How product managers can make OKRs drive real results

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TLDR

In my recent conversation with Ben Lamorte, the world’s most experienced OKR coach and founder of OKRs.com, we explored how product managers and leaders can transform their approach to Objectives and Key Results (OKRs). Ben shared insights about why many OKR implementations fail and how to avoid common pitfalls. The key to success lies in focusing on measurable outcomes, maintaining transparency, and avoiding the temptation to create too many OKRs. Whether you’re just starting with OKRs or looking to improve your existing implementation, this comprehensive guide will help you create an effective OKR framework that drives real results.

Key Topics:

• Understanding OKRs: Their evolution from Intel’s early days to modern implementation
• Common pitfalls: The top reasons why OKR programs fail and how to avoid them
• Implementation strategies: Key factors for successful OKR deployment
• Practical guidelines: Choosing the right cycle length and organizational levels
• Success factors: The importance of transparency and outcome-focused metrics
• Change management: How to transition your team to effective OKR usage

Introduction

Does the mention of OKRs make you break into a cold sweat, or does it energize you with a sense of purpose? Whether you’re nodding in recognition or scratching your head wondering what OKRs even are, you’re about to discover how this powerful framework can transform your work life. In this episode, we’ll cut through the confusion and show you exactly how to turn Objectives and Key Results from a dreaded management mandate into your secret weapon for driving success. Miss this episode, and you risk continuing to struggle with misaligned priorities, unclear metrics, and the frustration of not seeing how your work impacts the bigger picture.

With us is a true OKR expert, Ben Lamorte. Ben has more OKR coaching experience than anyone. Consequently, he has become the coach to OKR coaches. He has also helped business leaders and organizations to define and make measurable progress on their most important goals, guiding more than a hundred organizations in deploying OKRs. He is the founder of OKRs.com, which provides resources and coaching services. He co-authored Objectives and Key Results: Driving Focus, Alignment, and Engagement and authored The OKRs Field Book.

Understanding OKRs: From Intel to Modern Product Teams

The evolution of Objectives and Key Results (OKRs) began at Intel during the 1970s and 1980s, where Andy Grove transformed the traditional Management by Objectives (MBO) system into something more dynamic and outcome-focused. He decoupled objectives, which are broad qualitative statements, from their specific measurable results, creating a framework that would eventually reshape how organizations set and achieve goals.

While MBOs were typically tied directly to bonuses, OKRs intentionally separate performance measurement from goal setting. This separation encourages teams to think bigger and take calculated risks without fear of compensation impacts. Here’s how the two approaches differ:

Aspect Traditional MBOs OKRs Compensation Link Directly tied to bonuses Deliberately separated from compensation Goal Structure Combined goals and metrics Separated objectives from measurable results Review Cycle Usually annual More frequent (e.g., two- or four-month cycles) Transparency Often private between manager and employee Highly transparent across organization

Core Components of Effective OKRs

Ben emphasized that OKRs serve as a critical thinking framework rather than just a goal-setting tool. The objective answers the question “What is the most important area to focus on?” while key results address “How will we know we’ve achieved it?” This structure creates clarity and alignment across teams by:

• Establishing clear, measurable targets that indicate progress toward objectives
• Creating a common language for discussing goals across the organization
• Enabling teams to understand how their work contributes to larger organizational goals
• Promoting regular check-ins and adjustments based on measurable progress

As organizations like Oracle and Google adopted and refined the OKR framework, they demonstrated its effectiveness in driving alignment and results. These companies used OKRs as a communication tool, ensuring everyone spoke the same language about priorities and progress. This common understanding became particularly valuable for product teams, who often need to coordinate efforts across multiple departments and stakeholders.

The beauty of this system lies in its flexibility and focus on outcomes rather than activities. For product managers, this means shifting conversations from feature lists and deadlines to measurable impacts and customer value. This outcome-focused approach helps teams stay aligned on what truly matters while maintaining the agility to adjust their approach based on real results.

Common OKR Implementation Failures and How to Avoid Them

Some people have tried using OKRs and don’t like them. I asked Ben what reasons he has seen for this. Ben shared that the landscape of OKR implementation changed after 2018, when John Doerr’s book Measure What Matters sparked widespread interest in the framework. While the book effectively conveyed why organizations should implement OKRs, it left many teams struggling with practical implementation. Before this, most organizations that used OKRs were doing a pretty good job. After, more organizations wanted to start using OKRs, but many failed because they didn’t have a good reason to use them and had no idea how to use them effectively.

Ben pointed out several pitfalls that often derail OKR implementations. Understanding these common failure points is essential for product managers and leaders who want to ensure their OKR program drives real value rather than becoming another administrative burden.

• Using too many OKRs: OKRs are supposed to help an organization focus on the most important areas of progress, but some organizations use OKRs for every task.
• Confusing tasks with key results: An action like “update the blog” is a task, not a key result. Key results should be measurable outcomes that tells the team whether they are making positive progress, like “200 people sign up for the demo after reading the blog post.”
• Only one name next to every key result: Measure What Matters teaches that only one person should be accountable for every key result, but in many cases this is the wrong approach and causes teams to struggle with cross-functional alignment. Instead, enable cross-functional ownership when appropriate. For example, if a key result depends on both marketing and IT, assign two names to that key result.
• No name next to a key result: Ensure someone is accountable to every key result.
• Every key result written as commit-level: There are two types of key results: commit, which are achievable, and stretch, which are moonshots. Most teams only make lists of commit results, causing them to not stretch themselves enough. Other times, they have stretch results on their commit lists, but don’t identify them as stretch results. Instead, consider listing one commit result and one stretch result for each level.
• OKRs tied to bonuses
• Direct cascade: The company sets objective and key results, and a department adopts one of the key results as their objective. This limits the department’s thinking to the key results selected by the company and ignores the difference between objectives and key results.
• Failing to define why the objective is important and why it is important now
• Making OKRs a compliance system: Treat OKRs as a critical thinking framework, not a performance management system.
• OKRs at the individual level: When a company has team OKRs and individual OKRs for each person, the team members will prioritize their individual OKRs, even though the team OKRs are more important to the company.

Many companies have challenges implementing OKRs. If your organization is starting to use OKRs, don’t start blindly rolling them out as fast as you can. Take time to be thoughtful about why you’re doing it and what problem you’re trying to solve.

Transparency

Unlike traditional goal-setting approaches that keep objectives private between manager and employee, OKRs should be visible across the organization, enabling better alignment and collaboration. John Doerr’s startup companies would even write their OKRs in the bathroom for everyone to see.

Key Success Factors for OKR Implementation

The Importance of Alignment around Deployment Parameters

Successful implementation of OKRs requires alignment on answers to ten questions about deployment parameters before rolling out OKRs. These parameters help organizations avoid common pitfalls and create a framework that works for their specific context. All ten questions are in Ben’s book and on his website, but some key considerations include:

• Cycle duration: Choosing between quarterly, four-month, or six-month cycles based on business rhythm
• Organizational levels: Determining where in the organization to implement OKRs
• Goal-setting approach: Balancing commitment targets with stretch goals
• Cross-functional alignment: Establishing mechanisms for collaboration across teams
• Review cadence: Setting up regular check-ins to monitor progress

Choosing the Right Cycle Length

Ben challenged the conventional wisdom about quarterly OKR cycles, sharing insights about what actually works best for different organizations:

Cycle Length Best For Considerations Two Months Fast-moving tech companies High agility, but intensive management required Four Months Most product organizations Balances stability with adaptability Six Months Enterprise/regulated industries Allows for longer-term initiatives Annual Rare cases only Generally too long for effective OKRs

The Five Mantras for Success

Ben has five mantras for successful OKR implementation, but in our discussion he shared just three. You can find the others in his book.

Mantra Key Principle Application Less is More Focus on fewer, high-impact objectives Limit OKRs to the most critical priorities Crawl, Walk, Run Start small and scale gradually Begin with one organizational level before expanding Outcomes, Not Outputs Focus on measurable impact Define success through results, not activities

A Real-World Success Story: Transforming Through OKRs

During our conversation, Ben shared a success story that illustrates how organizations can transform their goal-setting approach through OKRs. The case involved a trading card marketplace company that initially struggled with their OKR implementation but ultimately achieved remarkable results by adapting the framework to their specific needs.

