Raise Your Confidence by Strategically Stacking Evidence

Late-stage design just hit a snag—now comes the moment that separates guesswork from great engineering. We walk through a clear, repeatable method to investigate unexpected failures and make high-impact decisions with confidence. Instead of hunting for a perfect test, we set a confidence target and stack multiple forms of imperfect evidence until we close the gap.

If you’re navigating late-stage product development and want a calm, methodical way to move from 40% to 90% confidence, this framework will help you choose the next best step, allocate limited time and budget, and know when to stop.

Join the Substack for monthly guides, templates, and Q&A where I help you apply these to your specific projects. Visit qualityduringdesign.substack.com.

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Stop Risk Theater, Start Real Decisions

We break down why risk analyses often become risk theater and replace them with a simple, practical impact vs likelihood matrix that guides action. From quick wins to high-stakes unknowns, we show how to calibrate effort, buy the right learning, and move with confidence.

Three key takeaways

•  Avoid “Risk Theater” by Using Tools for Decision-Making: Risk analysis tools like FMEAs should be used to make genuine design decisions and drive changes, not just to check a box for project completion. Simply going through the motions without acting on the information is unproductive “risk theater.”
•  Use the Impact vs. Likelihood Matrix to Guide Next Steps: The two-by-two matrix maps the Impact (if you’re wrong) against your Likelihood/Confidence (in your current decision). The resulting quadrant dictates the best course of action, ranging from delegating “Easy Wins” to prioritizing data-gathering for “Critical Unknowns.”
• Prioritize Investigation for High-Risk Scenarios: Decisions that have a High Impact and Low Confidence (Critical Unknowns) should not proceed until you have dedicated time and resources to investigate, test, and gather data. This step is necessary to increase your confidence and reduce the technical risk before proceeding with expensive or time-consuming implementation.

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How to Choose Risk Tools That Actually Help Decisions

If you reach for the nearest “risk” template, it might cause more problems.

There are two very different jobs we ask risk tools to do. In this episode, we talk about how to pick the one that actually moves your project forward.

• identification tools for unknown unknowns (like FMEA and preliminary hazard analysis) that systematically surface risks to users, systems, and environments
• decision tools for known unknowns that clarify impact, likelihood, and uncertainty so teams can choose a path with confidence.

Along the way, we call out organizational risks that belong in resilience planning, not product FMEAs.

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Design Clarity Through Cadence: Aligning Podcasts, Substack, and a Playbook for Teams

Big changes, clearer focus, and more ways to learn together. We’re tightening our cadence to two episodes a month and building monthly themes that travel across the podcast, blog, and a new Substack home—so you can go beyond ideas and into practice with tools, Q&A, and live community sessions.

Here’s what’s new and why it matters. The podcast keeps its familiar format, but now each month has a focused theme that carries into Substack deep dives. Subscribers get comprehensive guides, open Q&A weeks where we answer your specific questions in the comments, and a one-hour live chat each month to pressure-test methods on real scenarios. It’s a smarter learning loop: listen, explore, apply—then come back with better questions. You’ll also get access to the strategy vault filled with templates, worksheets, and facilitation guides.

We’re also thrilled to announce the launch of Pierce the Design Fog, a practical playbook for product, engineering, and UX teams who need structure without losing speed or humanity. With models like the concept space and ADEPT framework, you’ll align cross-functional teams, turn insights into actionable design inputs, and make confident calls under uncertainty. There’s a companion card deck—Concept Quest: Design Discovery—that acts like a portable facilitator, with prompts and instructions to guide workshops. Pre-order before October 14, 2025, to enter the card deck giveaway and bring these methods straight into your team’s next session.

Subscribe to the show, check out the Substack at qualityduringdesign.substack.com, and leave a review to help more builders find us.

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QDD Redux: Prioritizing Customer Satisfaction in Product Design (the Kano Model)

How do you balance customer wants with project constraints? If your customer-facing teammates are saying our customers want this, that and the other thing, which ones do we prioritize over others?

Not all features are equal in the eyes of our customers. And not all features are value-added, either.

In this episode, we delve into how to prioritize customer wants using the powerful Kano Model, a tool that maps customer satisfaction against the implementation of product features.

You’ll learn how to differentiate between essential and non-essential features, ensuring that your design truly resonates with your customers. This episode walks through the intricacies of the Kano Model’s two-by-two matrix and the different satisfaction levels represented by various lines and curves.

Too complex? We break it down. Prioritize your features based on their impact to the customer using their voice. Then, consider how well you want to implement that in your design using the Kano Model.

Get ready for practical tips and proven strategies to enhance your product’s value while managing cost, time, and design trade-offs. This episode is an introduction to the Kano Model for design.

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Beyond Requirements: How Quality Methods Provide Actionable Design Inputs

We explore the critical transition from concept development to engineering solutions in product development, highlighting quality tools that bridge the gap between customer needs and technical design inputs.

• Quality engineering tools help translate concept development insights into design requirements
• Results from concept development help focus engineering efforts on what matters most
• The goal is continuing the conversation from concept development through product design

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Map the User Journey: Design for Seamless Experiences

It’s important to evaluate the customer’s use process during concept development.

