This episode of Product Mastery Now features a conversation with Sarah Stabelfeldt, VP of Innovation, and Melissa Pierson, Innovation Programs Manager at Schreiber Foods, about building high-impact innovation processes within large organizations. The discussion centers on Schreiber Foods’ journey to revitalize their innovation culture, launch The Hatchery coaching and innovation program, and successfully integrate AI tools to accelerate value creation. Key takeaways include how to foster cross-functional collaboration, strategies for maintaining innovation momentum after sprints, and practical ways to leverage AI to free teams for more meaningful, creative work.

Product innovation processes are quickly improving. While this is great news, most organizations don’t even have a well-defined process. In this discussion, we’re exploring how to build an innovation engine that works, delivering value to customers and to the organization, with real AI integration that cuts development time from months to weeks or even days. If you’ve ever felt like your innovation sprints lose momentum, your stakeholders resist change, or you’re not sure how to practically use AI beyond the hype, you’re not alone. These are the challenges that led a $7 billion food company to reimagine how they innovate. And, we’ll learn about the innovation approach they created, called The Hatchery, including the AI tools they use.

Our guests are both with Schreiber Foods. Sara Stabelfeldt is the VP of Innovation and was previously an Innovation Leader at Kimberly-Clark. Melissa Pierson, is the Innovation Programs Manager, who previously worked in quality systems and also held quality positions at Eli Lilly. 

Schreiber Foods’ Innovation Transformation
Schreiber Foods is a $7 billion customer-branded food company that manufactures cheese, yogurt, cream cheese, and aseptic beverages for retailers and food service. When CEO Ron Dunford took over in 2019, he initiated a transformation to accelerate growth by amplifying innovation capability. This led to a comprehensive innovation ecosystem including core innovation (supporting existing business), adjacent innovation (new revenue streams), digital labs, corporate venture capital, and The Hatchery—an innovation approach that helps companies build practical innovation cultures and programs.

Building Culture Through the Snowball Effect
Sarah describes building culture as akin to building a snowball, an analogy coined by her colleague Erin Faulk. You can’t force culture by pushing too hard or it crumbles. Instead, you form it and let it roll, responding to the organizational climate, context, and people. Culture is built through repeated actions that demonstrate what’s valued, not just through messaging. This approach recognizes that innovation culture must adapt to its environment rather than being imposed from above.

The Hatchery Innovation Framework
Sara explains that The Hatchery is an innovation approach developed at Schreiber Foods to equip product managers and innovators with the tools, structure, and approach to maximize culture and impact. The program alternates between learning and doing to help teams develop, practice and embed mindsets, behaviors, and technical skills in the organization to reignite innovation journeys.

Practically implementing the Hatchery involves strategic coaching and mentoring, creating a culture of innovation, using an innovation toolbox, and running innovation sprints.

Building Innovation Culture
Melissa explains that The Hatchery helps teams believe that complex problems can be solved. Product teams that participate in sprints often return to their jobs with a new mindset to find different ways to solve problems.

Product Innovation Sprints
In The Hatchery framework, cross-functional teams participate in week-long innovation sprints, applying best practices from a variety of innovation methodologies. These sprints begin with determining what the business or team is trying to achieve and identifying and quantifying the problem that is holding them back. Next, the team approaches the problem with empathy, trying to understand how other business units experience the same problem. Understanding others’ pain points allows the organization to share a collaborative mission. Next, the team discusses Jobs-To-Be-Done or “How might we” statements to unlock progress. They then work on idea generation, prioritization, and prototyping. The outcome of the sprint is a set of ideas and clarity on the next steps.

Ending the Sprint with an Open House
The Hatchery sprints end with an open house, during which the team shows their work in progress to others from across the organization who help build ideas and give feedback.

Sustaining Momentum After Innovation Sprints
One of the biggest challenges in innovation is maintaining energy and progress after the initial sprint ends. The Hatchery address this by building momentum during and after the sprint. The sprint has an executive sponsor for the sprint and is strategically aligned to a business imperative. Innovation champions on the team have a passion for innovation and the mindset and skillset to help the team continue to implement what they learned during the sprint. The coaches who lead the sprint stay involved to help move the project forward.

Real-World Example: Industrial B2B Service Model Transformation
An organization in the industrial B2B space had an ambitious concept that would redefine their service model and expand market reach. When they presented the big idea, experienced stakeholders immediately became cautious, filtering the concept to protect the business from perceived risk, causing the market-moving idea to get chipped away into tiny changes that would solve nothing. Rather than shrinking the idea itself, Melissa’s team went back to the core vision and instead chunked down the steps to achieve it. They identified critical assumptions that could prove out the whole idea or potentially invalidate it, then tested those narrow pieces through overnight consumer testing, AI persona vetting, and isolated manufacturing process trials. By building buy-in through evidence and data from these quick, believable steps, they maintained the inspiration for the big vision while making it doable and realistic.

Strategic AI Integration
Sara and Melissa use AI tools to accelerate innovation. They have realized that unlocking AI’s potential isn’t about the tool itself but about learning how to interact with it. They’ve built a repeatable prompt library with persona roles, mindsets, specific innovation theory context, and relevant constraints. Their use of AI cultivates thought partnership, leveraging the unique strengths of both humans and AI.

The team’s mantra is “It’s not what AI gives us; it’s what it frees us to become.” When AI handles data synthesis, pattern recognition, and quantitative analysis, innovators can focus on empathy, intuition, emotional depth, cultural context, and nuanced judgment—the messy, fun parts of innovation. They use prompts to explore how ideas would be solved 10 years in the future, historically, or in other cultures.

The team uses multiple tools including Gemini, Copilot, and Aucctus, a set of AI agents trained on innovation theory that enables teams to chat with consumer personas.