This company got half of their annual business from one conference. Their CEO set an audacious goal for this conference to be a wild success. He clearly defined the why and why now around that objective, but the conference was eight months away, much longer than a typical OKR cycle. Ben encouraged the company to set an OKR for the conference anyway.

The CEO was initially unable to identify measurable outcomes that would show whether the conference was a success. He said the team would just have a feeling afterward about whether it went well or not. However, after talking with Ben, he identified several trackable metrics, like the number of private demos they complete. The team came up with OKRs that everyone in the organization was able to align around. They made two times their expected annual sales within the first week after the conference. This huge success was because everyone at the company was focused on a single goal with clear, measurable outcomes.

Ben advised that if you have a big event, don’t hesitate to write an OKR around that event’s timeframe. Tune your OKRs to what’s happening in your business.

Conclusion

Throughout our discussion, Ben Lamorte shared invaluable insights about making OKRs work effectively for product teams and organizations. His experience as the most experienced OKR coach revealed that success with OKRs isn’t about rigid implementation of rules, but rather about thoughtful adaptation of the framework to each organization’s unique context. The key lies in identifying measurable outcomes, maintaining transparency across teams, and ensuring that OKRs serve as a bridge between strategic planning and day-to-day execution.

For product managers and leaders looking to implement or improve their OKR process, the path forward is clear: start with clear deployment parameters, focus on meaningful outcomes, embrace transparency, and maintain the flexibility to adapt as you learn. By avoiding common pitfalls like over-cascading, task-based key results, and compliance-driven implementation, teams can transform OKRs from a management mandate into a powerful tool for driving focus, alignment, and exceptional results. The journey may take several cycles to perfect, but the potential impact on organizational alignment and product success makes it well worth the investment.

Useful links:

• Read about the 10 OKR deployment parameters
• Learn more about Ben’s OKRs coaching
• Check out The OKRs Field Book
• Learn more about OKRs Coach Network

Innovation Quote

“If you want something new, you have to stop doing something old.” – Peter Drucker 

Application Questions

1. Looking at your current product team’s goals, how could you transform task-based objectives into outcome-focused OKRs? For example, instead of “Launch feature X,” what measurable customer or business outcomes would indicate real success?
2. How could your team use cross-functional OKRs to improve collaboration between product, engineering, and other departments? What shared outcomes could create better alignment across these teams?
3. Thinking about your organization’s business rhythm, what OKR cycle length (2-month, 4-month, or 6-month) would work best for your product development process? How could you align OKR cycles with major product milestones or market events?
4. How could you modify your current OKR process to include both commitment-level and stretch goals? What would be appropriate stretch targets that could inspire innovation without causing team burnout?
5. What steps could you take to increase transparency around product team OKRs? How could making objectives and progress more visible help improve alignment with other teams and stakeholders?

Bio

Ben Lamorte is a leading figure in the space of “Objectives and Key Results” (OKRs). He has more OKRs coaching experience than anyone on the planet. Lamorte coaches business leaders focused on defining and making measurable progress on their most important goals. He started OKRs.com in 2014 and over the past decade has helped 200+ organizations based in 20+ countries implement OKRs including eBay, Adobe, Capital One, 3M, Booking.com, Zalando, and Nike. After co-authoring one of the first books dedicated to OKRs, Lamorte wrote The OKRs Field Book, the first book written specifically for OKRs coaches published by Wiley in 2022. Ben studied Engineering and Mathematics at University of California, Davis and holds a graduate degree in Management Science & Engineering from Stanford University.

Thanks!

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.

A product manager’s guide to breaking free from reactive problem solving

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TLDR

In my recent conversation with Doug Hall, master of turning chaos into clarity, we explored how product managers and innovation leaders can break free from reactive problem-solving and create more value through proactive innovation. Doug shared that the average manager wastes 3.5 hours daily fixing problems, with 75% of issues stemming from broken systems rather than employee mistakes. Even more concerning, products typically lose 50% of their innovative value during development as unique ideas get compromised to fit existing systems. Doug offered practical solutions through three powerful frameworks that can transform how teams approach innovation and problem-solving.

Key Topics:

• How to define problems effectively using the Yellow Card method, inspired by military Commander’s Intent principle
• Creating solutions through structured “Create Sessions” that leverage stimulus, diversity of thought, and fear reduction
• Six types of innovation stimulus, including patent mining and wisdom mining from academic sources
• Using the Deming Cycle (Plan-Do-Study-Act) to systematically reduce risks in product development
• Transforming organizational culture by focusing on system improvement rather than individual blame

Introduction

Ever feel like your organization is stuck in an endless cycle of putting out fires instead of truly innovating? You’re not alone in that frustration. Today, we’re diving into a well-practiced approach that will transform how you and your team solve problems and drive innovation. Our returning guest, Doug Hall, is a master of turning chaos into clarity – he’s not just the founder of Eureka! Ranch and co-founder of the Dexter Bourbon Distillery, but has spent decades helping companies break free from innovation roadblocks. Doug also has a new book hot off the press titled Proactive Problem Solving: How Everyone Can Fix Problems & Find Ideas for Working Smarter!

Doug joined us in episode 518 and is back to share battle-tested strategies that will help you fix problems faster and smarter.

Proactive Problem Solving

Doug was motivated to write Proactive Problem Solving by two pieces of data showing the impact of reactive problem solving:

• The average manager wastes 3.5 hours every day dealing with problems. Seventy-five percent of these issues stem from broken systems, bureaucracy, and inefficient processes, while only 25% come from employee mistakes.
• Products typically lose 50% of their innovative value during the development process. This happens because unique ideas get repeatedly compromised to fit existing systems, rather than adapting our systems to support innovation.

We discussed the book’s three main sections:

• Defining Problems
• Creating Solutions
• Driving out Risks

Defining Problems

Doug shared an approach for defining problems borrowed from military strategy – the Commander’s Intent framework. This methodology emerged from lessons learned during World War II and the Korean War, where military leaders discovered that simply telling teams what to do wasn’t enough. Instead, they needed to explain why it matters.

The Three Components of Commander’s Intent

• What needs to be done – The clear direction that points the organization toward a specific goal
• Why it matters – The deeper purpose that provides motivation and context for the work
• Boundaries and scope – Clear guidelines for what’s in and out of scope for the solution

The Yellow Card

The Yellow Card tool helps teams capture and communicate both problems and potential solutions effectively. Its first section focuses on problem definition, clearly stating what the problem is and why solving it matters. This why component is particularly important as it serves as the motivational energy source when teams face challenges or setbacks.

The second section of the Yellow Card focuses on communicating solutions, including how the solution works, its key benefits, and an easy next step for learning more. This last component – the easy next step – helps reduce resistance to change. When presenting new ideas, especially those that challenge existing systems, people naturally feel stress. By providing a simple, low-risk way to learn more about the solution, teams can build confidence gradually and increase buy-in for larger changes.

Structure of the Yellow Card Tool

Section Components Purpose Problem Definition What + Why Creates focus and motivation Solution Elements How it works + Key benefits Outlines approach and value Next Steps Easy actions for learning more Reduces resistance to change

The Yellow Card serves a dual purpose: it helps teams think through problems more clearly and provides a structured way to communicate solutions to stakeholders. Doug shared that this approach has proven so effective that when used in a Canadian TV show called “Backyard Inventor,” it helped inventors achieve a 100% success rate in pitching their ideas to CEOs. The clear structure helped them present their innovations in a way that made the value immediately apparent to decision-makers.

Creating Solutions

The Three Innovation Pillars

Successful solution creation rests on three innovation pillars, each backed by extensive research and quantitative data. These principles aren’t just theoretical – they’re practical tools that any product team can implement to enhance their innovation process.

Principle Description Impact Stimulus Disruptive elements that force new thinking Creates foundation for new ideas Diversity of Thought Multiple perspectives examining the stimulus Multiplies impact exponentially Fear Elimination Creating safety for sharing ideas Prevents self-censoring of solutions

Create Sessions

Doug uses Create Sessions to help teams stimulate ideas. These structured meetings come in different formats depending on the scope of the problem and the organization’s needs. He outlined two main approaches that product teams can implement.

