilization %, available hours, OEE Any others to add?

90% of companies stall before they’re able to scale. Not because the market changed. Not because the team isn’t capable. And certainly not because they lack vision. They stall because their operations can’t keep up with their growth. I’ve seen it over and over. The CEO is still making too many decisions. Processes live in people’s heads. Everyone’s working hard, but execution is inconsistent. So the team starts spinning. Firefighting replaces focus. And big goals turn into reactive checklists. When that happens, the fix isn’t more hustle. It’s operational discipline. But here’s the part most people miss: Operational excellence isn’t one big change. It’s a layered process. Built step by step. You start with standardization. Create one clear way to do the work. No more “everyone has their own method.” Then you move to automation. Eliminate repetitive tasks. Free up time for deeper work. Next comes measurement. Track the right numbers. Make them visible. Let the data guide your decisions. Then, layer in continuous improvement. Small weekly fixes. Fast iterations. Constant learning. Only then are you ready for real innovation. Not chaos disguised as creativity. Bold ideas that stick, scale, and move the business forward. This isn’t a theory. It’s how strong, sustainable companies actually scale. From startups to 8-figure teams, the pattern is the same. Build the layers in order. Tighten the engine before you step on the gas. Save this for when growth gets messy. Share it with your ops lead. Use it to make your business run smoother than ever. Curious... where do you think most teams stall? ♻️ Repost to help a leader in your network. — P.S. 📣 Ready to become a world-class CEO? Apply now to the Founder & CEO Accelerator Limited spots available. Learn more: https://lnkd.in/enG4XmRt P.S. Want a PDF of my Operational Excellence Cheat Sheet? Get it free here: https://lnkd.in/e5MBq3-x

AI agents and physical AI are shifting industrial automation from equipment supply to autonomous, self-optimizing systems. The most mature vendors are moving from pilots to production, with robots navigating complex environments and digital twins optimizing the value chain. This CB Insights brief gives a good view of where the top 20 industrial automation companies stand on AI maturity. Three key trends. 1. Leaders like Siemens Industry and ABB are linking AI systems across design, logistics, manufacturing, and maintenance creating compounding benefits. 2. Optimization dominates near-term priorities, while digital twins are emerging as the backbone for connecting hardware and software. 3. Partnerships with tech companies like Microsoft, Google, and Nvidia are essential, but they create new dependencies that must be managed. Siemens at the top of the ranking, combining copilots, edge platforms, and digital twins. Its work with Microsoft and Nvidia expands capabilities but increases reliance on external tech. Honeywell takes a more focused approach, embedding AI into devices and workflows. Its Qualcomm partnership highlights product-level integration over broad system building. ABB advances through its OmniCore platform and acquisitions such as Sevensense and SensorFact, blending robotics, software, and energy management. Schneider Electric pushes AI in energy management, using digital twins and partnerships with Nvidia, Microsoft, and Itron to extend from factory optimization into grid intelligence. The path forward in industrial AI is moving beyond pilots or isolated tools. It will depend on how well vendors embed AI into their platforms, link technologies across domains, and balance the benefits of external partners with the need for strategic independence. Those that will get it right will turn AI from experimentation into durable advantage. Just as critical is how their customers adopt these technologies. Industrial firms must shift from isolated use cases to embedding AI in design, production, energy, and logistics. Success requires not only advanced tools, but also the data, skills, and processes to make AI scale in complex operations.

🌱 Environmental Impact Assessment (EIA) Process Explained 1. 📌 Proposal Identification The process begins when a project proposal is submitted — like building a factory, dam, highway, etc. 2. 🔍 Screening Authorities decide if the project needs EIA. If it’s small or low-risk ➝ No EIA needed If it’s large or risky ➝ EIA Required Sometimes, an Initial Environmental Examination (IEE) is done to help make this decision. 3. 📢 Public Involvement At multiple points (like here or later), public can raise concerns or give suggestions. Their opinion matters in shaping the EIA. 4. 🧭 Scoping If EIA is needed, this step identifies what to study – air, water, soil, wildlife, people, etc. A Terms of Reference (ToR) is prepared. 5. 📊 Impact Analysis Detailed study of possible environmental impacts of the project — both positive and negative. 6. 🛡️ Mitigation and Impact Management Plans are made to reduce or manage the harmful impacts found in the analysis. 7. 📘 EIA Report Preparation All findings are compiled into a formal EIA Report, including baseline data, predicted impacts, and mitigation plans. 8. 🧪 Review Experts review the EIA report to check if it’s complete, accurate, and addresses all key issues. 9. ⚖️ Decision-making Authorities decide: ✅ Approved ➝ Project can begin with conditions. ❌ Not Approved ➝ Project is rejected or sent back. If rejected, the project can be redesigned and resubmitted. 10. 🚧 Implementation and Follow-up If approved, the project starts — but with regular monitoring to ensure environmental rules are followed. The results also help improve future EIA processes. 🔄 Public Involvement Throughout People can give input at various stages, not just at one point.