“If you want to know where your heart is, look to where your mind goes when it wanders.”   – Walt Whitman
 
“Tell me what is it that you plan to do with your one wild and precious life.” – Mary Oliver

As Innovation Programs Manager at Schreiber Foods, Melissa leads initiatives that inspire the core and activate a culture of curiosity and experimentation. She brings deep experience in intrapreneurship, product development, and business model innovation. Melissa is also a driving force behind The Hatchery—Schreiber’s external innovation service provider—where she helps teams move beyond “innovation talk” into real action.  Her work often explores how human-centered design and emerging technologies can work in harmony—amplifying creativity, accelerating learning, and unlocking meaningful, scalable impact. With a background spanning pharma, food, contract manufacturing, Lean/6-Sigma, and project management, she brings both structure and spark to the innovation ecosystem.  

Sara Stabelfeldt is a strategic thinker with the skills of an engineer and the soul of the customer. As the Vice President of Innovation at Schreiber Foods, Sara inspires a team of serial intrapreneurs and business builders to dream big and unlock new growth engines in service of the company’s mission to Do Good Through Food. 

Prior to Schreiber, Sara has a proven track record of leading innovation for iconic brands like Kleenex®, DEPEND®, and HUGGIES®. Samples of her work were featured in both Clayton Christensen’s time-tested book ‘Competing Against Luck’ and as a gift in the Emmy’s Swag Bag. 

Sara’s passion for her work stems from her love of strategy and commitment to building talent. She approaches every challenge with a focus on fundamental consumer insights and technical innovation principles. But it’s not just theory.  Her work is reflected in numerous patents and publications and can be found in millions of homes each and every day. 

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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Product managers struggle with using AI effectively despite the hype around its potential. Valerio Zanini, author of AI for Product Managers, shares practical frameworks for leveraging AI tools in customer discovery, hypothesis validation, and feature selection. Key insights include using AI as a discovery assistant to analyze customer interview transcripts, synthesizing market research across multiple sources, and creating rapid prototypes with AI coding tools. Our conversation addresses real barriers product managers face—from corporate restrictions to lack of expertise—and provides actionable approaches to accelerate time-to-insight from months to weeks or days.

Product managers know that discovery and validation can make or break a new product or a new version of a product. But, how can AI help us have more success in these areas while also accelerating our work from months to weeks or even days? Many product teams are drowning in customer data while simultaneously starving for actionable insights—it is a challenge I encounter often when I train product managers in companies. AI brings emerging tools to gain value from this data and improve our work. You’re probably already using AI in your work, but I also bet you want to know how to get more from it—how to unlock it’s real potential. Today, you’ll learn specific approaches for using AI to conduct customer discovery, validate hypotheses faster, and select features.  

Our guest, Valerio Zanini, brings 20 years of product experience, from founding startups to leading digital transformation at Capital One. He’s trained thousands of product managers worldwide and literally wrote the book on AI for Product Managers. His frameworks aren’t theoretical—they’re tested across industries and proven to accelerate time-to-insight. 

Valerio’s Book, AI for Product Managers
Valerio wrote AI for Product Managers after discovering a gap between AI hype and reality. While social media showcases impressive AI use cases, his research revealed most product managers don’t use AI due to corporate restrictions, lack knowledge about implementation, or struggle with basic application. The book addresses the practical barriers preventing product teams from capturing AI’s benefits, moving beyond theoretical possibilities to tested frameworks that work across industries. When used correctly, AI tools expand, simplify, and accelerate product managers’ work.

The Gap in AI Adoption by Product Managers
Many product managers face significant obstacles to AI adoption that don’t appear in success stories. Corporate environments often restrict AI tool access due to privacy concerns, leaving teams with sandboxed systems inferior to consumer tools like ChatGPT. Product managers frequently lack permission to use AI, don’t understand how to apply it effectively, or face organizational inertia. This creates a disconnect between the potential demonstrated in workshops and conferences versus day-to-day practice where teams remain starved for actionable insights despite drowning in customer data.

AI as a Discovery Assistant
AI excels at analyzing customer interview transcripts to find patterns and insights that humans might miss. After conducting customer interviews, product managers can feed transcripts into AI tools to identify recurring themes, pain points, and unmet needs across conversations. The AI can also act as a synthetized user, helping to expand thinking into areas not initially considered and providing different perspectives on customer feedback. This approach transforms hours of manual analysis into minutes while uncovering insights that might otherwise remain hidden in the data.

Synthetic Users vs Real Customer Interviews
Valerio shared an example of practicing customer interviews in different settings—sitting in a coffee shop talking to real people versus interviewing synthetic AI customers from your office. Synthetic users are digital personas that can simulate customer interviews, providing insights about behaviors, problems, and needs. This offers two key benefits: speed (conducting research in a day from your desk) and practice (refining interview techniques before engaging real customers). Valerio noticed that AI users can help uncover problems that real people may be uncomfortable sharing. On the other hand, real people helped him find edge cases that AI missed.

Synthesizing Market Research
Product managers typically gather market research from multiple sources—analyst reports, competitor analysis, industry trends—but may struggle to synthesize this information effectively. AI can process and combine insights from diverse sources, identifying connections and patterns across materials. Rather than spending days reading and consolidating reports manually, product managers can use AI to generate comprehensive summaries that highlight key trends, competitive dynamics, and market opportunities. This acceleration from weeks to hours enables faster strategic decision-making.

Problem Framing with AI
Before diving into solutions, product managers need clarity on the problem they’re solving. AI can help frame problems by analyzing customer feedback, market data, and business constraints to articulate the core challenge. This includes defining the problem space, identifying affected customer segments, and understanding the business context. AI tools can generate multiple problem framings from the same data, helping teams avoid premature solution-jumping and ensuring alignment on what problem deserves resources.