Small-Scale Create Sessions

These one-hour sessions work well for immediate operational challenges that work teams face. These sessions can include the following elements:

• Problem Definition: Begin by identifying the what and why of the problem using the Yellow Card framework
• Stimulus Introduction: Present relevant stimulus materials to the team
• Mind Mapping: Create visual connections between different ideas and perspectives
• Solution Development: Move quickly to actionable solutions

Large-Scale Create Sessions

For company-wide challenges or significant product innovations, Doug recommended a two-level approach: Start with an initial small-scale create session, then go deeper to take your ideas to the next level.

The key to successful Create Sessions lies in proper preparation, particularly in developing effective stimulus materials. This two-level approach mirrors how successful entrepreneurs naturally work. While corporate environments often expect perfect planning and immediate success, true innovation requires multiple cycles of creation, testing, and refinement.

At Eureka Ranch, they often run sessions over several days, allowing teams to generate ideas, test them, blow them up, and start over again multiple times. This iterative approach, while sometimes uncomfortable for traditional corporate cultures, consistently produces stronger results because it eliminates the pressure of trying to plan everything perfectly from the start.

The Create Session framework also addresses a common challenge in innovation – the tendency to rely on what Doug called the “brain drain” or “suck” method of creativity, where teams try to extract ideas from people’s heads without providing fresh stimulus or perspectives. By contrast, Create Sessions provide a structured environment that makes innovation more reliable and enjoyable for participants while producing better results for the organization.

Six Sources of Innovation Stimulus

Stimulus should be disruptive, forcing you to stop and think. Doug shared six specific types of stimulus that teams can use to spark innovation:

• Patent Mining: Exploring public domain patents for solution frameworks. Doug noted that 75% of patents are in the public domain, providing free access to detailed solution recipes.
• Wisdom Mining: Leveraging academic articles and research. This approach helped Doug build and sell an entire company based on insights from academic publications.
• Insight Mining: Understanding customer thinking and needs
• Market Mining: Analyzing competitive approaches and market trends
• Future Mining: Exploring emerging trends and possibilities
• Unrelated Mining: Drawing inspiration from random, thought-provoking sources

To make these stimulus sources more actionable, Doug’s colleague Maggie Slovonic developed the Spark Deck approach. A Spark Deck combines disruptive images, videos, facts, or research with thought-provoking prompts that help teams make new connections. Each slide pairs a piece of stimulus with questions like “How might we use this?” or “How could we twist this concept?” This structured approach helps teams move beyond simple brainstorming to generate more innovative solutions.

Driving Out Risks

When discussing risk reduction in product development, Doug drew heavily from W. Edwards Deming’s work, particularly the Plan-Do-Study-Act (PDSA) cycle. While many organizations use the similar Plan-Do-Check-Act cycle for implementation, PDSA is specifically designed for discovering and validating new approaches.

The PDSA Cycle Components

Stage Purpose Key Activities Plan Hypothesis Development Define what success looks like and how to achieve it Do Implementation & Measurement Execute the plan and document results Study Deep Analysis Understand why results occurred (success or failure) Act Decision Making Choose next steps based on learning

The Study phase is particularly important yet often overlooked. He illustrated this with a story about developing their Woodcraft Finishing process for whiskey. The team conducted 72 tests in seven days, meticulously documenting each attempt. When test number 72 failed on a Friday night, they initially felt defeated. However, by returning to their documentation the next day and deeply studying why each attempt had worked or failed, they discovered that they had misinterpreted the results of test number 13. This insight led to test number 73, which became their breakthrough success and is now patented in 51 countries.

The PDSA cycle offers several key benefits for product development:

• Risk Reduction: Each iteration builds understanding and reduces uncertainty
• Learning Acceleration: Structured documentation captures insights that might otherwise be lost
• Fear Reduction: The expectation of multiple iterations removes the pressure for immediate perfection
• Culture Change: Teams develop comfort with experimentation and learning from failure

Doug noted that about 98% of the time, teams need multiple PDSA cycles to reach their desired outcome. This iterative approach might seem time-consuming, but it actually accelerates development by ensuring teams learn from each attempt rather than repeating the same mistakes. He also shared how they’ve adapted this approach for rapid testing, developing systems that can test product concepts in 24 hours at 5% of the normal cost.

The key to making PDSA work effectively is maintaining a clear connection to the original what and why from the Commander’s Intent and Yellow Card. This core purpose provides the motivation to persist through multiple iterations and keeps teams focused on their ultimate goal rather than getting discouraged by initial failures.

Conclusion

Throughout our conversation, Doug Hall shared how product managers and innovation leaders can break free from reactive problem-solving and create more value through proactive problem solving. His research showed that the combination of wasted management time (3.5 hours daily) and value loss during product development (50%) creates a massive opportunity for improvement. By implementing the frameworks he shared – the Yellow Card for problem definition, Create Sessions for solution generation, and the PDSA cycle for risk reduction – teams can transform how they approach innovation and problem-solving.

The key to success lies in shifting focus from individual blame to system improvement, supported by the right tools and motivation. As Doug emphasized, true culture change happens when we empower employees to identify and solve systemic problems that affect their daily work. By making this shift, organizations can not only recover wasted time and preserve innovative value but also create an environment where breakthrough products can thrive. For product managers and innovation leaders, this provides a clear path forward: Focus on the systems, empower your teams with the right tools, and create an environment where proactive problem-solving can flourish.

Useful links:

• Learn more about Eureka! Ranch
• Check out Doug’s book, Proactive Problem Solving on Amazon or at an independent bookseller near you
• Check out Doug’s other books

Innovation Quote

“Ninety-four percent of the problem is the system. Six percent is the worker.” – W. Edwards Deming

Application Questions

1. Looking at your last three product launches, how could you identify where systemic issues caused compromises to the original innovative vision? What patterns emerge about which systems (manufacturing, sales, marketing, etc.) most frequently force compromises in your organization?
2. How could you implement small-scale Create Sessions (1-hour) with your team to address immediate product development challenges? What types of stimulus (patents, academic articles, market research) would be most relevant for your current product challenges?
3. Thinking about a current product development challenge, how could you use the Yellow Card method to clearly articulate both the problem and its importance to stakeholders across your organization? How might this change the way your team approaches the challenge?
4. How could your team modify its current development process to incorporate more deliberate Study phases after each iteration? What specific changes to your documentation and review processes would make learning from failures more systematic?
5. How could you shift your team’s focus from fixing immediate problems to identifying and improving the underlying systems that cause those problems? What specific benefits would motivate your team members to embrace this change?

Bio

Doug Hall is on a relentless, never-ever ending quest to enable everyone to think smarter, faster and more creatively.  His learning laboratories over the past 50+ years have included 10 years at Procter & Gamble where he rose to the rank of Master Inventor shipping a record 9 innovations in a 9 months and 40+ years as an entrepreneur including as founder of the Eureka! Ranch in Cincinnati Ohio – where he and his team have invented and quantified over 20,000 innovations for organizations such as Nike, Walt Disney, USA Department of Commerce, American Express and hundreds more.  Doug’s newest book,  out in December, PROACTIVE Problem Solving, was inspired by his experiences founding and leading a fast-growing manufacturing company, the Brain Brew Bourbon Distillery. Despite the COVID pandemic, Brain Brew grew from shipping a few thousand cases to shipping over 100,000 cases a year by enabling employee engagement. 

Thanks!

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.

The product manager’s journey from Individual Contributor to Chief Product Officer

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TLDR

Kimberly Bloomston’s journey from individual contributor to Chief Product Officer at LiveRamp demonstrates the key transitions and skills needed at each level of product management leadership. Her path highlights how responsibilities evolve from hands-on product development to strategic business leadership, emphasizing the importance of continuous learning, vulnerability, and strong relationship-building skills.

Key Topics:

• Career progression stages in product management, from IC to CPO
• Transition from tactical to strategic responsibilities at each level
• Evolution of stakeholder management and leadership requirements
• Importance of vulnerability and continuous learning in product leadership
• Role of business acumen in product management success
• Critical skills needed at different career stages
• Value of cross-functional understanding and relationships
• Impact of organizational structure on product leadership
• Balance between product expertise and business leadership
• Strategies for successful career transitions in product management

Introduction

In this episode, I interviewed Kimberly Bloomston, Chief Product Officer at LiveRamp, to explore her journey from individual contributor (IC) to executive leadership in product management. Kim’s unique perspective comes from climbing every rung of the product management career ladder, experiencing firsthand the evolving responsibilities and challenges at each level.

