End-User Validation Processes

User Feedback Loops: the missing piece in AI success? AI is only as good as the data it learns from -- but what happens after deployment? Many businesses focus on building AI products but miss a critical step: ensuring their outputs continue to improve with real-world use. Without a structured feedback loop, AI risks stagnating, delivering outdated insights, or losing relevance quickly. Instead of treating AI as a one-and-done solution, companies need workflows that continuously refine and adapt based on actual usage. That means capturing how users interact with AI outputs, where it succeeds, and where it fails. At Human Managed, we’ve embedded real-time feedback loops into our products, allowing customers to rate and review AI-generated intelligence. Users can flag insights as: 🔘Irrelevant 🔘Inaccurate 🔘Not Useful 🔘Others Every input is fed back into our system to fine-tune recommendations, improve accuracy, and enhance relevance over time. This is more than a quality check -- it’s a competitive advantage. - for CEOs & Product Leaders: AI-powered services that evolve with user behavior create stickier, high-retention experiences. - for Data Leaders: Dynamic feedback loops ensure AI systems stay aligned with shifting business realities. - for Cybersecurity & Compliance Teams: User validation enhances AI-driven threat detection, reducing false positives and improving response accuracy. An AI model that never learns from its users is already outdated. The best AI isn’t just trained -- it continuously evolves.

As BA, our goal is to bridge the gap between business needs and technical solutions, ensuring that end-user requirements are met with precision. One of the most potent tools in our arsenal? 𝐖𝐢𝐫𝐞𝐟𝐫𝐚𝐦𝐞𝐬. 🎨 𝐖𝐡𝐲 𝐖𝐢𝐫𝐞𝐟𝐫𝐚𝐦𝐞𝐬? ✅ Clarity: Wireframes transform abstract requirements into tangible visuals, helping stakeholders see and understand the proposed functionalities without distractions. ✅ Collaboration: They facilitate meaningful discussions by providing a common ground for feedback from both technical teams and non-technical stakeholders. ✅ Efficiency: Early use of wireframes can significantly reduce the need for changes during later development stages, saving time and resources. 𝐄𝐱𝐚𝐦𝐩𝐥𝐞: How Business Analysts Use Wireframes 𝐒𝐜𝐞𝐧𝐚𝐫𝐢𝐨: Imagine a project where a Business Analyst (BA) is working with a team to develop a new online booking system for a boutique hotel chain. The goal is to enhance user experience by simplifying the booking process. ✅ 𝐄𝐥𝐢𝐜𝐢𝐭 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬 The BA conducts interviews and observation sessions with front-desk staff, hotel management, and surveys frequent guests to gather requirements. From these interactions, the BA identifies key functionalities like room selection, booking modifications, and loyalty rewards integration. ✅ 𝐂𝐫𝐞𝐚𝐭𝐞 𝐈𝐧𝐢𝐭𝐢𝐚𝐥 𝐖𝐢𝐫𝐞𝐟𝐫𝐚𝐦𝐞𝐬 Using a tool like Balsamiq, the BA develops initial wireframes that outline the basic layout and interaction points of the booking system. These wireframes show the position of elements such as the room selection dropdown, date pickers, and special request forms. ✅ 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬 The BA presents these wireframes in a workshop with stakeholders, including hotel staff and a few select guests. During the session, the BA walks through the user journey with the wireframe, discussing how each element meets the requirements gathered earlier. For example, showing how the loyalty rewards section provides clarity and value to frequent guests. ✅ 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐞 𝐚𝐧𝐝 𝐈𝐭𝐞𝐫𝐚𝐭𝐞 Stakeholders provide feedback on the wireframes, suggesting improvements such as adding a visual calendar view for selecting dates and a feature to compare room types. The BA iterates on the wireframes, incorporating feedback and presenting updated versions in follow-up sessions. ✅ 𝐅𝐢𝐧𝐚𝐥 𝐕𝐚𝐥𝐢𝐝𝐚𝐭𝐢𝐨𝐧 Once all feedback is integrated and stakeholders are satisfied, the final wireframe is approved. It serves as a blueprint for the development team and a reference for further usability testing. 👥 Engage and Validate By engaging stakeholders with wireframes, we validate requirements early, adjust quickly, and avoid costly misunderstandings. It's not just about drawing screens; it's about drawing conclusions from user interactions and feedback. BA Helpline

Product validation does not usually make headlines. But in hearing health, it is one of the most consequential moments in the life of a product. It is the point where months or years of development stop being theoretical. Where decisions have to work not just in concept, but in practice. In clinics. In conversations. In everyday life. In a recent conversation with Maddie Olson, Au.D. on the Starkey Hearing Sound Bites Podcast, she described product validation as the culmination of the entire development process. Everything should be in its final form before a product ever reaches a patient or a provider. Sound quality. Accuracy. Regulatory confidence. All of it has to meet a very high bar. One comment in particular stayed with me. Matching to target is non‑negotiable. If that standard is not met, nothing else matters. What also stood out was Maddie’s perspective on bias. When you are deeply embedded in product development, it is easy to assume you fully understand provider needs. Experience helps, but proximity can also limit perspective. That is why her team intentionally brings in external audiologists and clinicians through usability studies and market research. Not to validate assumptions, but to challenge them. While provider needs are considered, the central focus remains the patient. The end user. The person who will live with this technology every day. That balance matters. Progress in hearing health depends on respecting clinical realities while never losing sight of the patient experience. When those two priorities align, innovation earns trust.

