Engineering Design Process Steps

"The Future of User Experience (UX) Might Not Be “UX” Anymore." That was one of the most thought-provoking insights from my recent conversation with Don Norman at the Book Passion Talk hosted by UX Unite and Helena Zilmer Levison in Denmark. He pointed out that the term UX has been trivialized, often reduced to just apps and websites. In fact, he’s even considered, through the IxDF - Interaction Design Foundation, rebranding it as "Design Experience." That struck me. But beyond that, here are my biggest takeaways from the session: 👩💻 Design teams need engineering representation. Having engineers involved from the start saves time and leads to stronger, more feasible solutions. 👬Designers must build relationships beyond design. Connecting with finance, marketing, and sales teams gives a holistic perspective of the business—expanding our impact beyond screens. 💡 Designers should be involved in product development from ideation, not just execution. We shouldn’t just be handed problems to solve—we should help define them. 🔹 Sustainable design matters. Aligning our work with the United Nations SDGs ensures we’re designing for the planet, not just for users. 🔬 Data-backed decisions always win. The best design arguments are evidence-based—let data tell the story. ✨ Personal reflection: This conversation reinforced the importance of cross-functional collaboration. As designers, our impact extends far beyond design tools—it’s about strategy, relationships, and systems thinking. I’d love to hear from you—which of these insights resonates most with you? And what are your thoughts on replacing UX with Design Experience? #UXDesign #DesignThinking #DonNorman #SustainableDesign #CrossFunctionalCollaboration