The path from IC to Chief Product Officer isn’t just about gaining more responsibility – it’s about transforming how you think about product development, team leadership, and business strategy. Whether you’re aiming for your first product management role or setting your sights on the C-suite, understanding these career dynamics can help you navigate your own path to product leadership success.

Early Career Foundation: Building a Base for Product Leadership

Kim’s journey into product management began with an unconventional blend of philosophy and computer science studies in college. This unique combination developed both her analytical thinking skills and her ability to question assumptions – capabilities that would later prove valuable in her product career. Growing up in a tech-friendly household with an entrepreneurial father who owned retail businesses gave her early exposure to both technology and business operations.

Her first professional role was with a retail industry consulting company, where she started as a part-time employee during college. Over ten years, she rose through the ranks until everyone in the company reported to her. The company operated a software platform for their call center, managing customer communications while ensuring compliance with state regulations. As VP of Operations, Kim worked with third-party engineering consultants to improve the platform’s ROI and customer outcomes.

It was during this time that Kim discovered her passion for product management. She shared a story about finding a way to save a hundred dollars per week through code automation. When discussing this achievement with her brother, an engineer, he pointed out that what she was doing – finding ways to improve processes and outcomes through technology – was essentially product management. This revelation led her to refocus her career from general business operations to technology product management.

Key Learnings from Early Career Experience

• Cross-functional understanding: Her operational role provided valuable insights into how different business functions work together, from support and services to sales and customer success
• Business metrics expertise: Managing operations gave her deep understanding of business KPIs and how they impact different teams
• Leadership experience: Early management responsibilities helped develop crucial people skills before entering product management
• Technical foundation: Growing up with technology and working with engineering teams built technical credibility

This foundation proved instrumental in Kim’s later product management roles. Her experience managing people, understanding business operations, and working with technology teams gave her a unique perspective that many product managers develop only later in their careers. Most importantly, it sparked her passion for using technology to solve real business problems – the core essence of product management.

These early experiences highlight an important lesson for aspiring product leaders: there’s no single “right” path into product management. Whether you’re coming from engineering, business operations, or another field entirely, your unique background can provide valuable perspective and skills for a successful product management career.

Transitioning to Individual Contributor (IC) Product Manager

Kim’s entry into product management came with a unique twist – she stepped down from an executive role to become a senior product manager. While most product managers work their way up to leadership positions, she chose to start fresh in a role that would let her work directly on product development.

As a new product manager, Kim faced the common challenge of understanding her company’s technical landscape. She joined a facial recognition company that built hardware and software primarily for government agencies. The company wanted to expand into commercial markets, particularly retail – a perfect fit for Kim’s background. However, she still needed to learn the company’s products, technology, and internal language.

Strategies for Success as a New Product Manager

Challenge Solution Approach Learning Technical Language Extensive listening in team meetings, especially scrum and QA sessions Understanding Products Reading documentation and sitting with different teams Building Credibility Being transparent about knowledge gaps while showing consistent progress Contributing Value Leveraging industry expertise while learning technical aspects

One of Kim’s most valuable insights was about the importance of asking “dumb questions.” She found that being vulnerable about what she didn’t know actually added value to the team. New perspectives often help challenge assumptions and bring fresh thinking to long-standing problems. Her approach was to acknowledge knowledge gaps openly while demonstrating steady progress in understanding the technical aspects of the role.

Kim developed what she called a “superpower” – the ability to remember information without fully understanding it initially, then gradually connecting the dots as her knowledge grew. She would often realize the meaning of something she’d heard weeks earlier, creating connections between different aspects of the business and technology.

Success as an IC product manager isn’t just about what you know coming in – it’s about your ability to learn, adapt, and bring new perspectives to the team. Whether transitioning from another field or starting fresh in product management, the key is to balance humility about what you don’t know with confidence in what you can contribute.

Director of Product: Expanding Scope and Influence

The transition from individual contributor to Director of Product marked a significant shift in Kim’s responsibilities and focus. After successfully bringing a retail product to market, she moved into a director role where she managed multiple product managers and took on broader strategic responsibilities. This role expanded beyond individual product features to encompass entire product lines and their impact on the business.

Key Changes in Responsibilities

• Roadmap Planning: Rather than focusing on individual features, directors need to plan comprehensive roadmaps across multiple products and teams
• Customer Engagement: More frequent and strategic customer interactions, including managing escalations and leading customer advisory boards
• Stakeholder Management: Building relationships across various organizational levels, from individual contributors to executive teams
• Revenue Focus: Greater emphasis on business outcomes and revenue impact of product decisions

One of the most significant changes Kim experienced was the depth of stakeholder alignment required. As a director, she needed to coordinate efforts across multiple engineering teams, platform teams, and both pre-sales and post-sales organizations. This led to the creation of “product success teams” – cross-functional groups that included leaders from various departments working together to ensure product success in the market.

Product Success Team Focus Areas

Area Key Considerations Market Strategy Competitive analysis, opportunity sizing, pricing Customer Success Time to value, implementation challenges, support needs Sales Enablement Sales team training, market messaging, deal support Technical Implementation Integration requirements, scalability, maintenance

Customer interaction also evolved at the director level. Beyond handling escalations, Kim found herself hosting customer development partner groups, speaking at industry events, and participating in strategic sales calls. These interactions weren’t just about immediate product needs – they focused on building long-term partnerships and ensuring customers saw value in the product vision and roadmap.

The director role required a delicate balance between tactical execution and strategic planning. While individual contributors focus primarily on getting features right, directors need to ensure that all product initiatives align with broader business goals and market needs. This transition highlighted the importance of developing both leadership skills and strategic business acumen alongside traditional product management capabilities.

Vice President of Product: Leading Through Others

Kim described her transition to Vice President of Product as her biggest career shift. While she had previously been a VP in operations, the VP of Product role demanded a fundamentally different approach to leadership and product strategy. This position was a departure from hands-on product work to leading through others and shaping organizational direction.

Core Changes in Role Focus

Area Key Responsibility Shift Team Management Leading managers instead of individual contributors Product Vision Developing broader organizational vision and storytelling Financial Oversight Managing budgets and business outcomes Executive Engagement Regular interaction with executive leadership

One of the most significant changes was stepping away from day-to-day product backlogs. While Kim occasionally found herself wanting to dive into tactical details, she learned that her role needed to focus on broader strategic initiatives. Her primary responsibility shifted to coaching teams, developing the practice of product management, and creating compelling narratives about the product vision that could inspire both the organization and customers.

The VP role also brought new financial responsibilities and accountability. While Kim didn’t directly own a P&L, her compensation structure became tied to business outcomes such as profitability, product growth, and customer satisfaction metrics. This alignment of incentives with business results changed how she approached product decisions and strategy development.

Key Success Factors at VP Level

• Storytelling Ability: Developing skills to communicate product vision effectively to diverse audiences, from development teams to executive stakeholders
• Strategic Thinking: Moving beyond individual product features to focus on portfolio-level decisions and market positioning
• Business Acumen: Understanding and influencing key business metrics, including revenue growth, customer retention, and profitability
• Leadership Development: Building and coaching a team of product managers and directors to execute effectively

The role also required a different approach to stakeholder management. Instead of working primarily with individual contributors, Kim needed to build strong relationships with other executives and senior leaders across the organization. This meant developing the ability to influence without direct authority and align different departments around common goals and objectives.

Chief Product Officer: Leading at the Executive Level

Chief Product Officer (CPO), Kim’s current role, brings new challenges and responsibilities at the executive level. As a member of the executive leadership team at LiveRamp, her focus has expanded beyond product organization to encompass overall business stewardship and strategic direction.

Executive Leadership Responsibilities

Responsibility Area Key Activities Board Engagement Regular reporting, strategic updates, vision alignment Business Leadership Contributing to overall company strategy and direction Shareholder Relations Public company responsibilities and investor communication Executive Team Collaboration Cross-functional strategic planning and execution

Kim’s primary team is the executive leadership team rather than just the product organization. This shift required viewing herself as a business leader first and a product leader second. Her role involves not just leading product strategy but contributing to all aspects of business operations and growth.

