Designing For User Empathy

Adaptive seating solutions for individuals with disabilities leverage a variety of technologies to enhance comfort, mobility, and overall well-being. Amazing innovation? Some of the technologies commonly incorporated into these solutions include: Pressure Redistribution Technology: Purpose: To prevent pressure sores and enhance comfort. Examples: Air-cell-based cushions, gel cushions, memory foam. Smart Fabrics and Materials: Purpose: Provide flexibility, support, and enhance durability. Examples: Fabrics with moisture-wicking properties, anti-microbial materials. Powered Mobility Devices: Purpose: Enhance independent mobility. Examples: Electric wheelchairs, motorized scooters. Positioning Technology: Purpose: Support proper posture and alignment. Examples: Customizable seating components, tilt and recline features. Sensors and IoT Connectivity: Purpose: Monitor user comfort, health, and usage patterns. Examples: Pressure sensors, temperature sensors, IoT-connected devices. Assistive Technology Integration: Purpose: Enhance user control and interaction. Examples: Switch interfaces, sip-and-puff controls, eye-gaze technology. Customizable and 3D Printing: Purpose: Tailor solutions to individual needs. Examples: 3D-printed components for personalized fittings. Power-Assist Technology: Purpose: Aid manual wheelchair users. Examples: Electric add-on devices for manual wheelchairs. Vibration and Massage Features: Purpose: Improve circulation and reduce muscle tension. Examples: Seating with built-in massage or vibration elements. Advanced Cushioning Systems: Purpose: Provide optimal support and pressure distribution. Examples: Air-cell-based systems with adjustable firmness. Remote Control and Apps: Purpose: Allow users to adjust settings and monitor usage. Examples: Smartphone apps for controlling powered devices. Ergonomic Design Principles: Purpose: Ensure comfort and accessibility. Examples: Contoured shapes, adjustable components. Biometric Feedback Systems: Purpose: Monitor physiological indicators for health. Examples: Heart rate monitors, biofeedback systems. #innovation #mobility

🧠 UX & Psychology: Guides and Cheatsheets. With useful resources on how people think, decide, remember and focus attention — guides, glossaries, Miro/Figjam boards and cheat sheets ↓ 🤔 We think we know what others are thinking (we don’t!). 🤔 Too often we fill in gaps and detail from stereotypes. 🤔 We project our assumptions onto the past and future. 🤔 We tend to avoid or postpone irreversible decisions. 🤔 We edit and reinforce some memories after the fact. 🤔 We don’t see everything and we overlook details. 🤔 We simplify probability and numbers to make sense. 🤔 We are drawn to details that confirm our own beliefs. 🤔 We tend to believe things we choose to believe. 🤔 We transfer our experiences on other people. As GK VanPatter noted, what is often missing in conversations on cognitive biases are divergent thinking bias and convergent thinking bias, with the latter being by far the most prevalent. With the divergent thinking bias, we often generate too many ideas without properly evaluating their quality of feasibility. As a result, we at times resist making decisions and narrow down solutions, and hence often overlook obvious solutions. I definitely fall into that trap frequently — and then get lost in all the fine details, without a clear path forward. With the convergent thinking bias, we rely too much on logical analysis while totally ignoring emotional factors, and then fall prey to confirmation bias when evaluating solutions. So we rush towards a single right answer, and often skip or ignore the option of experimentation. Both of these biases can be very counterproductive when we try to innovate and find solutions to a given problem. They are often overlooked and forgotten — so watch out for them, and flag them for yourself and for your team when designing the next big thing. --- 💎 Useful resources: Psychology Insights Cookbook, by Jerome Ribot 👍🏽 Docs: https://lnkd.in/epGNUd9j Figma: https://lnkd.in/gHEU4R9Y Laws of UX, by Jon Yablonski 👍🏽 https://lawsofux.com/ Psychology UX Glossary, by Peter Ramsey 👍🏽 https://lnkd.in/ek9Pi-CG Cognitive Bias Cheat Sheet, by Buster Benson https://lnkd.in/eCGDp4mP Psychological Principles And How To Apply Them (Figjam), by Maryna Kucherova 🇺🇦, via Paweł Huryn 🇺🇦 https://lnkd.in/eQE2y5HG The Psychology of Design, by Dan Benoni, Louis-Xavier Lavallée https://lnkd.in/d5Z6TpVt Cognitive Biases Explained, by Krisztina Szerovay https://lnkd.in/eCxbBBS9 Behavioral Science Insights (Miro board), by Elina Halonen https://lnkd.in/eW5XgwDk The Big Behavioral Bias (Miro Board), by Robert Meza https://lnkd.in/ei-Xs-tD Behavioral Evidence Hubs 👍🏽 https://www.bhub.org/ https://www.besci.org/ #ux #design #psychology