Rapid Prototyping and Validation
AI coding tools have eliminated traditional prototyping barriers by enabling anyone to create working prototypes without coding expertise. Product managers can describe a feature idea verbally and generate a functional prototype in hours or even a single day. These prototypes aren’t production-ready but allow teams to test problem-solution fit with customers before writing detailed specifications. The ability to iterate rapidly—testing, gathering feedback, and refining—transforms the validation process from a bottleneck requiring design and engineering resources into an empowering capability for product managers.

Feature Ideation and Prioritization
AI can generate feature ideas based on customer insights, market research, and business goals, then help evaluate and rank these options. Product managers can use AI to apply prioritization frameworks like RICE or opportunity scoring models to assess potential features. However, confidence scores should remain low for AI-generated ideas until validated through customer testing. The combination of AI ideation followed by rapid prototyping enables teams to explore a broader solution space while maintaining validation discipline.

Risks of AI Tools in Product Management
Valerio points out that a risk of using AI tools is that they can also accelerate problematic product management practices like feature creep. AI tools shouldn’t make strategic decisions for product managers. Teams can build features quickly and efficiently while still creating the wrong product if they lack clarity on customer problems and value creation. AI tools can’t replace the fundamental discipline of understanding what customers need.

“There can be no agility without product thinking.” – Valerio Zanini

Valerio Zanini is a Certified Product Innovation Trainer (CPIT) and a Certified Scrum Trainer (CST). As a trainer and consultant, Valerio works with companies around the world to help them learn, adopt, and improve their AI and Product Management practices. He has taught thousands of people ranging from small startups to large corporations.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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Three innovation consultants—Matt Phillips, Mike Hyzy, and Will Evans—share insights from facilitating the executive innovation track at PDMA’s Ignite Innovation Conference. The session brought together 25 senior directors and VPs from Fortune 100 companies to discuss their most pressing innovation challenges. They discussed key challenges to innovation, including managing capacity to carve out space for innovation work, driving AI adoption across the workforce, and building innovation cultures that spread beyond dedicated innovation teams. Solutions discussed include celebrating effort over success, creating visible recognition systems for innovators, and developing innovation models that train innovation champions across different parts of organizations.

What happens when innovation executives from across industries gather in one room to surface their most urgent challenges? In this discussion, we’re going behind the scenes of the Executive Innovation Track at PDMA’s Ignite Innovation conference—a rare opportunity where leaders dropped their guard and revealed the real innovation challenges keeping them up at night. We’ll discuss the actual challenges executives are facing right now, discover which constraints matter most, and learn how leaders are breaking through their biggest innovation barriers. 

Our guests facilitated this executive session. Matt Phillips founded Phillips & Co., advising companies like Paramount Pictures and Pepsi on accelerating innovation. Mike Hyzy leads CGI’s Product Studio, helping organizations turn AI and emerging tech into market-winning products. Will Evans from Fugue Strategy brings strategic foresight and Theory of Constraints expertise to help companies build adaptive organizations. 

Find out more about the Product Development and Management Association (PDMA) and next year’s innovation conference.

Managing Capacity for Innovation
Will Evans highlighted that executives struggle to carve out capacity—both internal and external resources—to do innovation work while managing existing operations. Organizations face the tension between day-to-day operational demands and the need to invest in future innovation.

AI Adoption and ROI
Mike Hyzy identified low adoption rates as a major challenge. Even after selecting AI platforms (Copilot, ChatGPT, Claude, GitHub Copilot, etc.), only 15% of employees typically use these tools. Without widespread adoption, organizations can’t achieve the promised ROI from AI investments. The challenge extends across different personas and roles, from knowledge workers to engineers.

Culture and Spreading Innovation Beyond the Few
Matt Phillips found that culture is a barrier to innovation. Executives are facing challenges trying to spread innovation beyond dedicated NPD or innovation groups. Leadership attitudes and organizational culture often prevent employees from suggesting ideas or taking innovation risks.

Celebrating Effort, Not Just Success
Organizations should recognize teams and individuals who attempt innovation, even when efforts don’t result in products. One manufacturing company created an “innovation wall” that celebrates anyone who suggests an idea or launches a product, reinforcing that innovation is valued regardless of outcome.

Moving Beyond Monetary Rewards
Effective recognition goes beyond financial incentives. Visibility matters—putting people on pedestals, sharing their stories, and creating narrative examples that shape culture. Recognition should be authentic and tied to what makes individuals feel valued in their specific organizational context.

Change Management Evolution
The discussion highlighted that template-driven change management is becoming less effective. Organizations need to relearn how to manage through change, starting with individual transformation rather than top-down mandates.

Breaking Down Silos Through Transparency and Communication
Organizational silos create significant waste and duplication. Executives shared examples of teams discovering they’d been working on identical projects for months, spending tens or hundreds of thousands of dollars unnecessarily. One IT leader from a large insurance company stressed the importance of making roadmaps and IT system implementations visible across the organization to prevent duplicate software license purchases and redundant project work. Effective communication unlocks innovation. Large companies excel at building silos, making continuous visibility into ongoing work critical for innovation efficiency.

Middle Management Resistance
Middle management often creates bottlenecks in the innovation process. While entry-level employees feel free to generate ideas and senior management supports experimentation, middle management can be threatened by new ideas or uncertain how to handle them, causing proposals to stall out. One executive’s advice for addressing this challenge was for lower-level employees to consider going around middle management directly to senior leadership to get approval for experiments.