Design validation testing and human factors Validation Human factors (HF) validation and user interface (UI) design validation are both performed at the end of a product’s development to ensure that the product is suitable for its intended use, users, and use environments, but each with a slightly different scope. Whereas HF validation testing is conducted to generate data related to whether users can interact with the product safely and effectively, UI design validation is conducted to yield evidence that the product meets users’ needs.   Noting the similarities between HF validation and user interface design validation, manufacturers might wonder how they can combine these activities. Incorporating design validation activities into human factors validation testing can be an excellent use of time and resources. This is especially true when the combined human factors and design validation test sessions are short enough that participants are not fatigued by the session’s end, enabling them to participate fully and generate robust data. Furthermore, combining these activities is useful from a recruiting perspective, noting you can recruit one set of participants for the combined session rather than recruiting one set of participants for each activity.  Consider the following best practices to ensure you are integrating user interface design validation elements into HF validation testing is a smooth and productive endeavor:  Understand the scope of HF validation and UI design validation activities. For the HF validation test, you will have participants complete use scenarios and knowledge tasks encompassing all critical tasks, and many of these activities will likely be important for user interface design validation as well. Ensure you have a clear understanding of what activities must be performed for the HF validation as well as the UI design validation such that you can determine what additional activities should be added for UI design validation. Furthermore, consider if you need to collect additional data from the HF validation test activities beyond what is traditionally planned (e.g., dominant hand used, glove size, task time).   Complete HF validation test activities before user interface design validation questions. Noting the necessary rigor in an HF validation test to avoid bias and represent a realistic interaction, you should not ask any UI design validation questions until you have completed all HF validation test activities. Completing the HF validation test activities would include completing any debrief on use scenarios and knowledge task performance, as well as any further subjective feedback questions. Furthermore, if there are additional hands-on activities required to validate the UI design elements that were not already encompassed within the HF validation test, you should also wait until completing the HF validation test activities to proceed with these UI design validation activities.  

"Hope it works" is not a QA testing strategy. You can end up with code that passes every test, but the platform fails to meet actual user needs. I see this pattern repeatedly in complex implementations. Teams run technical tests, check all the boxes, then wonder why their business processes collapse after go-live. Here's what most miss: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝘁𝗲𝘀𝘁𝗶𝗻𝗴 ≠ 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 ➡️ Technical testing asks: "Are we building the product right?" ➡️ Business validation asks: "Are we building the right product?" Verification confirms that the software meets all technical specifications, which sets a solid foundation for the validation phase. During validation, the software is tested from the user's perspective. Your order-to-cash process might technically function while completely breaking your sales workflow. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗵𝗮𝗽𝗽𝗲𝗻𝘀: Manual business validation is time-consuming, so teams skip it. Resource constraints push business process validation to "later" (which becomes never). James Bach warns us: "The testing mindset is a sophisticated and difficult thing to achieve. You can't be in the testing mindset while you are in the building mindset. They fight each other." 𝗪𝗵𝗮𝘁 𝘄𝗼𝗿𝗸𝘀 𝗶𝗻𝘀𝘁𝗲𝗮𝗱: ✅ Embed QA throughout development, not as an afterthought. ✅ Test real-world business scenarios, not just code functions. ✅ Automate both technical verification AND business process validation. ✅ Engage stakeholders actively during QA and user acceptance phases. ✅ Foster a culture where quality is everyone's responsibility. But it's the difference between project success and costly failure. Don't let your next implementation fall into the "hope it works" trap. What's your experience with balancing technical testing and business validation? #QualityAssurance #SoftwareTesting #ProjectManagement #DigitalTransformation #SoftwareDevelopment #TechLeadership #BusinessProcesses #QAStrategy #SystemsImplementation #TechnicalLeadership #EnterpriseSoftware #SoftwareQuality #TestingStrategy #BusinessValidation #ProjectSuccess #TechStrategy #SolutionsArchitecture #Consulting #TechConsulting #QAProcess #Excellence #Delivery #ProjectDelivery #Technology #B2B #B2BCommerce #eCommerce #ERP #Integration #Software #SoftwareDevelopment