HR doesn’t need more dashboards. It needs better listening. Most people teams measure what’s easy…like engagement scores or turnover. But the best teams? They build feedback loops that help them predict problems, not just react to them. This post gives you 11 of the most useful, often-overlooked loops you can implement across the employee lifecycle: 🟢 Week 2 new hire check-ins (capture early impressions) 🟠 Post-interview surveys (from both sides) 🔵 Onboarding reviews (day 90 is your goldmine) 🟡 Skip-level 1:1s (cross-level truth-telling) 🟣 Quarterly team health check-ins (lightweight, manager-led) …and 7 more. 📌 Save this if: • You’re building a modern HR function • You want fewer “We should’ve seen this coming” moments • You believe listening is strategy Which feedback loop is missing in your company?

64% of user stories fail to deliver value. Are yours in the majority—or the magic 36%? The problem isn’t agile. It’s how you’re framing user stories. Picture this: Your team’s sprint board is a sea of sticky notes. You’ve followed the “As a ___, I want ___, so that ___” formula. But stakeholders still ask, “𝗪𝗵𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝘃𝗮𝗹𝘂𝗲?” Sound familiar? In today’s “adapt or die” market, user stories that lack value are inefficient and pose existential risks. The secret isn’t in writing user stories—it’s in writing user stories that prioritize value. 1️⃣ Empathy ≠ Assumptions Mistake: Write stories based on what you think users need. 𝗙𝗶𝘅: 𝗘𝗺𝗯𝗲𝗱 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗱𝗮𝘁𝗮. Example: - A fintech team reduced feature churn by 40% by pairing user stories with Hotjar session recordings. Actionable Takeaway: > “𝘚𝘵𝘢𝘳𝘵 𝘦𝘷𝘦𝘳𝘺 𝘴𝘵𝘰𝘳𝘺 𝘸𝘪𝘵𝘩, ‘𝘞𝘦 𝘰𝘣𝘴𝘦𝘳𝘷𝘦𝘥 [𝘟 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘶𝘳], 𝘴𝘰 𝘸𝘦 𝘣𝘦𝘭𝘪𝘦𝘷𝘦 [𝘠 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯] 𝘸𝘪𝘭𝘭 𝘢𝘤𝘩𝘪𝘦𝘷𝘦 [𝘡 𝘰𝘶𝘵𝘤𝘰𝘮𝘦].’” 2️⃣ Outcome Over Output Mistake: Confusing tasks (“Build a login button”) with outcomes (“Reduce failed logins by 25%”). 𝗙𝗶𝘅: 𝗨𝘀𝗲 𝘁𝗵𝗲 𝗩𝗮𝗹𝘂𝗲 𝗖𝗮𝗻𝘃𝗮𝘀: 𝘞𝘩𝘦𝘯 [𝘴𝘪𝘵𝘶𝘢𝘵𝘪𝘰𝘯], 𝘐 𝘯𝘦𝘦𝘥 [𝘢𝘤𝘵𝘪𝘰𝘯], 𝘚𝘰 𝘐 𝘤𝘢𝘯 [𝘲𝘶𝘢𝘯𝘵𝘪𝘧𝘪𝘢𝘣𝘭𝘦 𝘰𝘶𝘵𝘤𝘰𝘮𝘦].  Example: Spotify’s “Discover Weekly” story focused on “Increase user engagement by 20% through personalized content”—not just “Build a playlist algorithm.” 3️⃣ The 5-Minute ‘So What?’ Test Mistake: Stories that survive sprint planning but die in retrospectives. 𝗙𝗶𝘅: 𝗔𝘀𝗸: - “If we don’t do this, what breaks?” - “Does this align with our Star Metric?” Data point: Teams using this test ship have 30% fewer “zombie stories” (The Standish Group). 4️⃣ Kill the ‘We’ll Figure It Out Later’ Lie Mistake: Vague acceptance criteria. 𝗙𝗶𝘅: 𝗕𝗼𝗿𝗿𝗼𝘄 𝗳𝗿𝗼𝗺 Amazon’𝘀 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝗕𝗮𝗰𝗸𝘄𝗮𝗿𝗱𝘀 𝗠𝗲𝘁𝗵𝗼𝗱: - Draft the press release first. Example: > “New feature X reduced onboarding time by 15% for 10K users in Q1.” 𝘐𝘧 𝘺𝘰𝘶 𝘤𝘢𝘯’𝘵 𝘸𝘳𝘪𝘵𝘦 𝘵𝘩𝘪𝘴, 𝘵𝘩𝘦 𝘴𝘵𝘰𝘳𝘺 𝘪𝘴𝘯’𝘵 𝘳𝘦𝘢𝘥𝘺. But here’s the twist: What if your user story isn’t about the user? (Hint: It’s about the ecosystem they operate in.) 𝗕𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂𝗿 𝗻𝗲𝘅𝘁 𝘀𝗽𝗿𝗶𝗻𝘁, 𝗔𝘂𝗱𝗶𝘁 𝟯 𝘂𝘀𝗲𝗿 𝘀𝘁𝗼𝗿𝗶𝗲𝘀 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗶𝘀 𝗰𝗵𝗲𝗰𝗸𝗹𝗶𝘀𝘁: ✅ Tied to a measured behaviour (not a guess) ✅ Defines a numeric outcome (not a task) ✅ Survives the “So What?” test ✅ Has a draft press release Teams that do this see 2.3x faster value realization (Forrester). “The goal of agile isn’t to finish sprints—it’s to deliver outcomes that matter.” - Jeff Patton ✅ TL;DR: Value-driven user stories = shorter sprints, happier users, fewer wasted $$$. Start with why and end with impact. P.S. Did you like this? Share it with your team—clarity is contagious. Let’s crowdsource brilliance—drop your take and tag a colleague who needs this. Image: Knowledge Train