Accountability and Follow-Through
Accountability is necessary for turning conference insights into action. After Matt’s team created a comfortable environment where executives openly shared their challenges, Mike and Will structured the second half of the workshop around identifying specific bottlenecks and Monday-morning actions. The session concluded with a deliberate accountability mechanism: Participants were paired with partners and instructed to reach out in 30 days and ask: “Did you do the things you said you were going to do in this workshop?” Often conference attendees absorb tremendous information over three days but struggle to implement changes when they return to work. By creating peer accountability partnerships and planning follow-up emails to reinforce commitments, the facilitators aimed to ensure executives actually execute on their stated intentions rather than letting insights fade without action.

Innovation Barriers in Academia and the Organizational-Market Mismatch
Will Evans described insights from the 25% of attendees with academic backgrounds. While universities are often viewed as hotbeds of innovation, they face the same organizational impediments as corporations. Academic participants reported struggling with the same challenges as their peers in industry: getting cross-functional groups together for basic tasks like IP licensing deals, navigating bottlenecks and policies that prevent commercializing novel university-generated innovations, and dealing with cultural inertia that blocks progress. Even converting university IP into commercial products faces numerous structural barriers. Across both academic and corporate organizations, there can be a mismatch between organizational structures and their markets. Despite these challenges, participants found solidarity at the conference, where leaders recognized they’re all facing similar struggles.

“Innovation is the ability to see change as an opportunity—not a threat.” – Steve Jobs

Mike Hyzy leads AI product innovation and strategic foresight at CGI, where he launched the product management practice and designed the AI Adoption Framework (A3F). As part of CGI’s national AI strategy team, he develops new solutions with internal teams and advises client executives on how to turn emerging AI capabilities into business advantage. Mike applies strategic foresight to separate signal from noise, giving leaders a clear view of emerging trajectories and the choices that matter for long-term strategy. 

Matt Phillips is a leading expert on strategy and innovation. For over 20 years, Matt has been an in-demand advisor to the Fortune 500, large nonprofits and rapidly growing mid-sized companies. As the founder of Phillips & Co., a Chicago-based innovation think tank, Matt leads a team of researchers, strategists and inventors who help organizations invent new products, services and businesses. Their clients include Paramount Pictures, Dell, Verizon, Purina, Pella, the National Science Foundation, the TSA, and the Crohn’s & Colitis Foundation. Matt holds an MBA from the Kellogg School of Management at Northwestern University and is a graduate of the Conservatory Program in Improv at The Second City.

Will Evans brings a wealth of experience with several of the best-known and most successful companies in experience design, healthcare, and the consumer web. He focuses on integrating design thinking and service design to delight customers and increase profitability. Essential to that effort is the development of future-casting organizational transformation teams that can work seamlessly across organizational functions—an area where Will brings deep expertise. Equal parts business strategist and creative visionary, he has served as a principal and executive creative director for design organizations and functions where he built teams, a client base, and products and services from the ground up. He holds patents for several products he designed in online search and navigation systems. Will has led transformational initiatives for Fortune 50 companies across a range of industries, as well as for start-ups and nonprofits. He has designed and built out enterprise digital/product transformation offices to sustain cultures of continuous discovery and delivery. He advises clients on driving innovation and the behavioral and culture change required to support it while creating products, services, capabilities, and ecosystems that improve the bottom line. Will is inspired by the next generation of design thinkers and lean practitioners. He has been a lecturer in the graduate design, technology, and business strategy programs as Design-Thinker-in-Residence at NYU’s Stern School of Business. Will has taught and facilitated design thinking sessions with Simon Sinek with TED Global Prize winners. He holds a Jonah, certified in Theory of Constraints from the Goldratt Institute, and more recently, he is the author of “Designing Resilience: The Strategy, Structure, and Spirit of Enterprise Agility.”

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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This episode explores how Pella Corporation transformed window installation by shifting their innovation focus from buyers to installers—the often-overlooked specialists whose work makes or breaks the customer experience. Director of Innovation, Design, and Brand Experience Jenn Tuetken shares the journey behind developing Pella’s award-winning Steady Set Interior Installation System, which slashes install time by 72% and enables a single person to complete what once required two. Learn about deeply immersive market research, uncovering hidden pain points, and the strategic moves that made industry-wide change possible—all without lowering prices.

What if your biggest innovation opportunity isn’t with the people who buy your product, but with the people who install it? We’re exploring how Pella Corporation revolutionized the window industry by obsessing over installers—the critical users who don’t purchase windows but determine whether every installation succeeds or fails. You’ll discover a framework for researching non-buyer stakeholders, specific techniques for uncovering hidden pain points people have accepted as normal, and strategies for driving market adoption without lowering prices—all through the story of an innovation that cuts installation time by 72% and can transform a two-person job into a one-person task.

Joining us is Jenn Tuetken, Director of Innovation, Design, and Brand Experience at Pella Corporation, where she’s led the development of award-winning innovations including the Steady Set Interior Installation System and Hidden Screen. With experience from Michael Graves Design Group to founding her own design consultancy, she brings over 15 years of expertise in translating user insights into breakthrough products.

Find out more about the Product Development and Management Association (PDMA) and next year’s innovation conference.

New Product Ideas from Customer Visits:
Jenn recommends visiting customers as a method to better understand their needs and generate ideas for new products. At Pella, a window company, product managers can easily visit customers or potential customers, since nearly everyone owns windows, but the large amount of information available can make distilling meaningful insights a challenge.

The Strategic Shift:
After 90 years of focusing innovation on homeowners, Pella recognized they had a critical blind spot. Their products were designed for building systems and codes, not for the installer experience. Pella’s innovation team discovered that poor installations were driving customer callbacks, damaging brand reputation, and creating market inefficiency. This realization led them to target installers as an innovation opportunity, even though installers don’t purchase the product.