There is a lot to unpack with November’s trade data. One pattern that is appearing in sector after sector can only be termed a decoupling of US activity with the rest of the world. This is shown below for seasonally and price adjusted imports (top) and exports (bottom) of industrial and service machinery. This BEA end use category includes (i) Industrial engines & pumps; (i) food & tobacco processing machinery; (iii) machine tools, metal working machines; (iv) industrial textiles, sewing machines; (v) woodworking, glass working machines; (vi) pulp & paper machinery; (vii) measuring, testing & control instruments; (viii) materials handling equipment; (ix) other industrial machinery; and (x) photo & other service industry machinery. Both series are expressed as indexes where 100 = 2023. Thoughts: •The top chart shows a sharp drop in imported industrial and service machinery since February 2025. We have seen especially weak imports in September, October, and November that were down 14.3%, 14.6%, and 12.7% from prior year readings, respectively. •The bottom chart shows a sharp drop in US exports of such machinery. September, October, and November were down 11.5%, 3.8%, and 11.9% year-over-year, respectively. •These are significant trade categories. In 2024, nominal exports were $14.8 billion a month. Nominal imports were $20.7 billion a month. •Before anyone makes a comment in the form of “but this is good, this means companies are buying more American-made machinery,” that’s not how things tend to work with specialized producer goods like those captured in these categories. Rather, we see US manufacturers across many sectors investing less in machinery (hence the declining imports) while our own machinery manufacturers are losing access to export markets. Consistent with this argument, US machinery wholesalers’ price and seasonally adjusted sales were down 6.0% and 7.9% from the prior year in October and November per the Census Bureau’s real wholesale trade program. There is also an asymmetry here in that foreign producers are increasingly concerned about trade policy instability in the USA and will begin to turn elsewhere. US buyers of foreign machinery aren't looking at this issue the same way from my conversations. Implication: declining imports and exports of industrial machinery are a troubling sign. When you then factor in how rapidly machinery prices are rising based on PPI data, I‘m not anticipating strong capital investment by manufacturers in 2026 in new machinery. #supplychain #shipsandshipping #manufacturing #freight #trucking

When borders become strategic assets 🇫🇷🇨🇭 Today, HK Frankreich-Schweiz is unfolding a pilot project that could reshape how Europe approaches industrial competitiveness. #ThinkAct The strategic logic is clear: France brings scale-up infrastructure, R&D depth, industrial heritage. Switzerland delivers precision engineering, talent ecosystems, execution excellence. Separately, they’re strong. Together, they create complementary competitive advantage that Europe desperately needs. Three Strategic Pillars to start with: 🏭 Industrie & Manufacturing – Industry 4.0 transformation through advanced robotics, applied AI, industrial vision, digital twins. Real-time optimization across borders. 🔐 Cyber & SecureTech – Positioning France-Switzerland as European leader in sovereign cloud defense and industrial cybersecurity. Post-quantum infrastructure that matters. 👥 NextGen Talents – Identifying Scale-Ups catalyzing workforce transformation. Harmonizing academic and professional competencies without homogenizing regional strengths. This isn’t regional cooperation. It’s about European industrial sovereignty. Digital twins and AI now make cross-border industrial optimization possible at system level while maintaining regional specialization. The strategic question: Do we compete internally and lose globally? Or leverage complementary strengths? France-Switzerland is the pilot project. The implications are continental. With bilateral strategic leadership, and industrial leaders from both sides at the table today—this moves from concept to implementation. For those shaping industrial policy and investment strategy: What role does cross-border complementarity play in your European manufacturing future? #IndustrialStrategy #EuropeanSovereignty #ThinkActManufacturing