🎧 #Storylistening for Instructional Designers (or how to get real stories from your SME instead of dry facts) 🗣️ Everyone talks about storytelling – and rightly so. Stories work! 💡 But what if your subject matter expert (SME) isn't naturally a storyteller? 🤔 Just listening to them recite a pile of facts? Not that helpful. 😐 You could find the same in Wikipedia. Or ask ChatGPT. 🤖 👉 So what should you do? Learn storylistening – the skill of not telling stories, but hearing them. 👂✨ 📌 The rules are simple: 1️⃣ Study the topic in advance – don't come in as an empty glass. 📚 2️⃣ Prepare questions – not as a checklist, but as a guide. 🧭 3️⃣ Listen carefully. And with curiosity. Yes, curiosity! 🧐 People tell better stories when they feel respected and heard. ❤️ 💬 Here’s a list of questions that truly encourage storytelling – the kind that brings examples, emotions, and turning points: 🎯 How did this process or approach first come into play in your work? 🛠️ Can you walk me through a specific situation where it worked especially well? 🌟 Tell me about a time when things didn’t go as planned – what happened? ⚠️ What’s the most surprising or unexpected thing you’ve encountered with this? 😲 Was there a turning point that changed how you see or use this? 🔄 What’s an example that you often use to explain this to others? 📖 Describe a situation where someone learned this the hard way. 🧠💥 Can you recall a moment when you or someone else had a breakthrough? 💡🎉 Tell me about a challenge you faced with this and how you overcame it. 🧗♀️ What real-life story do you think best illustrates the value of this process? 🏆 If I were watching this unfold in real time, what would I see? 🌈 And when the story starts flowing – don’t hold back: ✨ Really? Tell me more! ✨ Wow! That’s so unexpected. ✨ No way – what happened next? ✨ What were you thinking in that moment? ✨ And then? ✨ That’s brilliant – how did you come up with it? These questions aren't magic… But they create the space where real stories emerge. 🪄 And it's from these stories that strong, effective learning solutions are built. 🚀 #storylistening #LandD

