Simon Bernie 西蒙

Simon Bernie 西蒙Sep 28, 2026

Partnerships can open markets. Poorly structured partnerships can destroy momentum. Over more than 30 years working across technology, services, alliances and international markets, I have seen partnerships create opportunities that would have been difficult for either organisation to achieve independently. A partnership is announced with enthusiasm. Logos appear on presentations. An agreement is signed. Both organisations talk about the opportunity. Then very little happens. Why? Because 𝐚 𝐬𝐢𝐠𝐧𝐞𝐝 𝐚𝐠𝐫𝐞𝐞𝐦𝐞𝐧𝐭 𝐢𝐬 𝐧𝐨𝐭 𝐚 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩. Many organisations still treat partnerships primarily as a business development activity. I believe that when partnerships become material to growth, market expansion or delivery capability, they also become a 𝐛𝐨𝐚𝐫𝐝-𝐥𝐞𝐯𝐞𝐥 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐚𝐭𝐢𝐨𝐧. The partnership model can influence 𝐦𝐚𝐫𝐤𝐞𝐭 𝐚𝐜𝐜𝐞𝐬𝐬, 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐪𝐮𝐚𝐥𝐢𝐭𝐲, 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐭𝐫𝐮𝐬𝐭, 𝐝𝐞𝐥𝐢𝐯𝐞𝐫𝐲 𝐜𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐲, 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐛𝐫𝐚𝐧𝐝 𝐫𝐞𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧. They should understand 𝐰𝐡𝐲 𝐭𝐡𝐞 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬𝐡𝐢𝐩 𝐞𝐱𝐢𝐬𝐭𝐬, 𝐡𝐨𝐰 𝐯𝐚𝐥𝐮𝐞 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐜𝐫𝐞𝐚𝐭𝐞𝐝, 𝐰𝐡𝐨 𝐨𝐰𝐧𝐬 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧, 𝐰𝐡𝐚𝐭 𝐞𝐚𝐜𝐡 𝐩𝐚𝐫𝐭𝐲 𝐢𝐬 𝐜𝐨𝐦𝐦𝐢𝐭𝐭𝐢𝐧𝐠, 𝐡𝐨𝐰 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐦𝐞𝐚𝐬𝐮𝐫𝐞𝐝 𝐚𝐧𝐝 𝐰𝐡𝐚𝐭 𝐡𝐚𝐩𝐩𝐞𝐧𝐬 𝐰𝐡𝐞𝐧 𝐞𝐱𝐩𝐞𝐜𝐭𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐫𝐞 𝐧𝐨𝐭 𝐛𝐞𝐢𝐧𝐠 𝐦𝐞𝐭. Three disciplines make a significant difference. 𝟏. 𝐃𝐞𝐟𝐢𝐧𝐞 𝐬𝐮𝐜𝐜𝐞𝐬𝐬 𝐟𝐨𝐫 𝐛𝐨𝐭𝐡 𝐩𝐚𝐫𝐭𝐢𝐞𝐬. If only one organisation has a compelling reason to make the partnership successful, it will eventually lose momentum. Define measurable mutual outcomes from the beginning. 𝟐. 𝐄𝐬𝐭𝐚𝐛𝐥𝐢𝐬𝐡 𝐭𝐡𝐞 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐫𝐡𝐲𝐭𝐡𝐦 𝐛𝐞𝐟𝐨𝐫𝐞 𝐠𝐨𝐢𝐧𝐠 𝐭𝐨 𝐦𝐚𝐫𝐤𝐞𝐭. Agree executive sponsorship, opportunity ownership, sales engagement, enablement, governance, escalation and review cadence before the pipeline depends on them. 𝟑. 𝐌𝐞𝐚𝐬𝐮𝐫𝐞 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬, 𝐧𝐨𝐭 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲. Meetings, introductions and joint events demonstrate activity. They do not necessarily demonstrate value. Look at qualified pipeline, customer outcomes, revenue, market access, delivery performance and strategic value. The strongest partnerships I have experienced have one thing in common: 𝐁𝐨𝐭𝐡 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧𝐬 𝐤𝐧𝐨𝐰 𝐰𝐡𝐚𝐭 𝐭𝐡𝐞𝐲 𝐚𝐫𝐞 𝐭𝐫𝐲𝐢𝐧𝐠 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫, 𝐚𝐧𝐝 𝐰𝐡𝐨 𝐢𝐬 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐥𝐞 𝐟𝐨𝐫 𝐦𝐚𝐤𝐢𝐧𝐠 𝐢𝐭 𝐡𝐚𝐩𝐩𝐞𝐧. This is where boards and advisors can add considerable value. Not by managing the partnership, but by asking the questions that test whether the strategy, commercial model, governance and execution are genuinely aligned. I welcome conversations about how 𝐛𝐨𝐚𝐫𝐝-𝐥𝐞𝐯𝐞𝐥 𝐚𝐝𝐯𝐢𝐬𝐨𝐫𝐲 𝐚𝐧𝐝 𝐚𝐥𝐥𝐢𝐚𝐧𝐜𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 can strengthen the model. 𝐒𝐢𝐦𝐩𝐥𝐢𝐟𝐲. 𝐀𝐥𝐢𝐠𝐧. 𝐄𝐱𝐞𝐜𝐮𝐭𝐞.