The position demands a comprehensive understanding of business operations across all functions. Kim explained that being a CPO means having both the right and responsibility to identify challenges and opportunities throughout the organization, not just within product development. This systemic view helps ensure alignment between product strategy and overall business objectives.

Organizational Structure Insights

Based on her experience, Kim shared valuable insights about product organization structure:

• Direct CEO Reporting: Product leadership should report directly to the CEO to ensure proper strategic alignment
• Engineering Alignment: In some cases, combining product and engineering under a Chief Product and Technology Officer (CPTO) role can be beneficial
• Business Integration: Product organization should be structured to facilitate close collaboration with all business functions
• Leadership Development: Focus on developing strong product leaders at all levels of the organization

The CPO role represents the evolution from product leadership to business leadership, requiring a delicate balance between maintaining product excellence and contributing to overall business success. It demands the ability to think systematically about the business while ensuring the product organization remains effective and aligned with company goals.

Key Success Factors Across All Levels: Leadership Lessons and Best Practices

Throughout our conversation, Kim emphasized several critical factors that contributed to success across all levels of the product management career ladder. Her insights revealed that while technical skills are important, the ability to learn, adapt, and build strong relationships often determines long-term success in product leadership roles.

Essential Skills for Product Leadership Success

Skill Area Impact on Success Vulnerability Enables learning, innovation, and authentic leadership Failure Management Promotes learning and creative problem-solving Continuous Learning Supports adaptation to new roles and challenges Relationship Building Facilitates cross-functional collaboration and influence

Critical Success Behaviors

• Embrace Learning Opportunities: Actively seek new challenges and be willing to step outside your comfort zone
• Build Strong Relationships: Invest time in understanding different functions and building trust across the organization
• Celebrate Failures: View failures as learning opportunities and encourage teams to take calculated risks
• Maintain Curiosity: Stay interested in both technical and business aspects of product development
• Practice Authentic Leadership: Lead with transparency and create safe spaces for innovation

Another key insight was the importance of understanding business fundamentals at every level. Whether as an IC or CPO, having a clear grasp of how different business functions operate and contribute to success helps product leaders make better decisions and build more effective relationships across the organization.

Conclusion

Kim’s journey from philosophy major to Chief Product Officer demonstrated that success in product management isn’t about following a predetermined path – it’s about continuously learning, adapting, and growing while staying true to core principles of innovation and customer focus. As Kim’s experience showed, each level brings new challenges and opportunities, requiring different skills, perspectives, and approaches to success. While technical knowledge and product expertise form the foundation, long-term success depends increasingly on leadership ability, strategic thinking, and business acumen as you progress up the career ladder.

For product managers aspiring to advance their careers, the key takeaway is the importance of continuous learning and adaptation. Whether you’re just starting as an IC or preparing for an executive role, focus on developing both the hard and soft skills needed for the next level while maintaining curiosity and openness to new challenges. Remember that there’s no single “right” path to product leadership – your unique experiences and perspectives can become valuable assets as you progress in your career. The most successful product leaders combine strong technical and business knowledge with the ability to build relationships, foster innovation, and drive organizational success through authentic leadership.

Useful links:

• Learn more about LiveRamp
• Connect with Kim on LinkedIn

Innovation Quote

“So many leaders fail to realize that without vulnerability there is no creativity or innovation. Why? Because there is nothing more uncertain than the creative process, and there is absolutely no innovation without failure.” – Brené Brown

Application Questions

1. How could you use Kim’s insights about vulnerability and “asking dumb questions” to create a more innovative culture within your product team? Consider specific situations where being more open about knowledge gaps might lead to better outcomes.
2. What steps could you take in your current role to develop the skills needed for your next career move in product management? Think about the gaps between your current responsibilities and those of the next level up.
3. How could your team implement some version of the “product success teams” concept Kim described? Consider which stakeholders you would include and what specific challenges this cross-functional approach might help solve.
4. Looking at your current approach to stakeholder management, how could you expand or modify your relationships to better align with the next level of product leadership? Think about which relationships might need more development.
5. Based on Kim’s experience with balancing metrics and strategic thinking, how could you adjust your current focus to better demonstrate business impact while maintaining strong product leadership? Consider what metrics you might need to pay more attention to.

Bio

Kimberly Bloomston is Chief Product Officer at LiveRamp where she heads the company’s global product organization with an emphasis on cloud infrastructure growth. Kimberly previously served as LiveRamp’s Senior Vice President of Product, Vice President of Core Platform and Data Marketplace and Head of Product, Data Marketplace and Application Experience.

With over 15 years’ of experience leading product management and business operations, Kimberly spearheads strategic initiatives that focus on maturing and expanding solutions in the midst of market and company transformation. She has held executive roles leading product, design and operations across a variety of software companies and industries, including higher education, security and data enablement. Kimberly has also led sales, partner programs, managed services and customer success over the course of her career. Prior to LiveRamp, Kimberly served in leadership positions at Ellucian, Digital Signal Corporation and The Zellman Group.

Kimberly loves tackling hard problems and is passionate about design thinking, storytelling, collaboration and enabling product operations to scale and grow a business. She resides in California with her family where she enjoys exploring the outdoors, working out in her home gym, making art and spending time with her family.

Thanks!

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.

Start 2025 with the essential knowledge areas that give product managers more influence and success

In 2024 I co-authored the 3rd edition of the Product Development and Management Body of Knowledge: A Guidebook for Product Innovation Training and Certification. The book describes the seven knowledge areas that professional product managers, innovators, and leaders must have mastery of. I’m bringing back the episode from 2024 where I introduced these seven knowledge areas as it is the perfect way to start your 2025. Take a few minutes to focus on your career development by listening to this episode.

TLDR

Product mastery is essential for creating successful products and driving innovation within organizations. This article explores the seven knowledge areas crucial for product managers and innovators, as outlined by the Product Development and Management Association (PDMA) Body of Knowledge.

These knowledge areas include product innovation management, strategy, portfolio management, process, design and development, market research, and culture and teams. By understanding and applying these concepts, product professionals can enhance their skills, increase their influence within their organizations, and create products that truly resonate with customers.

The article also discusses the importance of continuous learning in product management, the value of professional certifications like the New Product Development Professional (NPDP), and provides insights into resources for further development in the field.

Introduction to Product Mastery

Product mastery is a critical skill for professionals aiming to create successful products and drive innovation within their organizations. The concept of product mastery encompasses a wide range of knowledge areas and skills that enable product managers and innovators to excel in their roles.

This article introduces the seven essential knowledge areas for product mastery, as outlined by the Product Development and Management Association (PDMA) Body of Knowledge. These areas form the foundation of successful product management and innovation practices across various industries.

The Seven Knowledge Areas for Product Mastery

The PDMA Body of Knowledge identifies seven crucial knowledge areas that product professionals should master to achieve success in their roles:

1. Product Innovation Management
2. Strategy
3. Portfolio Management
4. Process
5. Design and Development
6. Market Research
7. Culture and Teams

Let’s explore each of these areas in detail to understand their importance in the product management landscape.

1. Product Innovation Management

Product innovation management serves as the foundation for all other knowledge areas. It encompasses the overarching principles and practices that guide the creation of new products and the improvement of existing ones. This area focuses on:

• Understanding customer needs and market opportunities
• Generating and evaluating new product ideas
• Managing the innovation process from concept to launch
• Fostering a culture of innovation within the organization

Mastering product innovation management enables product professionals to drive meaningful change and create products that truly resonate with customers.

2. Strategy

Strategy plays a crucial role in aligning product development efforts with organizational goals. This knowledge area covers:

• Developing and implementing product strategies
• Aligning product roadmaps with business objectives
• Identifying and prioritizing market opportunities
• Competitive analysis and positioning

By mastering strategic thinking, product managers can ensure that their efforts contribute to the overall success of their organization.

3. Portfolio Management

Portfolio management focuses on optimizing the mix of products and projects within an organization. Key aspects include:

• Balancing resources across multiple products or projects
• Prioritizing initiatives based on strategic fit and potential value
• Managing risk across the product portfolio
• Evaluating and selecting new product opportunities

Effective portfolio management ensures that organizations invest in the right products and initiatives to maximize their return on investment.

