One thing to keep in mind is to keep to task with the minimum viable product of what customers are willing to pay. Measure performance against your checklist.

Validation Goals need to be understood by your organization, including the stake holders prior to starting your project. Solid project development procedures (like a gated system) that are agreed prior to project validation is essential to a successful development effort.

Design validation goals should keep two additional items for consideration. - overall system design and functionality - End user experience (especially when design is for software products) Limiting the validation goal to individual part or independent feature discounts the overall improvement at system level which can cause counter productive effects than original design goal.

Ensure the product design meets the key customers’ requirements. Test the new design to collect feedback on design’s functionality, performances, environmental & regulatory requirements, ease of use, and overall user experience. Showcase the proto or the design concept at tech fair or exhibition to all the potential customers and get the feedback on the design in terms of their preferences, perceptions and satisfaction. In case, there are any important aspects of the design that are expressed by the key customers, make a conscious decision if they could be implemented in the design before first launching of the product. Post the news about the design on social media and analyze the heatmap to make an early assessment of impact.

Few critical things which measure : - Customer's requirements - Success criteria & metrics for validation - Risk & criticalities in design - User experience is the utmost to care of

One thing I’ve found helpful is to choose a combination of validation methods that suit your design goals, your resources, and your timeline. Some of the common validation methods are: - User testing: getting feedback from real or potential users by observing them using your design or a prototype. - Expert review: getting feedback from domain experts or peers who can evaluate your design against best practices and standards. - Data analysis: collecting and analyzing quantitative data from your design or a prototype, such as usage metrics, performance indicators, or user satisfaction scores. - Simulation: using mathematical models or software tools to simulate the behavior or performance of your design under different scenarios or conditions

I think that choosing the right validation method depends on the context and the purpose of the design. For example, user research is more suitable for exploring user problems and needs, prototyping is more suitable for testing design concepts and usability, MVP is more suitable for validating product-market fit, and A/B testing is more suitable for optimizing design elements and conversions. I also think that validation methods should be used iteratively and collaboratively, as design is an ongoing process that requires constant feedback and improvement.

There are different validation methods, we should choose our method/s depending on our design stages, goals and project requirements.

High-level steps to consider: 1) Check design against requirements and regulations 2) model/computer simulation and benchmarking 3) small scale and/or component testing, followed by 4) integrated and/or prototype (small or at scale) or demo (at scale) testing 5) live/commissioning testing 6) throw a project completion party (celebrate) after documenting lessons learned Depending on the specifics and degree of novelty of the new design, not all above steps may be needed. For example, only one or two of steps 2 to 4 may be needed. The others would all be needed, IMO.

Prototyping and Testing: Creating prototypes, whether physical or digital, allows for hands-on testing of functionality, durability, and performance. Usability, stress, and simulation testing identify issues early, refining the design to meet requirements and user expectations. User Feedback and Testing: Soliciting feedback from users via surveys, focus groups, or usability testing provides insights into preferences, needs, and pain points. Early user input ensures alignment with expectations and informs design improvements. By leveraging these methods, designers can minimize risks, optimize performance, and increase the likelihood of success for new products or innovations.

Using data-driven methods to gauge effectiveness. Here are some key techniques: - A/B Testing: Helps compare with the baseline with actual insights between design variations. - Customer/User Analytics: Analyzes how users interact and engage with the design based on their journey, engagements and other data analytics. - Customer interviews & surveys: Gathers structured feedback/preferences from customers via these methods to validate design hypotheses. - Expert & Internal user reviews: Involves expert designers, PO and internal reviews of designs during development stages using mockups/interactive prototypes. - Accessibility Testing: Use adaptive tools and align with accessibility guidelines, ensure it’s accessible to all users.

Gather your data with the precision of a detective and the curiosity of a scientist. Use every piece of feedback as a breadcrumb leading you closer to the truth. Analyzing this data isn’t just about numbers; it’s about uncovering the story behind the stats.

Efficiently gather data through chosen methods user testing, A/B testing, and more. Prioritize both quantitative and qualitative data for a holistic view. Employ analytics tools for in-depth insights. Ensure data integrity, meticulously analyze patterns, and draw actionable conclusions to inform your design refinement.

Once you've identified the key questions, the next step is to define what success looks like for your project. Success criteria are the benchmarks that indicate whether your design meets the intended goals, such as usability, performance, and user satisfaction. These criteria should be SMART: Specific, Measurable, Achievable, Relevant, and Time-bound. Alongside these criteria, you must determine the metrics that will be used to measure success. These could range from qualitative feedback from user testing sessions to quantitative data such as engagement rates or time spent using the app. Clear metrics enable you to assess the effectiveness of your design objectively and make data-driven decisions.

Once you've chosen your validation method, it's crucial to collect and analyse the data effectively. In Point 2 above, I have talked about methods of collecting data. Next, we will need to analyse the data. 1) Organise your data: Use spreadsheets, or note-taking apps to categorise and organise your collected data. 2) Identify patterns and trends: Look for recurring themes across the data. Do users consistently struggle with a specific feature? Are there certain design elements that evoke positive or negative feedback? 3) Don't focus on isolated comments: Focus on recurring issues mentioned by multiple users. 4) Analyse for both strengths and weaknesses: Identify areas where the design excels and areas that need improvement.