Simon Bernie 西蒙Sep 30, 2026

𝐀𝐈 𝐢𝐬 𝐧𝐨 𝐥𝐨𝐧𝐠𝐞𝐫 𝐨𝐧𝐥𝐲 𝐚 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧. 𝐈𝐭 𝐢𝐬 𝐧𝐨𝐰 𝐚 𝐛𝐨𝐚𝐫𝐝-𝐥𝐞𝐯𝐞𝐥 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 𝐢𝐬𝐬𝐮𝐞. For several years, many organisations treated AI as experimentation. A proof of concept here. A chatbot there. A productivity tool introduced by one team. Another AI platform being tested somewhere else. AI is moving deeper into 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐬, 𝐩𝐫𝐨𝐜𝐮𝐫𝐞𝐦𝐞𝐧𝐭, 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬, 𝐜𝐲𝐛𝐞𝐫𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲, 𝐟𝐢𝐧𝐚𝐧𝐜𝐞, 𝐇𝐑, 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐬𝐮𝐩𝐩𝐨𝐫𝐭 𝐚𝐧𝐝 𝐜𝐨𝐫𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬. As that happens, the conversation needs to move beyond the CIO and technology team and into the boardroom. Not because directors need to become AI engineers. They don't. But I believe boards need enough 𝐀𝐈 𝐥𝐢𝐭𝐞𝐫𝐚𝐜𝐲 𝐭𝐨 𝐚𝐬𝐤 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐭𝐡𝐞 𝐫𝐢𝐠𝐡𝐭 𝐚𝐬𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧𝐬. Where is AI already being used across the organisation? What data is it accessing? What decisions is it influencing or making? Who is accountable when AI contributes to a decision? What happens when the model is wrong? Where are the human decision gates? How are cybersecurity, privacy, bias and regulatory obligations being considered? And perhaps one of the most important questions: 𝐇𝐨𝐰 𝐝𝐨 𝐰𝐞 𝐤𝐧𝐨𝐰 𝐀𝐈 𝐢𝐬 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐯𝐚𝐥𝐮𝐞 𝐫𝐚𝐭𝐡𝐞𝐫 𝐭𝐡𝐚𝐧 𝐬𝐢𝐦𝐩𝐥𝐲 𝐜𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐦𝐨𝐫𝐞 𝐀𝐈 𝐚𝐜𝐭𝐢𝐯𝐢𝐭𝐲? For me, three actions should agenda. 𝟏. 𝐌𝐚𝐩 𝐭𝐡𝐞 𝐀𝐈 𝐟𝐨𝐨𝐭𝐩𝐫𝐢𝐧𝐭. Understand where AI is already being used, including tools introduced outside formal technology programmes. You cannot govern what you cannot see. 𝟐. 𝐄𝐬𝐭𝐚𝐛𝐥𝐢𝐬𝐡 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐛𝐞𝐟𝐨𝐫𝐞 𝐬𝐜𝐚𝐥𝐢𝐧𝐠. Define ownership, decision rights, human oversight, escalation, controls and evidence requirements for AI-enabled processes. Responsible AI needs an operating model, not simply a policy document. 𝟑. 𝐂𝐨𝐧𝐧𝐞𝐜𝐭 𝐀𝐈 𝐢𝐧𝐯𝐞𝐬𝐭𝐦𝐞𝐧𝐭 𝐭𝐨 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬. Every meaningful AI initiative should have a reason to exist. Productivity. Customer experience. Revenue. Risk reduction. Operational resilience. Better decisions. Accessibility. Or another clearly defined business outcome. It should be to create the conditions in which the organisation can adopt AI 𝐰𝐢𝐭𝐡 𝐠𝐫𝐞𝐚𝐭𝐞𝐫 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞, 𝐚𝐜𝐜𝐨𝐮𝐧𝐭𝐚𝐛𝐢𝐥𝐢𝐭𝐲 𝐚𝐧𝐝 𝐝𝐢𝐬𝐜𝐢𝐩𝐥𝐢𝐧𝐞. Because the question facing boards is no longer: “𝑆ℎ𝑜𝑢𝑙𝑑 𝑤𝑒 𝑏𝑒 𝑡ℎ𝑖𝑛𝑘𝑖𝑛𝑔 𝑎𝑏𝑜𝑢𝑡 𝐴𝐼?” It is increasingly: “𝐃𝐨 𝐰𝐞 𝐮𝐧𝐝𝐞𝐫𝐬𝐭𝐚𝐧𝐝 𝐰𝐡𝐞𝐫𝐞 𝐀𝐈 𝐢𝐬 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐢𝐧𝐟𝐥𝐮𝐞𝐧𝐜𝐢𝐧𝐠 𝐨𝐮𝐫 𝐨𝐫𝐠𝐚𝐧𝐢𝐬𝐚𝐭𝐢𝐨𝐧, 𝐚𝐧𝐝 𝐚𝐫𝐞 𝐰𝐞 𝐠𝐨𝐯𝐞𝐫𝐧𝐢𝐧𝐠 𝐢𝐭 𝐚𝐩𝐩𝐫𝐨𝐩𝐫𝐢𝐚𝐭𝐞𝐥𝐲?” I welcome conversations about AI governance, board readiness and turning AI ambition into measurable business outcomes. 𝐒𝐢𝐦𝐩𝐥𝐢𝐟𝐲. 𝐀𝐥𝐢𝐠𝐧. 𝐄𝐱𝐞𝐜𝐮𝐭𝐞.