4. Process

The process knowledge area covers the various methodologies and frameworks used to guide product development from idea to market. This includes:

• Stage-gate processes
• Agile and lean product development methodologies
• Design thinking approaches
• Continuous improvement and iteration

Mastering different product development processes allows product managers to choose the most appropriate approach for each project and adapt to changing market conditions.

5. Design and Development

Design and development focus on the actual creation of products, encompassing both the creative and technical aspects. This area includes:

• User experience (UX) and user interface (UI) design
• Technical architecture and engineering
• Prototyping and testing
• Quality assurance and product refinement

A strong understanding of design and development principles enables product managers to collaborate effectively with cross-functional teams and ensure the creation of high-quality products.

6. Market Research

Market research is crucial for understanding customer needs, market trends, and competitive landscapes. This knowledge area covers:

• Qualitative and quantitative research methodologies
• Customer segmentation and persona development
• Competitive analysis and market sizing
• Voice of the customer (VoC) programs

By mastering market research techniques, product managers can make data-driven decisions and create products that truly meet customer needs.

7. Culture and Teams

The culture and teams knowledge area focuses on the human aspects of product management, including:

• Building and leading high-performing product teams
• Fostering a culture of innovation and collaboration
• Managing stakeholders and cross-functional relationships
• Developing leadership skills for product managers

Understanding how to create a positive team culture and effectively lead product teams is essential for long-term success in product management.

The Importance of Continuous Learning in Product Management

The field of product management is constantly evolving, with new methodologies, tools, and best practices emerging regularly. As such, continuous learning is crucial for product professionals to stay ahead of the curve and maintain their effectiveness in their roles.

Professional Development Opportunities

There are various ways for product managers to continue their professional development:

Method Description Benefits Certifications Formal recognition of product management expertise (e.g., NPDP) Demonstrates proficiency, enhances credibility Online Courses Self-paced learning on specific product management topics Flexible, targeted skill development Conferences Industry events featuring speakers and networking opportunities Exposure to new ideas, peer learning Podcasts Audio content discussing product management trends and practices Convenient learning during commutes or downtime Books In-depth exploration of product management concepts Comprehensive understanding of specific topics

The Value of Professional Certifications

Professional certifications, such as the New Product Development Professional (NPDP) offered by PDMA, can provide significant value to product managers. These certifications:

• Demonstrate a commitment to professional development
• Validate expertise in product management practices
• Enhance credibility with colleagues and stakeholders
• Provide a structured framework for learning and skill development

While certifications are not always required for product management roles, they can be a valuable differentiator in competitive job markets and help professionals advance their careers.

Applying Product Management Knowledge in Practice

Understanding the seven knowledge areas is just the first step in achieving product mastery. The real value comes from applying these concepts in real-world situations. Here are some strategies for putting product management knowledge into practice:

1. Start with self-assessment: Evaluate your strengths and weaknesses across the seven knowledge areas to identify areas for improvement.
2. Set learning goals: Prioritize specific skills or knowledge areas to focus on and create a plan for developing them.
3. Seek diverse experiences: Look for opportunities to work on different types of products or in various industries to broaden your perspective.
4. Collaborate and share knowledge: Engage with other product professionals through networking events, online forums, or mentorship programs.
5. Experiment with new techniques: Try implementing new methodologies or tools in your product development process and evaluate their effectiveness.

By actively applying and refining your product management skills, you can continually improve your ability to create successful products and drive innovation within your organization.

The Evolution of Product Management

Product management as a discipline has a rich history dating back to the 1930s when it emerged as “brand management” at Procter & Gamble. Since then, the field has evolved significantly, adapting to changing market conditions, technological advancements, and shifting consumer expectations.

Key Milestones in Product Management History

Decade Development 1930s Brand management introduced at Procter & Gamble 1960s Emergence of formal product management roles in technology companies 1980s Rise of customer-centric approaches and market-driven product development 1990s Introduction of Agile methodologies in software development 2000s Growth of digital product management and user experience focus 2010s Emphasis on data-driven decision making and product analytics 2020s Integration of AI and machine learning in product management practices

Understanding the evolution of product management can provide valuable context for current practices and help product professionals anticipate future trends in the field.

Challenges and Opportunities in Modern Product Management

Today’s product managers face a unique set of challenges and opportunities in their roles:

Challenges:

• Rapidly changing market conditions and customer expectations
• Increasing complexity of products and technologies
• Balancing short-term demands with long-term strategic goals
• Managing cross-functional teams in remote or hybrid work environments
• Navigating ethical considerations in product development and data usage

Opportunities:

• Leveraging data and analytics for more informed decision-making
• Embracing new technologies like AI and machine learning to enhance products
• Developing sustainable and socially responsible products
• Creating personalized user experiences at scale
• Exploring new business models and revenue streams

By staying informed about these challenges and opportunities, product managers can position themselves and their organizations for success in an ever-changing landscape.

Conclusion

Mastering the seven knowledge areas of product management is a journey that requires continuous learning, practice, and adaptation. By developing expertise in product innovation management, strategy, portfolio management, process, design and development, market research, and culture and teams, product professionals can enhance their ability to create successful products and drive innovation within their organizations.

As the field of product management continues to evolve, staying informed about industry trends, embracing new technologies, and continuously refining your skills will be crucial for long-term success. Whether you’re just starting your product management career or you’re a seasoned professional, there’s always room for growth and improvement in this dynamic and rewarding field.

By leveraging resources like the PDMA Body of Knowledge, professional certifications, and ongoing learning opportunities, you can build a strong foundation for product mastery and position yourself as a leader in the product management community. Remember, the ultimate goal is not just to create products, but to create products that truly resonate with customers and drive meaningful value for your organization.

Useful links:

• Check out the 2024 Product Development and Management Body of Knowledge by Allan Anderson, Chad McAllister, and Ernie Harris
• Find out how the Rapid Product Mastery Experience, the fastest path to higher-performing product managers and teams, can help your team

Application Questions

1. How do you currently apply the seven knowledge areas for product mastery in your role? Which areas do you feel most confident in, and which do you think need improvement?
2. What strategies have you found most effective for balancing short-term product demands with long-term strategic goals? How do you align your product roadmap with overall business objectives?
3. In what ways has your approach to product management evolved over the course of your career? How have industry trends or technological advancements influenced your practices?
4. How do you foster a culture of innovation within your product team and the broader organization? What challenges have you faced in this area, and how have you addressed them?

Chad’s Bio

Chad McAllister, PhD, is a product management professor, practitioner, trainer, and host of the Product Mastery Now podcast. He has 30+ years of professional experience in product and leadership roles across large and small organizations and dynamic startups, and now devotes his time to teaching and helping others improve. He co-authored “Product Development and Management Body of Knowledge: A Guide Book for Product Innovation Training and Certification.” The book distills five decades of industry research and current practice into actionable wisdom, empowering product professionals to innovate and excel. Chad also teaches the next generation of product leaders through advanced graduate courses at institutions including Boston University and Colorado State University and notably re-engineered the Innovation MBA program at the University of Fredericton, significantly broadening its impact. Further, he provides online training for product managers and leaders to prepare for their next career step — see https://productmasterynow.com/.

Thanks!

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.

How product managers are transforming innovation with AI tools

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TLDR

In this deep dive into AI’s impact on product innovation and management, former PayPal Senior Director of Innovation Mike Todasco shares insights on how AI tools are revolutionizing product development. From enhancing team brainstorming and prototype development to product iteration, AI is becoming an essential tool for product managers. However, Mike emphasizes the importance of balancing AI capabilities with human oversight, warning against over-reliance on AI. The discussion explores practical applications of AI tools like ChatGPT and Claude in product development, including MVP refinement, customer testing, and marketing content creation. Drawing from his experience building PayPal’s Innovation Labs, Mike also shares valuable insights on creating an innovation culture that empowers all employees to contribute to product innovation, regardless of their role.