Ethnographic Research Methodology:
Pella conducted ethnographic field research with installers across different skill levels and markets, shadowing them for 8-10 hour days to observe their workflows and pain points. Two innovation team members—an engineer and a designer—observed installers and distilled insights full-time for three months. The team focused on watching what people do rather than just listening to what they say. This approach proved essential for uncovering normalized inefficiencies that users had accepted as standard practice and no longer thought to mention or complain about.

Customer Insights:
The research revealed that installers weren’t complaining because they assumed “this is just how it is.” The windows were designed to be installed from the outside of the house, but for safety most installers installed windows from the inside, requiring two people. Installers had been adapting their work to poorly designed products rather than products being designed for their needs. Market research showed that installers would actually pay more for products that saved them time and reduced labor requirements.

The Innovation: InstaLaunch System:
Pella redesigned their windows to be installable from the inside of the house. The InstaLaunch system improves safety and transforms two-person installation jobs into one-person tasks. This provides faster speed to market for builders and creates product differentiation without competing on price. The innovation addressed the core pain point while delivering measurable value across the entire value chain.

Launch Strategy:
Pella started by validating their hypothesis through installer conversations, then built early prototypes for field testing and iteration. They tested their prototypes with installers on the job site, including testing how easy it was to learn how to use the system. The company took a calculated risk by accepting public pre-launch visibility to gain market momentum, which enabled partners to forecast demand through joint business planning sessions.

Impact of Customer Stories:
The product innovation team brought back real quotes, stories, and videos from customers using their new product. These real stories motivated the development team and influenced other stakeholders by showing them the transformational impact their product was having.

Business Impact:
The InstaLaunch system helped Pella gain market share without lowering prices. Customer service callbacks related to installation decreased. The innovation strengthened brand positioning around quality and innovation while creating scale across product lines and customer segments.

“I don’t exactly know where I’m going, but I know how I’m going to get there.” – Boyd Varty, lion tracker

Leading Pella Corporation’s innovation trajectory, Jenn Tuetken harness strategic leadership and design acumen to propel product and brand experiences into the future. Her role as Director of Innovation, Design, and Brand Experience is a testament to a refined skill set in project portfolio management and stakeholder engagement, ensuring resource allocation aligns with our visionary goals. The innovation pipeline at Pella has continuously and successfully launched award-winning products like the Steady Set Interior Installation System, Easy Slide Operator and Hidden Screen. Jenn’s team’s collaborative spirit and customer-centric approach have culminated in industry recognition, setting new benchmarks for excellence in the window and door sector.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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This episode dives into the increasingly impactful world of product operations, with insights from Robert Marten, Senior Manager of Product Operations at Pendo. We discuss what product operations is, how it streamlines efficiency for product teams, its key pillars (tools, data, process), cultural shifts toward focusing on customer problems over requirements, and practical examples of tool use and benefits at Pendo. You’ll learn how product operations makes product management less chaotic, accelerates onboarding, and fosters a collaborative, efficient culture.

Today’s topic is product operations. A lot of product teams are drowning in documentation, don’t have a clear focus, and might not really know what their North Star is. Groups that have adopted product operations have found success, but a lot of organizations don’t know about product operations yet. We’re going to dive into details about what product operations is.

I am joined by Robert Marten. He is the Senior Manager of Product Operations at Pendo. You may recognize Pendo as the software tool that helps people writing software products themselves augment them with instrumentation to get better insights. Robert is revolutionizing how Pendo does operations themselves. He has a unique background spanning military operations as an Air Force commander to leading Agile transformations at Johnson & Johnson. Robert brings a systems thinking approach to produce development and product management.

Find out more about the Product Development and Management Association (PDMA) and next year’s innovation conference.

What is Product Operations?
Robert shares that product operations is about maximizing efficiency in executing a product’s mission. At Pendo, it focuses on tools, data, and process, aiming to empower product managers to do deep work rather than get bogged down in administrative chaos.

Reducing Process & Enhancing Efficiency
Process isn’t about bureaucracy—it’s about streamlining activities and ruthlessly removing unnecessary steps. Robert emphasizes that the goal is efficiency, not standardization for its own sake. Product ops should remove process whenever the cost of the process in time or money outweighs its benefits.

Solving Communication Challenges
Disjointed communication and documentation practices slow teams down. Standardized reporting and tool use help with transparency, giving everyone access to current information and helping align teams on customer-centric objectives.

Focus on Solving Customer Problems
Robert has observed product teams focusing on the product’s scope or requirement document instead of solving the customer problem. This leads to inefficiencies like not killing a feature soon enough or killing it too soon. Simply changing your language in conversations to reference the customer problem rather than the scope of the product can help the team maintain the right focus.

Tooling at Pendo
Robert describes how Pendo itself, Airtable, and the Atlassian Suite (JIRA, Confluence) are used to drive product ops. Tools are chosen for flexibility, enabling tailored views and efficient status reporting.

From Chaos to Clarity
One of the most tangible benefits of product ops is the reduction in “fires”—less confusion, fewer last-minute emergencies, and more time for meaningful work. Product ops ensures that everyone is on the same page, facilitating faster time to market and better alignment to customer needs.

Impact on Career Growth
Product ops helps product managers ramp up faster, develop their skills more quickly, and spend more time on impactful work that helps them build their brand within the organization.

“Learning is not compulsory. Neither is survival.” – Edwards Deming

“Every system is perfectly designed to get the result it gets.” – Edwards Deming

Robert Marten is currently the Senior Manager of Product Operations at Pendo, a high-growth SaaS company, where he helps the product organization scale effectively and deliver with impact. With more than 15 years of experience spanning agile, project management, product operations, and leadership, Robert has built a career focused on developing high-performing R&D teams and driving efficiency in product delivery. 