Rather than focusing solely on what your product does, understanding how users will interact with it creates opportunities to design more intuitive, enjoyable experiences. By mapping out the steps users take from beginning to end using process flowcharts, development teams gain clarity on inputs, outputs, and the journey between them.

Whether you need to simplify complex steps, compare competitor approaches, or identify critical-to-quality elements, these analytical methods help prioritize design decisions based on what truly matters to users.

The goal is creating products that feel intuitive and natural, preventing those awkward validation testing moments when engineers want to shout, “You’re doing it wrong!” When we evaluate the use process early, we develop products others love while minimizing costly redesigns and user frustration.

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Keven Wang’s 4-Step Journey to AI-Powered Quality Control (A Chat with Cross-Functional Experts)

Dianna Deeney interviews Keven Wang from UnitX. Keven shared valuable insights about how AI-powered quality control is revolutionizing factories worldwide, beyond inspection. With over 160 customers benefiting from this technology, Wang’s expertise offers a glimpse into both the present capabilities and future potential of AI in manufacturing.

This interview is part of our series, “A Chat with Cross Functional Experts”. Our focus is speaking with people that are typically part of a cross-functional team within engineering projects.

About Keven

Keven Wang is the Co-Founder & CEO of UnitX, a leading AI Robotics company automating visual inspection in factories. Keven graduated from Stanford University with a degree in Computer Science concentrating on AI. He has visited 135+ manufactures worldwide helping to improve yield and quality, and holds patents in AI
technology for visual inspection.

Keven and Dianna talk about

• Best time to implement AI-powered quality control
• What it takes to train AI
• Best practices in validating new vision systems
• Keven’s 4-step journey to AI manufacturing
• Real success stories

Perhaps most surprising is Kevin’s observation that the greatest challenge in AI adoption isn’t technical but human—aligning teams, establishing shared goals, and helping personnel become comfortable with the technology. This insight underscores that successful implementation requires thoughtful change management alongside technical expertise.
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Design to Avoid Problems: Focusing on Symptoms Early On

The art of product development is fraught with challenges, but perhaps none is more heartbreaking than hearing negative customer feedback when you thought you were at the finish line.

Picture this all-too-common scenario: after months of development and seemingly thorough customer engagement throughout the process, you finally present your polished product to users only to hear crushing feedback like “I don’t like that” or “That doesn’t work for me.” These late-stage revelations often necessitate extensive redesigns, creating costly delays and team frustration.

This painful experience begs the question: how could we have missed these issues despite our efforts to involve customers along the way?

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Slow Down to Speed Up: Jake McKee’s Guide to AIX (A Chat with Cross-Functional Experts)

Dianna Deeney interviews Jake McKee to explore AI Experience Design (AIX), the practice of designing relationships between humans and intelligent AI systems, and how it’s reshaping product development in today’s rapidly advancing technological landscape.

In this eye-opening conversation, Jake draws a powerful parallel between today’s AI transformation and the digital transformation of the early 2000s. The key difference? Scale and speed. While the early web had natural boundaries, AI presents an almost limitless frontier advancing at breathtaking pace. This creates unique challenges for product teams caught between executive demands for AI innovation and the practical realities of implementation. Jake explains how this pressure often leads to a predictable cycle of over-reliance followed by algorithm aversion before teams eventually find balance.

Rather than viewing AI as a replacement for human capabilities, Jake advocates for seeing it as a “creative and critical partner” that enhances our thinking and processes. He shares practical examples of how product teams can thoughtfully integrate AI – from using it to test early concepts against customer data to employing it as a collaborative ideation tool. Throughout our discussion, Jake emphasizes that successful AI integration depends on maintaining human relationships at the center of product development, not pushing customers further away behind technological barriers.

This interview is part of our series, “A Chat with Cross Functional Experts”. Our focus is speaking with people that are typically part of a cross-functional team within engineering projects. We discuss their viewpoints and perspectives regarding new products, the values they bring to new product development, and how they’re involved and work with product design engineering teammates. [Read more…]

Uncovering Customer Desires: Understanding Benefits in Concept Development

In product development, we often get caught up in the technical specifications and features we’re creating, forgetting the fundamental reason we’re building products in the first place: to provide benefits that improve users’ lives. This foundational concept of benefits versus features deserves revisiting regularly, especially when we’re deep in the weeds of development work.

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Blank Flipcharts Don’t Make Magic, But Templates Do

In product development, the “fuzzy front end” of concept development often represents both tremendous opportunity and significant challenge. During this critical phase, teams are tasked with defining problems, understanding customers, and generating solutions—all before any engineering begins.

How we navigate this phase dramatically impacts bottom-line results, market share, customer satisfaction, and whether projects even launch at all.

What makes concept development particularly difficult is that teams typically lack something concrete to discuss. Without prototypes or developed products, conversations can become abstract and unfocused. This challenge is compounded when cross-functional team members approach problems from vastly different perspectives, sometimes unknowingly working to solve entirely different issues altogether.

The traditional approach of gathering everyone in a room for open brainstorming sessions has proven remarkably ineffective. Research confirms what many of us have experienced: teams engaged in unstructured brainstorming typically generate fewer ideas, and those ideas are often of lower quality compared to more structured approaches.

The solution lies in using visual models and templates—structured frameworks that guide the creative process and facilitate meaningful team collaboration.

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