Key Topics:

• Building Innovation Culture (PayPal Case Study)
• AI as a Brainstorming Partner
• AI Tools in Product Development
• Product Development Acceleration
• AI Implementation Cautions
• Future of AI in Product Development
• Customer Testing and Validation

AI’s Impact on Product Innovation and Management: A New Era for Product Teams

In this episode of Product Mastery Now, I’m interviewing Mike Todasco, former Senior Director of Innovation at PayPal and current visiting fellow at the James Silberrad Brown Center for Artificial Intelligence. Mike brings valuable insights about the revolutionary transformation of product development through artificial intelligence. Through our discussion, Mike shares how this dramatic acceleration in product development processes signals a fundamental shift for product teams. Drawing from his experience leading innovation at PayPal and holding over 100 patents, Mike explains how AI tools are creating new opportunities for innovation, faster iteration cycles, and more comprehensive market understanding while maintaining a balance between artificial intelligence and human insight.

Building Innovation Culture: Lessons from PayPal’s Innovation Lab

In our discussion, Mike shares insights from his experience building PayPal’s Innovation Lab following the company’s separation from eBay in 2015. He explains that their approach to innovation deliberately avoided the common pitfall of creating a two-tiered system where only designated “innovators” were responsible for new ideas.

Creating an Inclusive Innovation Environment

The foundation of PayPal’s innovation success rested on a culture of trust and autonomy. Mike points to their unlimited vacation policy as a symbol of this trust-based culture, where employees were treated as responsible adults capable of managing their time and contributions. This philosophy extended to how employees could engage with the Innovation Lab, allowing them to pursue innovative projects alongside their regular responsibilities.

Traditional Innovation Model PayPal’s Inclusive Approach Designated innovation teams Open to all employees Structured innovation times Flexible engagement Rigid definition of innovation Adaptable interpretation Top-down innovation goals Self-directed innovation

Implementation Strategy

PayPal deliberately kept the definition of innovation flexible. Rather than imposing a strict interpretation, they allowed different roles to define innovation in ways that made sense for their work. Mike encouraged employees to include innovation in their annual goals but never forced this approach.

• Innovation goals were customized to individual roles and responsibilities
• The Innovation Lab served as a gathering space for collaborative work
• Employees had freedom to explore projects in their spare time
• Leadership encouraged but didn’t mandate innovation participation

This approach helped create a culture where innovation wasn’t seen as an additional burden but as an organic part of the workplace. While some areas of the company found this adjustment challenging, PayPal’s long-standing history of innovation made the cultural shift more natural. The success of this approach demonstrates how creating the right environment for innovation can be more effective than mandating it through formal structures.

Leveraging AI in Product Development: A Practical Approach

Mike shares examples of how AI is transforming product development, starting with his own daily interactions with tools like Claude and ChatGPT. His examples demonstrate the versatility of AI in both personal and professional contexts.

AI as Your Development Partner

Through our discussion, Mike explains how AI can serve as a brainstorming partner for product managers. He illustrates this with a recent experience helping an entrepreneur develop a video analysis product. What stands out is their approach to rapid iteration – continuously challenging themselves to simplify their concept, moving from four-week solutions to one-week versions, and ultimately to one-day tests. This methodology helps teams identify the core value proposition quickly.

Choosing the Right AI Tools

When it comes to selecting AI tools for product development, Mike shares several practical approaches to compare different models:

30-Minute Evaluation Method Quick Comparison Method Create test scenarios Open multiple tool windows Test across different AI models Input identical prompts Score responses systematically Compare immediate responses Evaluate reasoning patterns Assess response quality

Available AI Tools for Product Managers

Mike outlines several key AI platforms product managers should consider:

• Claude: Excels at analytical tasks and detailed explanations
• ChatGPT: Strong general-purpose tool with quick responses
• Gemini: Google’s AI with robust integration capabilities
• Copilot: Particularly useful for technical development
• Mistral: Emerging option worth exploring

The key takeaway from our discussion is that AI tools aren’t just about automation – they’re about augmenting human creativity and decision-making in product development. Mike notes that while no single tool is perfect for every task, having multiple AI resources available allows product managers to leverage the right tool for specific needs.

The quality of AI’s work is not as good as human’s work, but its speed is superhuman, and product managers can take advantage of that.

AI Applications Across Product Development Phases

In our discussion, Mike provides valuable insights into how AI can enhance each stage of product development, particularly emphasizing the importance of rapid testing and validation. His perspective on using AI to accelerate the MVP (Minimum Viable Product) process is particularly enlightening. Product managers can use AI to help make their tests simpler.

Early Stage Development with AI

Mike strongly advocates for the 24-hour testing principle – the idea that teams should strive to test core concepts within a single day. He explains that AI tools can help product teams:

• Rapidly refine MVP concepts through multiple iterations
• Generate and evaluate multiple solution approaches quickly
• Test core assumptions before investing significant resources
• Create basic prototypes for initial feedback

Customer Testing and Validation

One of the most innovative approaches Mike shares is using AI for initial customer testing. However, he emphasizes that this should complement, not replace, traditional customer research.

Testing Phase AI Role Human Role Initial Concept Rapid persona-based testing Define customer personas Early Validation Multiple iteration cycles Interpret results Market Testing Automated feedback analysis Customer interviews Launch Preparation Message testing Strategic decisions

Mike suggests an experimental approach to using AI in early customer testing, though he emphasizes this is something he hasn’t fully implemented yet. He explains that product teams could potentially feed customer personas into AI models and run multiple tests to gauge reactions to different product options. For example, if you run the same prompt ten times and the AI selects option A eight times versus option B two times, this might indicate a preference pattern.

However, Mike strongly emphasizes that this approach should never replace actual customer research. He explains that while AI might help teams get their product into a better place before customer testing, it’s important to remember that AI models are trained on internet data, not real customer thoughts and behaviors. As he puts it, “People are weird complex beings,” and AI might not always catch the nuances of real customer behavior.

The key takeaway from Mike’s discussion is that while AI can be a useful tool for early-stage testing and iteration, it should be used to supplement, not replace, traditional customer research methods.

Product Launch and Marketing

Mike shares how AI can significantly enhance product launch activities:

• Generating initial marketing messages for different customer segments
• Testing various positioning approaches
• Creating customized content for different channels
• Analyzing market response patterns

What makes Mike’s approach particularly effective is his emphasis on using AI to accelerate the learning process while maintaining human oversight for strategic decisions. He explains that the goal isn’t to automate the entire development process but to remove bottlenecks and speed up iteration cycles.

Cautions in AI Implementation

Mike provides a word of caution. He introduces the metaphor of “falling asleep at the wheel” – if we over-rely on a driverless car that is not 100% perfect, we could be in trouble. Similarly, we should not over-trust AI in product development. This analogy serves as a reminder of the importance of maintaining human oversight in AI-assisted processes.

Understanding the Risks

Mike shares real-world examples of AI implementation failures, citing incidents at Sports Illustrated and CNET where over-reliance on AI led to publishing errors. He explains that these situations often occur not because the AI tools failed completely, but because human oversight gradually decreased after seeing consistent success.

Risk Area Warning Signs Preventive Measures Customer Understanding Over-reliance on AI-generated personas Regular real customer interactions Decision Making Automatic acceptance of AI suggestions Structured human review process Content Creation Minimal editing of AI outputs Thorough human verification Market Analysis Exclusive use of AI interpretations Cross-reference with human insights

Balancing AI and Human Input

Mike emphasizes several key principles for maintaining effective AI integration:

• AI should not be a replacement for interactions with real customers
• Use AI as a complement to human expertise, not a replacement
• Maintain regular customer contact through traditional research methods
• Implement structured review processes for AI-generated content
• Regularly validate AI insights against real-world data

The most valuable insight Mike shares is that AI tools should enhance rather than replace human judgment. He explains that while AI can process information and generate options at superhuman speeds, the final decisions about product direction should always incorporate human experience and intuition. This balanced approach ensures that teams can benefit from AI’s capabilities while avoiding the pitfalls of over-automation.

The Future of AI in Product Development: Team Collaboration

In our discussion, Mike shares an exciting vision of how AI will transform team collaboration in product development. Drawing from his experience running innovation sessions at PayPal, where teams of 5-25 people would gather in the innovation lab, he explains how AI could enhance these collaborative environments.