Like many in the technology industry, Robert is in his second career. Before moving into the civilian sector, he served for eight years as a pilot in the U.S. Air Force, where he developed the leadership and adaptability he now brings to building successful product teams. 

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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In this episode, I sit down with Dr. David Robertson, senior lecturer at MIT Sloan and co-founder of ProtoBoost AI, to explore the transformative impact of AI on the innovation process. Drawing on decades of experience in product management and innovation, David Robertson discusses how product managers can leverage AI at every stage of the innovation lifecycle—from customer research and need-finding to prototyping, business case development, and cross-functional coordination. The episode covers practical challenges product managers face, ways AI can augment key skills, and the future potential and risks of AI-driven innovation.

 Our guest is Dr. David Robertson, a senior lecturer at MIT Sloan School of Management. We are talking about the impact of AI on the innovation process. David is the author of Brick by Brick, the book on LEGO’s rebound from near bankruptcy around 2003, and the author of The Power of Little Ideas on complementary innovation. David spent five years at McKinsey leading the product development practice and has served as CEO of multiple tech companies. He recently co-founded his own tech company, ProtoBoost.ai to accelerate AI driven innovation. He has also taught at Wharton and IMD Switzerland and now runs MIT’s largest executive ed program.

AI’s Transformation of Innovation:
AI can now be applied at nearly every step in the traditional innovation process—design sprints, customer insight, prototyping, business modeling, and more.

A Brief History of AI:
David Robertson reflects on the evolution from 1980s rule-based AI to today’s data-driven, generative models capable of natural language processing and complex tasks.

Challenges for Product Managers:
Many product managers have strengths in some areas (e.g. customer understanding, engineering dialogue) but lack expertise in others (e.g. financial modeling, stakeholder communication). AI is emerging as a tool to fill these skill gaps. David highlights the use of AI in helping product managers communicate with other stakeholders, understand the effect of a new feature on P&L, and talk to customers.

Synthetic Customers:
Recent advances show AI can act as synthetic customers, simulating human responses for interviews and market research, sometimes even more reliably than real users.

AI Agents for Every Stage:
David anticipates specialized AI agents for building business cases, segmenting markets, or validating user needs—PMs shift from juggling every detail to orchestrating and validating agent outputs.

 “Play all the keys on the innovation piano.
“Date your customer. Don’t fight your competitor.
“Innovation flourishes when the space for it is limited.” – David Robertson

David Robertson teaches AI-driven Innovation at the MIT Sloan School of Management and is the Faculty Director for Sloan’s largest executive education program, the Executive Program in General Management.  David has also created and leads MIT Sloan’s new executive program Revitalizing Existing Products Using AI-Driven Innovation.  Prior to MIT, David was a Professor at the Wharton School and from 2002 through 2010 was the LEGO Professor of Innovation at the Swiss business school IMD.  At IMD David was given inside access to The LEGO Group where he wrote his award-winning book ‘Brick by Brick:  How LEGO Rewrote the Rules of Innovation and Conquered the Global Toy Industry’.   David’s follow-on book – The Power of Little Ideas: A Low-Risk, High-Reward Approach to Innovation – explained how to apply the LEGO innovation strategy to any company in any industry. 

David has been recognized as a “Thinkers50” thought leader, has won numerous teaching awards, and has published 3 award-winning books.  He is a member of the Cherokee Nation and is currently working on a book on Native Innovation. 

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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In this episode, I’m interviewing John Mitchell, President of Applied Marketing Science (AMS), on the evolving role of AI in Voice of the Customer (VOC) research. We discuss how AI is transforming the way companies capture customer needs, the importance of thoughtful customer research design, common pitfalls, and the critical balance between leveraging human insight and machine learning. John gives practical advice on asking better questions, the value of storytelling, and real-world examples demonstrate both the power and current limitations of AI-driven VOC.

 Today we’re talking about how we understand customers’ unmet needs and problems. There’s a lot of information these days in reviews, social media posts, and other online mechanisms, and we’re probably missing a lot of it. There are some tools out there that could help us do a better job understanding what’s going on. We’ll dive into just what some of the options are for us and also how AI is impacting this.

Our guest is John Mitchell. He is the president of Applied Marketing Science (AMS). John has spent over 20 years helping Fortune 500 companies and startups alike understand their customers better. He has trained over a thousand people on Voice of the Customer (VOC) approaches and led customer-insight workshops at McKinsey, Innosight, and Vistaprint before coming back to lead AMS. Whether you’re pioneering VOC research in your organization or just getting into how AI can help us with this, AMS has a deep history with this that John has been part of.

This episode was recorded live at the Ignite Innovation Conference, the Product Development and Management Association’s annual conference. To find out more about PDMA and how it can help your career, go to PDMA.org.

The Evolution of VOC & AI’s Role:
John Mitchell traces VOC from face-to-face interviews and observational research to today’s use of AI and machine learning, highlighting how AI accelerates insights, uncovers overlooked data, and helps companies extract more value from existing information.

Common VOC Mistakes:
Many teams underprepare for VOC research, talk only to “A-list” or friendly customers, or simply ask customers what they want (which often leads to generic answers). Deep customer understanding and competitive advantage come from well-structured research and targeting a broader audience.

Asking Better Questions:
Instead of generic questions, John Mitchell recommends getting customers to tell detailed stories about their experiences, which reveal both functional and emotional needs.

AI Tools in VOC:
There are three main AI approaches for VOC work: open tools (with noted security risks), secure commercial data analysis platforms, and purpose-built tools trained to articulate customer needs from large data sources. AI extends and enhances human analysis, often finding emotional unmet needs that people might miss.