LLMs are optimized for next turn response. This results in poor Human-AI collaboration, as it doesn't help users achieve their goals or clarify intent. A new model CollabLLM is optimized for long-term collaboration. The paper "CollabLLM: From Passive Responders to Active Collaborators" by Stanford University and Microsoft researchers tests this approach to improving outcomes from LLM interaction. (link in comments) 💡 CollabLLM transforms AI from passive responders to active collaborators. Traditional LLMs focus on single-turn responses, often missing user intent and leading to inefficient conversations. CollabLLM introduces a :"Multiturn-aware reward" system, apply reinforcement fine-tuning on these rewards. This enables AI to engage in deeper, more interactive exchanges by actively uncovering user intent and guiding users toward their goals. 🔄 Multiturn-aware rewards optimize long-term collaboration. Unlike standard reinforcement learning that prioritizes immediate responses, CollabLLM uses forward sampling - simulating potential conversations - to estimate the long-term value of interactions. This approach improves interactivity by 46.3% and enhances task performance by 18.5%, making conversations more productive and user-centered. 📊 CollabLLM outperforms traditional models in complex tasks. In document editing, coding assistance, and math problem-solving, CollabLLM increases user satisfaction by 17.6% and reduces time spent by 10.4%. It ensures that AI-generated content aligns with user expectations through dynamic feedback loops. 🤝 Proactive intent discovery leads to better responses. Unlike standard LLMs that assume user needs, CollabLLM asks clarifying questions before responding, leading to more accurate and relevant answers. This results in higher-quality output and a smoother user experience. 🚀 CollabLLM generalizes well across different domains. Tested on the Abg-CoQA conversational QA benchmark, CollabLLM proactively asked clarifying questions 52.8% of the time, compared to just 15.4% for GPT-4o. This demonstrates its ability to handle ambiguous queries effectively, making it more adaptable to real-world scenarios. 🔬 Real-world studies confirm efficiency and engagement gains. A 201-person user study showed that CollabLLM-generated documents received higher quality ratings (8.50/10) and sustained higher engagement over multiple turns, unlike baseline models, which saw declining satisfaction in longer conversations. It is time to move beyond the single-step LLM responses that we have been used to, to interactions that lead to where we want to go. This is a useful advance to better human-AI collaboration. It's a critical topic, I'll be sharing a lot more on how we can get there.

Trust isn't complicated. But most people get it wrong. Let me explain. I analyzed 500+ sales conversations and found something shocking: The highest-performing reps weren't using fancy trust-building techniques. They were using these 3 simple triggers that nobody talks about: 1. Real-time validation 🚫 Not customer logos 🚫 Not case studies 🚫 Not testimonials But showing prospects LIVE: → Who's viewing their content right now → Questions others are asking → Active engagement metrics Result? 73% higher meeting show rates. 2. Reverse referrals Instead of asking for referrals, document exactly: → How others found you → Their specific journey → Their exact results I tested this with 50 prospects: ✅ 41% response rate ✅ 28% meeting rate ✅ 19% close rate 3. Ambient reassurance Small, consistent actions that build trust: → Weekly performance updates → Public progress tracking → Regular capability proof My team's results: ✅ Trust scores up 47% ✅ Sales cycle shortened by 31% ✅ Close rates increased 22% Here's what nobody tells you: Trust isn't built through big gestures. It's built through small, consistent actions that prove you're reliable. I implemented these triggers last quarter: → Pipeline increased 52% → Close rate jumped 31% → Average deal size up 27% I’ve broken down this full framework above so you can study it, save it, and start applying it immediately. Remember: While others focus on complex trust-building strategies, these simple triggers consistently outperform. Ready to transform your trust-building approach? Let's connect. #SalesStrategy #TrustBuilding #B2BSales #GrowthHacking #RevenueLeadership

SXSW London! This week I presented "Empathy is the source for all great design" to a full room (400 people turned away because no additional space-darn!). I was left with a feeling that many in the creative class are in a crisis of change, with concerns about trust, erosion of accepted norms of integrity, AI displacing employment and anxiety about a collapse of empathy. Well! 100 years ago (almost precisely), Louis Kalff (the first Global Head of Design for Philips) penned the title of my talk. There are 4 key tools that bridge the empathy gap: 1.   Direct observation – there is no substitute for seeing customer pain points right where they are. Don’t listen – WATCH. People are notoriously unreliable at telling you what’s wrong and what their pain points are. This is particularly true for hospital workflows. 2.   Work backwards from the customer - Answer these key 5 questions: Who is your customer? What is their pain point or need? What benefit will our solution bring them? How do we know we are right and was this validated? What does it looks like? SHOW me the prototype. As Dennis Boyle from IDEO told me years ago, Don’t schedule a meeting unless you have a prototype to show me. :) 3.   Co-Create DIRECTLY with your customers – Don’t outsource your strategy to an agency. Work directly with your customers and solve their problems together because every customer is different and you will fail early to succeed sooner. 4.   Psychological Safety – One of the things I learned from the design (spaghetti tower) challenge that I presented at TED in 2006 is that the highest performing group of all (kindergarteners), succeeded over the worst performing group of all (business school students). Why? The kinders don’t spend half their time arguing about who is going to be CEO of spaghetti corporation. They just build and learn faster. Thesis: Status transactions are the death of innovation and leaders need to serve their teams and leverage that quiet brilliance of the introverts. And as a closing message I shared one of the key lessons in my quest to unlock the creative potential of other people: Invest in putting others above yourself – you will be rewarded. There is no win and no fail. There is Only MAKE.