🧪 𝑪𝑨𝑵 𝑨 𝑷𝑹𝑶𝑻𝑶𝑻𝒀𝑷𝑬 𝑷𝑹𝑬𝑫𝑰𝑪𝑻 𝑻𝑯𝑬 𝑭𝑼𝑻𝑼𝑹𝑬? 𝑺𝑪𝑰𝑬𝑵𝑪𝑬 𝑺𝑨𝒀𝑺 𝒀𝑬𝑺 — 𝑩𝑬𝑪𝑨𝑼𝑺𝑬 𝑾𝑯𝑨𝑻 𝒀𝑶𝑼 𝑩𝑼𝑰𝑳𝑫 𝑹𝑬𝑽𝑬𝑨𝑳𝑺 𝑴𝑶𝑹𝑬 𝑻𝑯𝑨𝑵 𝑾𝑯𝑨𝑻 𝒀𝑶𝑼 𝑩𝑹𝑨𝑰𝑵𝑺𝑻𝑶𝑹𝑴. 🧠💡🔧🎯  ⠀⠀⠀⠀⠀⠀⠀⠀ 📊 𝑨 2023 𝒔𝒕𝒖𝒅𝒚 𝒇𝒓𝒐𝒎 𝑰𝑫𝑬𝑶 + 𝑺𝒕𝒂𝒏𝒇𝒐𝒓𝒅’𝒔 𝒅.𝒔𝒄𝒉𝒐𝒐𝒍 𝒇𝒐𝒖𝒏𝒅 𝒕𝒉𝒂𝒕 𝒆𝒂𝒓𝒍𝒚-𝒔𝒕𝒂𝒈𝒆 𝒑𝒓𝒐𝒕𝒐𝒕𝒚𝒑𝒊𝒏𝒈 𝒓𝒆𝒅𝒖𝒄𝒆𝒔 𝒅𝒐𝒘𝒏𝒔𝒕𝒓𝒆𝒂𝒎 𝒑𝒓𝒐𝒅𝒖𝒄𝒕 𝒆𝒓𝒓𝒐𝒓𝒔 𝒃𝒚 41%, 𝒊𝒏𝒄𝒓𝒆𝒂𝒔𝒆𝒔 𝒔𝒕𝒂𝒌𝒆𝒉𝒐𝒍𝒅𝒆𝒓 𝒃𝒖𝒚-𝒊𝒏 𝒃𝒚 57%, 𝒂𝒏𝒅 𝒂𝒄𝒄𝒆𝒍𝒆𝒓𝒂𝒕𝒆𝒔 𝒅𝒆𝒄𝒊��𝒊𝒐𝒏-𝒎𝒂𝒌𝒊𝒏𝒈 𝒄𝒚𝒄𝒍𝒆𝒔 𝒃𝒚 𝒖𝒑 𝒕𝒐 38%. ⚙️📈 ⠀⠀⠀⠀⠀⠀⠀⠀ 🧬 𝑾𝒉𝒚 𝑷𝒓𝒐𝒕𝒐𝒕𝒚𝒑𝒊𝒏𝒈 𝑾𝒐𝒓𝒌𝒔 (𝑺𝒄𝒊𝒆𝒏𝒕𝒊𝒇𝒊𝒄𝒂𝒍𝒍𝒚): 🔍 𝑰𝒕 𝒂𝒄𝒕𝒊𝒗𝒂𝒕𝒆𝒔 𝒅𝒖𝒂𝒍-𝒑𝒓𝒐𝒄𝒆𝒔𝒔𝒊𝒏𝒈 𝒊𝒏 𝒕𝒉𝒆 𝒃𝒓𝒂𝒊𝒏 — 𝒄𝒐𝒎𝒃𝒊𝒏𝒊𝒏𝒈 𝒂𝒃𝒔𝒕𝒓𝒂𝒄𝒕 𝒄𝒐𝒈𝒏𝒊𝒕𝒊𝒐𝒏 (𝒊𝒅𝒆𝒂) 𝒘𝒊𝒕𝒉 𝒔𝒆𝒏𝒔𝒐𝒓𝒊𝒎𝒐𝒕𝒐𝒓 𝒂𝒄𝒕𝒊𝒗𝒂𝒕𝒊𝒐𝒏 (𝒑𝒉𝒚𝒔𝒊𝒄𝒂𝒍 𝒓𝒆𝒂𝒍𝒊𝒕𝒚). 📥 That means: ideas move from "what if?" to "what now?" in real time. ⠀⠀⠀⠀⠀⠀⠀⠀ 🔁 Whether you're designing a SaaS interface or a smart medical device, prototyping: 🧩 Reveals friction early 🧪 Tests assumptions fast 🗣️ Triggers feedback loops 🔧 De-risks innovation ⠀⠀⠀⠀⠀⠀⠀⠀ 🎯 Use Cases That Prove It: • Apple’s ��30 Prototypes in 30 Days” rule 🖥️ • NASA’s mission modules tested in VR sims 🚀 • Toyota’s clay models — still used in 2025 🚗 ⠀⠀⠀⠀⠀⠀⠀⠀ 💬 So here’s a question that matters: 🔍 What’s the boldest lesson a prototype ever taught you? Did it kill a billion-dollar idea—or birth one? 🧠🔥 ⠀⠀⠀⠀⠀⠀⠀⠀ 📢 Share your prototyping story 💭 👥 Tag a design thinker, maker, or founder 🔗 🔔 Follow for more content on human-centered design, R&D strategy, and innovation testing frameworks 🧠🛠️🚀 ⠀⠀⠀⠀⠀⠀⠀⠀ 🌈 Real clarity doesn’t come from the whiteboard. It comes when your idea finally stands on its own legs. ⚙️ ⠀⠀⠀⠀⠀⠀⠀⠀ Credits: 🌟 All write-up is done by me (P.S. Mahesh) after in-depth research. All rights for visuals belong to respective owners. 📚    

As Product Managers it’s so easy to loose trust if features on the roadmap are not prioritised correctly. Here are 5 prioritization frameworks and when to actually use them: 1. RICE (Reach, Impact, Confidence, Effort) ✅ Use when: You have multiple ideas/features and want to prioritize based on expected impact. 📌 Best for: Growth experiments, new features, MVP ideas 💡Tip: Confidence % is often biased calibrate with data! 2. MoSCoW (Must have, Should have, Could have, Won’t have) ✅ Use when: You’re working with tight deadlines and multiple stakeholders. 📌 Best for: Sprint planning, product launches 💡Tip: Don’t let every stakeholder label everything as “Must have.” 3. Kano Model ✅ Use when: You want to balance delight with functionality. 📌 Best for: Customer-facing products 💡Tip: A feature that delights today might be expected tomorrow. 4. ICE (Impact, Confidence, Ease) ✅ Use when: You want a quicker version of RICE for fast decision-making. 📌 Best for: Rapid prototyping, early-stage prioritization 💡Tip: Use ICE when you don’t have a ton of data but still need to move. 5. Value vs. Effort Matrix ✅ Use when: You want to visualize trade-offs with stakeholders. 📌 Best for: Roadmap discussions, stakeholder alignment 💡Tip: Plot features on a 2×2: * Quick Wins (High value, low effort) * Strategic Bets (High value, high effort) * Time Wasters (Low value, high effort) * Fillers (Low value, low effort) So which one should you pick? Use RICE when you’re in a data-driven company. Use MoSCoW when time is tight and alignment is tough. Use ICE when you need speed > accuracy. Use Kano when delight matters. Use the Value/Effort Matrix when people keep asking, “Why this first?” 📌 Save this for your next prioritization war. 💬 Tried any of these at work? Drop your go-to framework in comments! #productmanager #job #PMjobs #learning #frameworks