Synthetic Customers:
While not yet widely adopted by AMS, synthetic personas have potential for rapid concept evaluation—though John Mitchell cautions against over-reliance, emphasizing that real human feedback remains irreplaceable.

Real-World Example:
In the paint and stains category, AMS compared traditional human VOC analysis to an AI model, finding that a combined approach surfaced the most comprehensive set of customer needs.

Voice Recorder Tip:
John recommends that every product researcher should record their customer interviews (using a dedicated device), ensuring nothing is missed and allowing for high-quality AI or human analysis downstream.

“ If I had asked customers what they want, they would have said a faster horse.” – attributed to Henry Ford

John has over 25 years’ experience in marketing strategy, market research, and innovation. He specializes in research to support new product development and customer experience design, and has led engagements in the U.S., Latin America, Europe and Asia. John has also trained and coached hundreds of AMS clients to develop their in-house insight capabilities. 

He is a RIVA-trained focus group moderator and was formerly a Customer Insights Expert in the Marketing & Sales practice of McKinsey & Company and North America Customer Insights Director at Vistaprint. His clients include leading medical device, technology, and consumer services companies. 

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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In this episode of Product Mastery Now, Katie Trauth Taylor, PhD, CEO and co-founder of Narratize AI, joins me to discuss how AI is transforming product innovation processes. She shares insights from working with Fortune 500 companies like NASA, Boeing, and Comcast, and dives into research showing that product and R&D teams spend up to 70% of their time on documentation and communication rather than true innovation. Katie outlines four best practices for leveraging AI, including the use of knowledge hubs, AI agents, and robust documentation processes, to unlock productivity, capture tribal knowledge, and speed up time to market by as much as 46%. The conversation also highlights the importance of storytelling in gaining buy-in for new ideas and the potential for AI to revolutionize knowledge management and portfolio intelligence.

 Product teams waste a lot of their time doing things that don’t help get to the heart of product innovation. We need to flip the script on that so that we can be more productive with our innovation efforts. In this discussion, you’re going to learn how companies like Boeing, Comcast, and others are accomplishing this. We’re going to talk about four specific approaches for unleashing AI for product innovation.

To help us with that is our guest, Dr. Katie Trauth Taylor. She is the CEO and co-founder of Narratize AI, and she helps R&D transform their scattered knowledge into a competitive advantage. She has worked with NASA, Boeing, and other Fortune 500 companies to cut documentation time and speed products to market. Katie discovered that innovators are spending too much of their time just trying to communicate their ideas, and she built an AI platform to improve this. She holds a PhD from Purdue University and has published peer-reviewed research on innovation storytelling that’s reshaping how teams work.

Find out more about the Product Development and Management Association (PDMA) and next year’s innovation conference.

The Problem with Documentation:
Product teams spend roughly 70% of their time on documentation, reporting, and knowledge lookup instead of direct innovation. This significantly slows time to market.

AI as a Knowledge Capture Tool:
Katie turned to large language models to transform how product teams do documentation. AI can systematically prompt and capture insights, store tribal knowledge, and automate documentation customized to roles and project phases.

The Power of Storytelling:
Successful innovation relies on crafting compelling narratives, not just data. Five drivers for effective storytelling are empathy, engagement, alignment, evidence, and impact.

Best Practices for Leveraging AI in Product Teams:

Knowledge Management Revolution:
Capturing lessons learned and even past failures allows organizations to prevent repeating mistakes and leverage prior discoveries, especially as a significant portion of the workforce retires.

Actionable Insights for Product Managers:

“If it’s a truly disruptive innovation from a company, you can almost guarantee it wasn’t a straight A-to-B path that delivered the results. So as you recognize the success, recognize also the journey that got you there.” – Joel Schall

Katie Trauth Taylor is CEO and Cofounder of Narratize AI, a product intelligence and innovation platform empowering teams to bring products and discoveries to market faster, smarter, and with greater impact by eliminating inefficiencies, aligning teams, and preserving institutional knowledge. Katie is a growth-focused entrepreneur executive with 10+ years experience inspiring teams to design and deliver magnetic products, memorable experiences, and groundbreaking impacts. She has led strategic innovation narratives and served as a senior content strategist within fast-growth tech startups and the Fortune 500, including Boeing, NASA, Hershey, Sunoco, AAA, IFF, Dupont, Edgewell, Cincinnati Children’s, Argonne National Lab, Crossover Health, Parsley Health, Omada, Physera, US Dept of Veterans Affairs, Millennium Challenge Corporation, World Food Forum, and the United Nations. She believes that everyone can be an innovator–when empowered to share their bold ideas.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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In this episode, I’m interviewing Paul Dailey, Product Manager for Low Volume Irrigation at Rain Bird, about the complete innovation journey of bringing a new commercial irrigation product—the all-in-one zone control—from concept to market. Paul Dailey shares actionable insights on hardware product development, leveraging focus groups, customer interviews, and production-intent prototyping. He discusses balancing technical feasibility with actual user needs, learning from failed launches, and executing a strategic “rolling thunder” go-to-market plan. Tune in for practical frameworks and candid lessons from 25+ years of hardware B2B product innovation.

I love how universal product innovation and management is. The same principles that advanced solar energy storage are now transforming how we irrigate our landscapes and green spaces. In this episode we detail the journey of hardware product innovation by examining the development of a commercial irrigation product from concept to launch. You’ll discover the frameworks and tools used to develop products at one of the world’s leading irrigation companies, Rain Bird—practical tools you can use immediately.

We’re about to learn from Paul Dailey, Product Manager for Low Volume Irrigation at Rain Bird Corporation. Paul is responsible for landscape drip irrigation products and is about to bring a new product, The All-in-One Zone Control, from initial concept to launch. Paul has also successfully developed a number of sustainable energy products. At OutBack Power, he directed product and marketing strategy as well as product management. He’s built product management teams and has over 25 years of experience in B2B hardware innovation. He is also an accomplished maker in his spare time.