What is (CSV) ? CSV is the documented process of verifying that a computer-based system performs its intended function accurately and consistently while meeting regulatory standards, such as FDA's 21 CFR Part 11 or EMA Annex 11. It involves assessing systems used in activities like production, quality assurance, clinical trials, and more. Why is CSV Important? 1. Regulatory Compliance 2. Data Integrity 3. Risk Mitigation 4. Operational Efficiency Examples of Computerized Systems Requiring Validation 1. Laboratory Information Management System (LIMS) Tracks samples and associated data during quality control testing. Validation ensures data traceability and accuracy. 2. Enterprise Resource Planning (ERP) Systems Manages manufacturing, inventory, and supply chain. Validation ensures system-generated reports are reliable and accurate. 3. Electronic Batch Records (EBR) Automates batch manufacturing documentation. Validation guarantees proper tracking of deviations, approvals, and compliance. 4. SCADA Systems (Supervisory Control and Data Acquisition) Monitors and controls pharmaceutical production processes. Validation ensures accurate real-time data capture and alarm handling. 5. Environmental Monitoring Systems Tracks conditions like temperature, humidity, and particle counts in cleanrooms. Validation ensures reliable data critical for product quality. Steps in CSV :- 1. Risk Assessment Identify the system's impact on product quality and compliance. 2. Validation Planning Develop a Validation Master Plan (VMP) outlining scope, timelines, and responsibilities. 3. Testing (IQ, OQ, PQ) IQ: Verifies system installation. OQ: Confirms system operation within specified limits. PQ: Ensures performance under actual conditions. 4. Documentation Maintain thorough records, including protocols, test scripts, and deviation reports. 5. Periodic Review Revalidate systems regularly or after significant changes to ensure continued compliance.

Software's silent killer: skipping validation. This fatal mistake wastes $50K+ in developer time and kills 7 out of 10 projects before launch. The truth is harsh: 70% of software projects fail globally, and customers NEVER use 45% of features. Developers waste half their time fixing preventable bugs while morale tanks and relationships turn adversarial. Verification ensures that the code works as designed. Validation ensures you're solving problems worth solving. My 3-day validation framework: Day 1: Define your assumptions. What problem exists? Why your solution? Who pays and how much? Dropbox validated with just an explainer video—scoring 70,000 sign-ups overnight. Day 2: Build a minimum viable prototype. It could be manual service, landing page, or mockup. The Zappos founder photographed local store inventory and fulfilled orders by buying retail. Sell first, build second. Day 3: Test with real users. Watch what they do, not what they say. One team discovered that 82% of users were confused by their core feature. By pivoting, they saved $63K and achieved 3x higher adoption. The ROI? $500K saved annually, 75% fewer debugging costs, and 92% faster execution. Avoid these traps: mistaking opinions for data, overbuilding, ignoring feedback, and asking leading questions. "No market need" causes 35% of startup failures. Three days of validation saves months of wasted development. Test your idea or join the 70% who are failing. The best operators choose execution over wishful thinking. Follow me for more software, cybersecurity insights and execution strategies that work.

Have you ever assumed you knew exactly what your users wanted, only to discover something unexpected once they started using it? Whether you’re developing software or building a little backyard pond, it’s crucial to actually observe how end users interact with your creation. The idea is to start with a Minimum Desirable Product (MDP) - a stripped -down version that’s good enough for users to begin engaging with. Then, by watching their behavior - where they get comfortable, where they stumble - you can adjust the design to address genuine needs rather than guessing what might work. Here’s how to keep the process on track: - Start Simple: Launch with the core elements only. This helps you pinpoint what’s truly important and avoid feature overload. - Observe & Learn: Pay close attention to actual usage. Where do they linger, what do they avoid, and where do they need more guidance? - Refine with Purpose: Don’t just add bells and whistles. Focus on solving real issues so every enhancement serves a clear purpose. In essence, it’s all about feedback loops. The more you check in with actual users, the less likely you are to waste time on stuff they don’t actually want. What methods have worked best for you in gathering real-world user insights? #innovation #technology #future #management #startups

This past week, I gave a brief intro to the ‘secret sauce’ behind Frogslayer’s 97% success rate: the VDP. Let’s dive into some specifics about the first step in our VDP process: Validation. Validation is all about confirming the need for your product and how it supports your business goals. Here's what happens during the Validation phase: 1️⃣ Kickoff Workshop We start with a deep dive into your project's background, identifying problems, needs, and risks. We'll craft a business model canvas, product strategy, and even initial user personas. 2️⃣ Research & Discovery Our team conducts stakeholder interviews, user surveys, and field studies. We refine personas, map out user journeys, and develop contextual scenarios. 3️⃣ Product Hypothesis & Validation We prioritize and test user needs, plan the business model, and validate the initial product strategy. By thoroughly validating your idea, we make sure we’re building the right product for the right audience. The next step in the VDP phase is Design, which we’ll dive into in a future post! For now, what’s been your experience in doing this ‘prep work’ to validate your product ideas?