𝗠𝗼𝘀𝘁 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝘀 𝗳𝗮𝗶𝗹 𝗳𝗿𝗼𝗺 𝗱𝗼𝗶𝗻𝗴 𝘁𝗼𝗼 𝗺𝘂𝗰𝗵, 𝗻𝗼𝘁 𝘁𝗼𝗼 𝗹𝗶𝘁𝘁𝗹𝗲. The difference between good PMs and the great ones lies in their ability to say "no" with conviction.  Prioritization isn’t about task management, it’s about strategic sacrifice. The frameworks you use determine whether you:   - Multiply impact (or spread teams thin)   - Build what moves the needle (or what’s loudest)   - Create category-defining products (or bloated ones)  𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝘁𝗵𝗲 7 𝗺𝗼𝘀𝘁 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 𝗱𝗲𝗰𝗼𝗱𝗲𝗱:  1️⃣ RICE – When you need to quantify "gut feel" (Score Reach, Impact, Confidence, Effort)   2️⃣ MoSCoW – For ruthless trade-offs (Must-have, Should-have, Could-have, Won’t-have)   3️⃣ Kano Model – To separate "delighters" from "basics" (Before competitors copy them)   4️⃣ Opportunity Scoring – When user pain points > feature ideas   5️⃣ Weighted Scoring – For stakeholder battles (Math beats opinions)   6️⃣ User Story Mapping – To prioritize features based on the user journey   7️⃣ Value vs Effort Matrix – The 2x2 that kills pet projects  Swipe for the breakdown on each framework! Your turn: Which framework has saved you from a disaster? (Or which one needs a funeral?) 👇  

🧪 Useful Guidelines and Calculators For UX Research (https://lnkd.in/dvf8fFsE), with practical guidelines for choosing the right sample sizes — from card sorting and tree testing to surveys and usability sessions ↓ --- 🔸 1. UX Research Is Not Validation UX research often serves as a way to “validate” already decided concepts and decisions. These decisions often happen before research even started. There, validation means merely accepting and confirming existing assumptions, rather than challenging or dismissing them. But the reason why we research isn’t to confirm — it’s to raise questions and red flags. It's also to reduce risk of wasting time and efforts on something that has little value and little impact. For that, we need to study behavior without any preconceived notions or affiliations. In other words, we shouldn’t validate — we should research instead. We need to be clear about what we want to learn, the questions we need to ask, research method to use and sample sizes to aim for. --- 🔹 2. Rules Of Thumbs For UX Research You don't need hundreds of participants to get started. With very limited amount of time and resources, I typically start with 5×45 mins interviews to spot critical blockers and unmet user needs. As we run sessions, I mark critical areas and record short screen share snippets — with consent — and make them visible in the company. For usability testing, 5 users per segment often reveal major issues; 10-15 users usually reach saturation. If new insights still emerge, the scope might be too broad. Instead of doing 20 interviews at once, run a small batch first (e.g. 5 sessions), analyze them and then decide if you need more. Test, adjust, test again. Here are a few rules of thumbs that I try to keep in mind: 1. Scale ≠ clarity: we must know what we’re trying to learn first. 2. Surveys: aim for confidence level 95%, margin of error 2–5%. 3. Interviews (open-ended): start with a baseline of 8 participants. 4. Distinct personas: at least 3–5 participants per persona. 5. Card sorting: invite 30+ participants to sort items independently. 6. Tree testing: invite at least 25 (better: 50) participants. 7. Task success: at 15–18 people success rates and times stabilize. 8. A/B Testing: smaller changes need larger sample sizes. 9. With surveys, aim for confidence level 95%, margin of error 2–5%. 10. Assume the response rate of 20–30% (incl. no-show-rate). 11. Nothing matters more than targeted and diverse sample Full article: https://lnkd.in/dvf8fFsE --- 🌻 My friendly, practical UX guides (15% off with 🎟 LINKEDIN): Smart Design Patterns → https://smashed.by/smart Design Patterns For AI → https://smashed.by/ai-ux Measure UX & Design Impact → https://measure-ux.com Happy designing, everyone — and thank you so much for reading! 🎉🥳 #ux #design