Get ready to take notes—Paul will share the step-by-step process he uses to innovate in a 90-year-old company.

Rain Bird’s Stage-Gate Innovation Process:
Paul Dailey describes Rain Bird’s product development stage-gate process, all with a strong emphasis on quality:

Customer-Centric Product Ideation:
The All-in-One Zone Controller originated from a deep understanding of landscape architects’ pain points—mainly space constraints and installation complexity in valve boxes. Rapid prototyping enabled fast, iterative feedback.

Focus Groups & Customer Interviews:
Rain Bird leveraged both moderated external focus groups and on-site customer interviews across the country. This hybrid approach surfaced insights on design, usability, regional differences, and buying motivations.

Prototyping & Field Trials:
Transitioning from concept to manufacturable prototypes, the team used low-volume “bridge tooling” for field-ready units, validating both design and assembly line processes.

Go-To-Market Strategy:
Rain Bird uses a “rolling thunder” launch, building anticipation with customers, sales teams, and channel partners ahead of full release, ensuring the market is primed and ready.

Key Learnings:

“There is nothing new under the sun.” – King Solomon  (~900 BCE) 

Paul Dailey is an experienced product management leader with a demonstrated history of success in the renewables and distributed energy industry. He is skilled in Sales, Market Research, Management, Renewable Energy, and Business Development. He has a Master of Business Administration (M.B.A.) focused in Marketing and Product Development from Washington State University.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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In this episode, I’m joined by David Carstens, a seasoned IP attorney and founding partner at Carstens, Allen & Gourley, who brings over 30 years of legal and technical experience in intellectual property (IP) strategy. Our conversation dives into the importance of IP management for product managers, how to build an IP strategy, when to consider patents versus trade secrets, the complexities of software and AI-generated content, and the rapid pace of change in the IP landscape. The episode is a must-listen for any product manager navigating decisions around invention protection, copyright, and the evolving influence of artificial intelligence.

If you’ve ever wondered whether to patent that new feature, worried about AI training data copyright issues, or struggled to justify IP investment to leadership, you’re not alone. We’re exploring intellectual property strategy for product managers—and what it means to get it right and how expensive it can be when you get it wrong. Most product managers don’t receive training on IP strategy, yet the decisions you make daily have massive IP implications.

Our guest is David Carstens, who has a unique combination of technical depth and legal expertise. He’s a founding partner at Carstens, Allen & Gourley. He has dual engineering degrees, an MBA, and over 30 years experience protecting IP for companies building software, medical devices, and telecommunications products. He’s also an entrepreneur who founded multiple companies including a nationally chartered bank and an innovation platform, plus he’s been teaching IP law at SMU for three decades. David is currently investing in and speaking about the Fifth Industrial Revolution, making him well positioned to help us also understand how AI is reshaping IP strategy. 

IP Strategy Framework:
David mentions that there isn’t a “one-size-fits-all” framework for IP strategy; it starts with assessing a company’s current position, identifying valuable innovations, evaluating what can realistically be protected, and aligning actions with budget constraints. Key steps include identifying strong value propositions, checking for existing patents or IP conflicts, and sometimes considering licensing or redesign if a competitor already owns relevant patents.

Timing and Collaboration:
Product managers should start thinking about IP early—preferably well before product launch or tooling investment. Collaborating with an IP attorney and creating a culture that values teamwork and knowledge sharing can help spot and protect innovations more effectively.

Patents, Trade Secrets, and Value:
Patents offer competitive advantages by providing pricing freedom, can act as bargaining assets, and are vital for companies seeking investment. Trade secrets, by contrast, are about keeping valuable information confidential (e.g., formulas or processes not disclosed publicly), but are only effective if the information can’t be easily reverse-engineered from the product.

Software & AI Challenges:
The fast pace of software development often complicates patent decisions. Patentability is more likely when software enables a genuinely novel technical process rather than automating routine tasks. For AI-generated content, copyright ownership is still unsettled; it usually depends on the degree of human contribution to the creative process. Legal systems are racing to catch up as AI shakes up traditional definitions of authorship and originality.

The Fifth Industrial Revolution and Legal Evolution:
David argues we’re entering a new industrial age defined by AI, blockchain, quantum computing, and advanced materials. The IP legal framework, largely unchanged for centuries, is struggling to keep pace with these rapid innovations, making adaptability and ongoing awareness essential for product managers.

“Pressure is a privilege.” – Billie Jean King

David Carstens distinguishes himself not only through his comprehensive knowledge of legal protection of Intellectual Property (IP) but also through his innovative approaches to IP strategy and valuation. With an educational foundation that is as diverse as it is solid—holding bachelor’s degrees in both Electrical and Mechanical Engineering from the University of Texas at Dallas and Texas A&M University, respectively, a J.D. and an MBA from Southern Methodist University, along with completing the General Management Program at the Wharton School at the University of Pennsylvania —David offers a distinctively strategic perspective in this specialized legal domain. 

His multifaceted expertise demonstrates his capacity to transcend traditional legal strategies, offering his clients not just defense, but a competitive advantage in various industries including technology, medical devices, cosmetics, and telecommunications. 

David is a founding partner of Carstens, Allen & Gourley and has been a pivotal figure on multiple boards. His ability to navigate the complexities of IP law, combined with his technical and business acumen, places him at the forefront of the field.

Thank you for taking the journey to product mastery and learning with me from the successes and failures of product innovators, managers, and developers. If you enjoyed the discussion, help out a fellow product manager by sharing it using the social media buttons you see below.

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