Simon Bernie 西蒙Sep 29, 2026

Most engineering/construction capital projects don't lose time in construction. They lose it in FEED (front end engineering design) Before a single pipe is ordered, every facility goes through the same loop: Room Design Basis and Room Data Sheets → 20-30 primary engineering drawings → BOQ and a ballpark estimate → Engineering and regulatory compliance checks → FEED approval, then detailed engineering. On paper, it's one workflow. In practice, it's five disconnected handoffs. Every change to a room's grade, pressure or air changes ripples through HVAC layouts, ceiling plans, utility drawings, quantities and compliance reviews, and most of that rework is still done by hand. The result: weeks of iteration, compliance gaps found late, and cost estimates that trail the design they're meant to describe. The shift I'm seeing is simple but significant. Treat the Room Data Sheet as the single source of truth, and let everything downstream be generated and validated from it: • Drawings produced from the design basis, not redrawn for every revision • Compliance scored against GMP, cleanroom, HVAC and local codes as the design evolves, with suggested fixes • Quantities and cost estimates that update with the design • A complete FEED docket (Room Book, layouts, 3D walkthrough, regulatory alignment, capital requirements) ready for a confident approval decision That's the approach behind EPC Flux AI, which we're bringing to pharma and process owners, EPCs and PMCs. Swipe through to see how the FEED workflow comes together. If you're planning a new facility or expansion and want to see this on your own project, send me a DM or reach me at [email protected] or +6591077910 at Goh Bernie Advisory. I will be at Data Centre World Asia 2026, 29-30 Sept, at Marina Bay Sands Expo & Convention Centre, Basement 2, Level 1 and Level 3. If you are around, let's meet up and discuss. #PharmaEngineering #FEED #CapitalProjects #EPC #GMP #Cleanroom #AIinEngineering #DigitalTransformation #GohBernie #GohBernieAdvisory Technology Partnership: Data Nectar (Data, Gen AI Consulting & Solutions) & Dhiren C.