✈️ Alliance Strategy: Aviation's Greatest Strategic Paradox Alliance members collaborate extensively, coordinating schedules, sharing facilities, offering reciprocal benefits, while maintaining complete financial independence and competing directly for passengers and routes. This is the paradox! This cooperative competition model enables systematic advantages that individual airlines cannot replicate, yet successful airlines increasingly transcend alliance boundaries through strategic bilateral partnerships. Alliance membership delivers network scale across hundreds of destinations, coordinated market access, and operational efficiencies without massive capital investment, advantages that individual airlines simply cannot replicate independently. 𝗦𝘁𝗮𝗿 𝗔𝗹𝗹𝗶𝗮𝗻𝗰𝗲, 𝗦𝗸𝘆𝗧𝗲𝗮𝗺, 𝗮𝗻𝗱 𝗼𝗻𝗲𝘄𝗼𝗿𝗹𝗱 control 42.9% of global traffic through this cooperative competition model, demonstrating the strategic power of coordinated aviation networks. Despite aviation being the world's most global industry, regulatory restrictions prevent truly global airlines from emerging. Alliances became the innovative solution, enabling global reach while respecting national aviation sovereignty. LCC business models fundamentally conflict with alliance requirements: premium services, operational complexity, and reciprocal benefits directly oppose their cost optimization strategies. This isn't a strategic choice; it's operational incompatibility. 𝗪𝗵𝗮𝘁'𝘀 𝗜𝗻𝘀𝗶𝗱𝗲: • Alliance structures, competitive paradoxes, and market dominance analysis • Why LCC business models make alliance membership counterproductive • Strategic frameworks for alliance benefits versus trade-off evaluation • How cross-alliance partnerships transcend traditional boundaries through joint ventures and investments    The smartest airlines leverage alliance membership as their global foundation while selectively developing bilateral partnerships for specific advantages, it's portfolio optimization, not either/or decision-making. 𝗟𝗶𝗸𝗲 𝘁𝗵𝗶𝘀 𝗽𝗼𝘀𝘁: 💾 Save for future reference 🔄 Share with your aviation network 💬Comment below: Alliance member or independent, which strategy have you seen deliver better results in your aviation experience? #aviation  #airlinealliances  #aviationstrategy  #airlines  #air52insights  

Too many strategic alliances with Global System Integrators (GSIs) fail to deliver promised revenue. The #1 reason? They skip the basics — and then scale chaos. 👇 Here’s how to do it right. If you’re partnering with GSIs like Accenture, Capgemini, TCS, or Infosys, you already know they’re powerful growth channels — but only if your alliance is strategically designed, operationally aligned, and commercially activated. At Alliance Best Practice, we’ve studied over 800 high-tech alliances and found that commercial success with GSIs isn’t magic — it’s method. The most successful partnerships follow a repeatable pattern across three critical stages: 🔹 Initiation: Get the Foundation Right Secure real executive sponsorship (not lip service). Co-create a joint value proposition that solves real customer problems. Build a 12–24 month joint business plan with targets, priorities, and a shared “why now.” 🔹 Activation: Make It Real Launch field enablement with role-based playbooks, demos, and deal support. Identify 10–50 strategic accounts for joint pursuit. Share pipeline, assign pursuit leads, and celebrate early wins publicly. 🔹 Acceleration: Scale What Works Invest in repeatable, co-branded solution offerings. Launch joint marketing campaigns and track sourced/influenced revenue. Embed governance, metrics, and incentives that make the alliance sustainable. 💬 As one alliance leader told us: "If you can’t describe how the GSI makes money with you, they won’t put you in front of a client.” If you're building or rebooting a GSI alliance and want a proven roadmap — ✅ Read our latest article: Best Practices in GSI Alliances 📍 Now live on the Alliance Best Practice site: 🔗 https://lnkd.in/eJaHMXE #alliances #partnerships #GSI #channelstrategy #cosell #strategicalliances #growth #b2bpartnerships #alliancemanagement #hightech