📘The Civil Brief 📑 Documentation Series Brief No. 33 – Safety in Design (SiD) Welcome to The Civil Brief, where we explore practical, well-grounded insights every civil engineer should know. This episode is part of the Documentation Series and focuses on integrating Safety in Design (SiD) principles throughout project stages. 💡 Why Safety in Design (SiD) Matters Design decisions made early in the project lifecycle can significantly reduce or eliminate health and safety risks for construction workers, operators, and future maintenance teams. SiD isn't just best practice—it's a statutory duty under the Work Health and Safety (WHS) Act 2011. 🛠️ Core SiD Principles in Civil & Infrastructure Projects ▪️ Risk Thinking in Design Embed SiD principles early—identify hazards across all life stages (construction, operation, maintenance, demolition). Use risk workshops to guide design decisions. ▪️ Risk Rating & Controls Rate risks using likelihood × consequence matrices. Apply the hierarchy of controls—always aim for elimination or engineering solutions before admin or PPE. ▪️ Documentation & Accountability Maintain a live SiD Register. Record design changes, risk treatments, and control measures. Use tools like Bluebeam for annotated drawings and clear design traceability. 🔧 Typical Safety in Design Workflow 1️⃣ Initiation & Roles Define project-specific WHS obligations (e.g., WHS Act 2011) and clarify design duty holders under the legislation. 2️⃣ Design Integration Conduct formal SiD workshops, capture design-stage risks, and continuously update the SiD Register through IFC, tender, and construction phases. 3️⃣ Collaborative Consultation Engage with construction, operations, and maintenance teams to validate risks and refine solutions, especially for access, traffic, and utilities. 4️⃣ Close-Out & Handover Package final SiD documentation with design deliverables. Clearly highlight residual risks and operational safety notes. ⚠️ Common Pitfalls ⛔ Rushing the design phase without risk workshops ⛔ Ignoring residual risks that can’t be designed out ⛔ Poor documentation—“if it’s not documented, it didn’t happen” Did You Know ❓ Under the WHS Act 2011, designers have a legal duty to ensure the structures they design are safe—not just during construction, but for the life of the asset. 📚 Relevant Legislation and Standards Work Health and Safety Act 2011 ISO 45001 – Occupational health and safety In future episodes of The Civil Brief, we will dive deeper into practical documentation tools and how they link to safe project delivery. Stay tuned! Islam Seif #TheCivilBrief #CivilEngineering #KnowledgeSharing

𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝗢𝘃𝗲𝗿 𝗜𝘀𝗼𝗹𝗮𝘁𝗶𝗼𝗻 Cross-functional engagement isn’t a buzzword-du-jour. It’s the only way architecture drives business value. How to put it into practice? Champion collaboration and cross-functional engagement over siloed operations and departmental barriers. Because no transformation, strategy, or architectural change succeeds in isolation. Silos create the illusion of control, but they cost you: • 𝗙𝗿𝗮𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 • 𝗥𝗲𝗱𝘂𝗻𝗱𝗮𝗻𝘁 𝗶𝗻𝘃𝗲𝘀𝘁𝗺𝗲𝗻𝘁𝘀 • 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝗻𝗴 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝗲𝘀 • 𝗦𝗹𝗼𝘄, 𝗶𝗻𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 Architecture’s work is to knit the enterprise together, not document the chaos from a distance. Great EA practices don’t just define standards; they also establish expectations. They enable collaboration that would not happen otherwise. They create shared language, forums, and alignment rituals that pull business, technology, design, and operations into one coherent system. When architects intentionally facilitate cross-team interaction, the payoff is immediate: • 𝗣𝗿𝗼𝗯𝗹𝗲𝗺𝘀 𝗴𝗲𝘁 𝘀𝗼𝗹𝘃𝗲𝗱 𝗳𝗮𝘀𝘁𝗲𝗿 • 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗯𝗿𝗼𝗮𝗱𝗲𝗿 𝗽𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲𝘀 • 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝘆 𝗴𝗲𝘁𝘀 𝗲𝗮𝘀𝗶𝗲𝗿 𝘁𝗼 𝗲𝘅𝗲𝗰𝘂𝘁𝗲 • 𝗧𝗲𝗮𝗺𝘀 𝗳𝗲𝗲𝗹 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽, 𝗻𝗼𝘁 𝗲𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗘𝗔 𝗶𝘀 𝗮 𝘁𝗲𝗮𝗺 𝘀𝗽𝗼𝗿𝘁. 𝗔𝗻𝗱 𝗰𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝘀 𝘁𝗵𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲. If your EA practice isn’t intentionally breaking down silos, it may be unintentionally reinforcing them. Where do you see the biggest barriers to cross-functional collaboration in your organization today? --- 🚀 Join 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐬’ 𝐇𝐮𝐛 – Join our newsletter and connect with a community that understands. Enhance your skills, meet peers, and advance your career! Subscribe 👉 https://lnkd.in/ephZvk4B ➕ Follow Kevin Donovan 🔔 ♻️ Repost | 💬 Comment | 👍 Like

1 + 1 = 11. That’s the new math of building products. This is the best time to be building. Not because AI makes everything easier, but because it makes “figuring out what NOT to build” incredibly fast. With tools like Figma Make, our PM can sketch an interface. Our engineer can turn it into a prototype in minutes. When someone says “I want to discuss this design,” my answer is simple: “Calling you right now.” No scrambling for calendar slots. No waiting days and weeks for alignment. Speed gives you wisdom. It teaches you what not to do. But here’s the thing: the idea is just 1% of building. The other 99%? Taste. Strategic thinking. Craftsmanship. Evaluation. Brainstorming together. And this is exactly why cross-functional collaboration matters more than ever. Designers see things PMs don’t. PMs see things engineers don’t. Engineers see things designers miss. We each bring a lens that sharpens the whole picture. That’s not inefficiency. That’s the whole point. The blurry lines between roles? They’re good for brainstorming and killing bad ideas quickly. But building something great still takes enormous effort from people with different expertise creating together. When priorities are clear and people have agency to solve problems, agility becomes an accelerator. Just do it. Don’t worry about stepping on toes. This is where culture matters most. Speed breakers rarely come from the work itself. They come from environments where people are afraid to brainstorm openly, challenge ideas, or move without permission. We don’t have enough time to build everything anyway. Why introduce artificial friction? Create the safe space. Trust the expertise around you. Move fast together. That’s how 1 + 1 becomes 11. #bettertogether

I had a fascinating conversation with Steve Quinlan of NatWest Group recently, and it really highlighted a fundamental issue in how many product teams approach experimentation. Too often, "experimentation" is seen as something that happens after a feature is built. This is the cart-before-the-horse. You've already invested significant time and resources, and now you're hoping to validate if it was worth it. True experimentation should be about validating and developing ideas before they enter serious development and as they go through design. Steve sits with a 'prototyping' function at Natwest created with this purpose in mind. They focus on de-risking development by rigorously testing and iterating on ideas early in the process. This approach not only saves valuable resources but also ensures that the final product truly meets customer needs. Moreover, Steve's team's work disambiguates from the narrow view that experimentation is just about A/B testing. It's about a broader, more strategic approach to product research, discovery and validation. It begs the question: how many product teams are missing out on this critical early-stage validation? How often are we building features based on assumptions rather than solid evidence, even if they are 'tested' before release? Shifting our mindset to prioritize prototyping and early-stage experimentation can revolutionize how we build products and drive innovation. How does your team ensure that experimentation is integrated into the entire product development lifecycle, not just tacked on at the end? #experimentation #cro #productmanagement #growth #digitalexperience #experimentationledgrowth #elg