When empathy meets design, magic happens. Doug Dietz's story is proof. Discover how he did it. As product managers, we are constantly looking for ways to improve user experiences and create meaningful results. At GE Healthcare, Doug Dietz transformed the MRI experience for paediatric patients, providing a compelling example. The Problem Despite building a cutting-edge MRI scanner, Dietz noticed a young patient's tremendous anxiety while using it. This revealed a key flaw in the machine's design: it did not account for children's emotional needs. The Use of Design Thinking Dietz used design thinking to redesign the MRI experience. 1/ Empathise: He spoke with kids in daycare centres and sought advice from child life experts to understand their viewpoints. 2/ Define: It was shown that 80% of young children needed anaesthesia because they were afraid of the MRI process. 3/ Ideate: To generate creative ideas, a varied team comprising volunteers, hospital employees, and specialists from a nearby children's museum worked together. 4/ Prototype: Developed the "Adventure Series," which turned MRI rooms into spaceships and pirate ships. 5/ Test: The Children's Hospital of Pittsburgh piloted the updated experience, which resulted in notable enhancements. The Results ↳Patient satisfaction scores increased by 90% ↳The need for sedation dropped from 80% to 10% ↳Anxiety levels in children decreased, making it easier for them to remain still during procedures ↳The reduced need for anesthesiologists allowed more patients to be scanned each day, improving efficiency and reducing costs The Key Takeaways for Product Managers 1/ Innovation Is Driven by Empathy: A thorough comprehension of user experiences can reveal unmet requirements and stimulate game-changing solutions. 2/ Reframe the problem: Dietz switched from focussing on the machine to developing the complete patient experience. 3/ Holistic Problem-Solving: More thorough solutions result from addressing the user experience's emotional and functional elements. 4/ Collaborative Ideation: Including a range of stakeholders encourages innovation and reveals fresh viewpoints. 5/ Iterative prototyping: Creating and testing prototypes in real-world contexts to validate ideas and inform necessary refinements. 6/ Measurable impact: The redesign enhanced operational effectiveness and patient experience. Doug Dietz's case study highlights how effective design thinking leads to transformative solutions for challenging problems in healthcare and beyond. Dietz and his colleagues developed a solution that not only soothed children's anxieties but also enhanced operational effectiveness and medical results by prioritising empathy and rethinking the entire process. Your Turn: ↳ How have you applied design thinking principles in your projects?  Share your thoughts in the comments below! 👍 LIKE this post, 🔄 REPOST this to your network and follow me, Monica Jasuja

Why inclusion and universal design need to come together We often hear organisations talk about diversity and inclusion. Yet inclusion alone isn’t enough if the systems we work within were never designed with difference in mind. A review by Shore and colleagues (2018) (https://lnkd.in/e6vjNAXM) looked at what makes workplaces truly inclusive. They emphasised fairness, authenticity, and equal access to opportunities. Their model shows that inclusion is not just about who is in the workforce, but whether everyone feels respected, valued, and able to participate fully. But here’s the challenge: many workplace practices are retrofits. Adjustments are made once someone discloses a need or points out a barrier. That can work but it’s often costly, time-consuming, and can unintentionally stigmatise the individual. This is where Universal Design (UD) comes in. Instead of waiting to respond, UD builds accessibility, flexibility, and usability into everyday business-as-usual. It reduces the number of case-by-case “fixes” by planning for variation from the outset. For example: Providing captions and transcripts in training as standard helps Deaf staff, those learning English, and anyone re-watching on mute. Clear communication, step-by-step checklists, and structured task tools reduce overload not only for neurodivergent employees but for everyone. Designing sensory-friendly workspaces supports those with sensory sensitivities—and also improves focus and wellbeing for the whole team. So how do the two approaches differ and align? Inclusion models focus on culture: creating fairness, authenticity, and psychological safety. Universal Design focuses on structures: embedding accessibility and flexibility into systems, tools, and environments. Bringing them together means leaders shape workplaces that are both fair and functional, inclusive and accessible. For employers, this isn’t just the right thing to do it’s efficient. Many UD approaches are low or no cost, but they reduce duplication, improve resilience, and make personalised support less stigmatising. 👉 Take away.... Inclusive practices creates the right mindset; Universal Design creates the mechanisms. Together, they help us move from patching barriers to preventing them.