In my view, interpreting and communicating your validation results is a key step to share your findings and insights with your stakeholders, and to justify your design decisions and recommendations. Some of the tips for this step are: - Use clear and concise language: avoid jargon, technical terms, or acronyms that may confuse or alienate your audience. - Use visual aids and storytelling: use graphs, charts, images, or stories to illustrate your results and make them more engaging and memorable. - Highlight the main points and implications: summarize your results and explain what they mean for your design goals, your users, and your business.

Use knowledgeable others to refine your goals, choose validation methods, collect and analyse data, interpret and communicate results, iterate and improve design etc

From my perspective. I recommend to translate your data into actionable insights. Identify trends, patterns, and user feedback. Craft a clear narrative that communicates key findings. Share results with stakeholders, fostering a collaborative understanding. Effective communication of validation outcomes lays the foundation for informed decision-making and aligns your team toward design improvement.

Given the finite resources and time constraints typical in design projects, prioritizing and scoping your validation activities is essential. This involves assessing the risks and uncertainties associated with your design and focusing your validation efforts where the need for information is greatest and the impact on the final design is most significant. High-priority areas typically include aspects of the design that are innovative, areas with high user interaction, and features critical to the core functionality of the product. By prioritizing these areas, you can ensure that your validation efforts are focused on reducing the most critical risks to your project's success.

Interpreting results is the most interesting part of design validation. This is where you translate your findings into actionable insights for your design team and stakeholders. When interpreting results, make sure you go beyond the data and not just present raw numbers or user quotes. Explain the data and how it relates to your validation goals. Also, Identify the root cause, and try to understand the reason behind them. Lastly, prioritising the issues; as not all findings will have equal weight, focus on the most critical issues that significantly impact user experience or business objectives. Communicating results, focus on visuals and story telling. These have lasting impacts on the audiences. Also, provide actionable next steps!

Leverage validation insights for iterative design refinement. Adopt an agile mindset, incorporating feedback and analysis to enhance user alignment. Continuously refine elements collaboratively with your team, fostering an evolving, user-centric design. This cyclical process drives ongoing innovation and improvement.

Validation isn’t a one-and-done deal, it’s the beat to your design’s heart. Use the insights gained to refine, tweak, and enhance your design. Each iteration brings you closer to a product that doesn’t just meet expectations but exceeds them.

1. There is no right or wrong design, only designs that solve the correct problem and those that don't. 2. Design is meant to explain HOW we solve a problem. Without knowing WHAT we're trying to achieve and WHY, the risk is for personal bias to drive the design process by deciding what's important. 3. Everybody has opinions, especially when they care. But in reality nobody KNOWS what will happen after a change is made. Experimentation is key to validate these design assumptions. The sooner you confront your design to reality, the better.

Defining your validation goals at the outset of your design process is critical for ensuring that your validation efforts are strategic, focused, and efficient. By identifying the key assumptions, hypotheses, and questions that underpin your design, you establish a framework for what needs to be tested and answered before launch. Setting clear success criteria and metrics allows you to measure the outcomes of your validation activities objectively, providing a basis for decision-making and improvements. Lastly, prioritizing and scoping your validation efforts based on the risks and uncertainties of your design ensures that you allocate resources to the most impactful areas, ultimately leading to a more successful and user-centered design.

Siempre hacer mejora continua a los equipos que empleamos ,pero como logramos esto ? Fácil realizando Re-Ingenieria para mejorar el desempeño de la máquina. Invitar a los equipos de técnicos o ingenieros a participar en mejoras continuas de las máquinas

I recommend Corner case testing (CCT), which involves testing the design under extreme or unusual conditions to ensure its robustness and reliability. To do CCT effectively, analyze the design and user scenarios to identify edge cases, unusual inputs, or unexpected user behaviors that could occur. Create test cases specifically targeting these corner cases, including both positive and negative scenarios. Run the test cases systematically, ensuring that each corner case scenario is thoroughly tested to uncover any unexpected issues or vulnerabilities in the design. Monitor the results by paying attention to any deviations. CCT can identify and mitigate potential risks or weaknesses in the design before launch, enhancing its quality

Navigate the crucial waters of design validation with precision. Begin by immersing in the user journey to align seamlessly with expectations. Conduct rapid prototype tests, refining iteratively for a seaworthy design. Transform the process into a usability treasure hunt, fortifying against potential obstacles. A/B testing compares design variations empirically, guiding you to the most effective solution. Enlist your design team as expert sailors for a comprehensive review. Install a reality check wind gauge for technical feasibility and compliance. Lastly, ensure stakeholder alignment through expedition briefings. Each activity is a crucial anchor, collectively ensuring the success of your design launch into uncharted waters.

I remember when I was a junior engineer, I used to think that validation was a one-time activity that happened at the end of the design process. However, I learned that validation is an ongoing and iterative process that should happen throughout the design process. Validation helps you to: - Reduce risks and uncertainties: by testing your assumptions and hypotheses, and finding and fixing errors or flaws early on. - Increase user satisfaction and loyalty: by involving your users and meeting their needs and expectations. - Enhance innovation and quality: by discovering new insights and opportunities, and creating better solutions.

While defining the effectiveness of a design or project, cost is another key factor. In an ideal world with unlimited resources, we would always try to create the "best possible" outcomes. However, in real life, sometimes the "good is good enough" principle has helped my teams in the past. The 1.0 version of a design should try to meet the critical requirements and with every incremental release we can strive to achieve the North Star.

Validation should be from two perspectives: variability in production and variability in use. Validation model should check combinations of both. I agree with another comment- this needs to be repeated at significant intervals: when production changes, or when user needs or practice changes.