AI as a Team Member

Mike describes several ways AI could augment team interactions:

• Acting as a neutral, knowledgeable participant in brainstorming sessions
• Capturing and synthesizing team discussions in real-time
• Providing fresh perspectives when conversations hit a lull
• Helping teams maintain energy and creativity during intensive sessions

Evolution of Workspace Integration

Looking five years ahead, Mike envisions AI becoming seamlessly integrated into everyday work environments:

Current State Future Integration Individual AI interactions AI-enabled conference rooms Manual note-taking Automated meeting synthesis Scheduled brainstorming Continuous AI collaboration Text-based AI interaction Multi-modal AI communication

Emerging Collaboration Patterns

Mike shares how these changes are already beginning to appear. He points to WhatsApp’s integration of AI into group chats as an example of how AI collaboration is evolving. In these environments, AI can:

• Contribute to group discussions when prompted
• Help teams find information or resources quickly
• Assist with scheduling and coordination
• Provide real-time analysis of ideas and suggestions

The key insight Mike emphasizes is that this future isn’t about replacing human collaboration but enhancing it. He explains that AI can help teams overcome common barriers in collaborative work, such as mental fatigue during intensive brainstorming sessions or the challenge of capturing and organizing multiple threads of discussion.

Conclusion

Throughout our discussion, Mike Todasco shares valuable insights about integrating AI tools into product development processes, drawing from his experience at PayPal’s Innovation Lab and his current work in artificial intelligence. His practical approach to using AI as a development partner while maintaining human oversight provides a blueprint for product managers looking to enhance their innovation processes.

The key to success lies in striking the right balance – using AI to accelerate ideation, streamline product development, and enhance team collaboration while maintaining the human judgment essential for product success. As Mike emphasizes, AI tools aren’t replacing product managers; they’re empowering them to work more efficiently and innovatively. For product teams ready to embrace this transformation, the combination of AI-powered product development tools and human creativity opens new horizons for product innovation and market success.

Useful links:

• Connect with Mike on LinkedIn
• Read Mike’s articles on Medium
• Subscribe to Mike’s Newsletter, AI Conversations
• Learn more about the James Silberrad Brown Center for Artificial Intelligence at San Diego State University SDSU

Innovation Quote

“The best way to have a good idea is to have lots of ideas.” – Linus Pauling

Application Questions

1. How could you restructure your current sprint process to incorporate AI tools while maintaining the most valuable human interactions?
2. How could your team use AI to get faster feedback on product concepts while ensuring you’re still capturing genuine customer insights?
3. What safeguards could you put in place to prevent over-reliance on AI while still taking full advantage of its capabilities?
4. How could you integrate AI into your team’s brainstorming sessions in a way that enhances rather than replaces human creativity?
5. How could you balance the speed of AI-powered development with the need for thoughtful product decisions and human oversight?

Bio

Mike Todasco is a former Senior Director of Innovation at PayPal and a current Visiting Fellow at the James Silberrad Brown Center for Artificial Intelligence at SDSU. With over 100 patents to his name, Mike played a key role in fostering a culture of innovation across PayPal’s 20,000+ employees. A recognized expert in AI and innovation, he explores how AI can enhance creativity and revolutionize business processes and personal tasks. Passionate about democratizing advanced technology, Mike advocates for enabling innovation without requiring deep technical expertise. He frequently shares his insights on AI’s impact on innovation, decision-making, and cognition through articles on Medium and LinkedIn. 

Thanks!

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.

How product managers can adapt core responsibilities across different organizations and contexts

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TLDR

Through his research and practical experience at MasterCard, Nishant Parikh identified 19 key activities that define the role of software product managers. He emphasizes that these activities vary based on context (large vs. small organizations, B2B vs. B2C, Agile vs. Waterfall). The discussion reveals how product management has evolved since 1931 and highlights the importance of clear role definition to prevent job frustration. The core focus of these activities is on thorough market research, continuous customer engagement, and strategic product development.

Key Topics:

• Market research as the foundation of product success
• Evolution from problem space to solution identification
  Product positioning and vision development
• Differences between product manager and product owner roles
• Flexible vs. fixed roadmapping approaches
• Continuous customer engagement throughout product lifecycle
• Financial analysis and business case development
• Impact of organizational size on PM responsibilities
• Role of AI tools in modernizing product management
• Importance of cross-functional collaboration

Introduction

In this episode, I’m interviewing Nishant Parikh, Director of Product Management at MasterCard. We explored the 19 essential activities that define successful software product management today.

Drawing from his 20+ years of technology experience and extensive research, Nishant shared insights about how these activities vary across different organizational contexts – from startups to enterprises, B2B to B2C, and Agile to Waterfall environments. He emphasized the importance of role clarity and how the lack of it often leads to frustrated product managers leaving their positions.

In this article, I’ll share the key takeaways from our discussion, including why market research should be your foundation, how customer engagement has evolved to become a continuous process, and the ways AI is reshaping traditional product management activities.

Why study the 19 key activities of software product managers?

Nishant’s motivation came from his personal experience navigating different product management roles over six years. Each position required vastly different responsibilities:

• In his first PM role, he focused on high-level solution development and feature writing
• His next position emphasized go-to-market activities
• At a small MasterCard acquisition company, he had to handle everything from product development to writing stories and epics
• Currently at MasterCard’s foundry team, his focus is on innovation and ideation

This variety of experiences left him confused about the core responsibilities of a product manager. This confusion motivated him to pursue research to better understand:

• What a product manager’s key responsibilities should be
• How the discipline has evolved since its inception in 1931
• Why many PMs leave their jobs due to lack of role clarity
• How to address the overlapping responsibilities between product managers, product leaders, and innovators

He noted that while large organizations might have 100 defined activities for product managers, it’s impossible for one person to handle them all. This led him to research and identify 19 core activities specific to product management, with clear separation from product marketing, sales, and go-to-market functions.

Consolidating insights from different bodies of knowledge

Nishant identified three main bodies of knowledge in product management, each with distinct limitations:

1. PDMA (Product Development and Management Association)
2. ISPMA (International Software Product Management Association) – focused specifically on software industry
3. Product Marketing Body of Knowledge – combines product management and product marketing

The key problem he identified is that none of these bodies of knowledge clearly distinguish between different product management roles or account for various contextual factors that affect how product managers should work, such as:

• Organization size (large vs. small companies)
• Development methodology (Agile vs. Waterfall)
• Product type (AI vs. non-AI products)
• Market focus (B2B vs. B2C)

He emphasized that these contextual factors significantly impact a product manager’s role. For example:

• In large companies, different departments handle specialized functions
• In small companies, one product manager might handle all responsibilities
• The same role can look very different between B2B and B2C products

Nishant’s research aimed to consolidate insights from these different bodies of knowledge and account for various contextual factors to provide a clearer, more comprehensive perspective for product managers and leaders. His goal was to help product managers understand how their role should adapt based on their specific organizational context and product type.

1. Market Research

As software product managers navigate the complex landscape of product development, market research emerges as a crucial first activity. Thorough market research in the problem space is fundamental to product success.

Understanding the Problem Space

The primary goal of market research is to validate whether a real problem exists and if customers truly care about solving it. This validation process requires intensive effort but sets the foundation for all subsequent product development activities. As Nishant emphasizes from his own research experience, investing time in understanding and defining the problem statement pays significant dividends later in the product lifecycle.

Organizational Differences in Market Research

How market research is conducted varies significantly between large and small organizations:

Large Companies:

• Have dedicated research departments
• Access to specialized agencies
• Multiple partnership resources
• Challenge: Information silos between departments
• Need for effective cross-functional communication to share insights

Small Companies:

• Limited budget for research
• Often lack dedicated research resources
• Product managers typically handle research directly
• Despite resource constraints, market research remains crucial for innovation success

The Impact of AI on Market Research

Modern market research has been transformed by artificial intelligence tools:

• Secondary research benefits significantly from tools like Perplexity.AI and ChatGPT
• Primary research, especially customer interviews, still requires direct human involvement
• AI tools complement but don’t replace the need for direct customer interaction

Best Practices for Product Managers

The key takeaway for software product managers is clear: invest heavily in market research regardless of organizational size or resources. A solid understanding of the problem space leads to:

• Better solution development
• Higher likelihood of customer adoption
• Increased chances of customers willing to pay for the solution
• More efficient product development process

2. Solution Identification

After establishing a clear understanding of the market through research, the next critical activity for software product managers is solution identification.

A Straightforward but Critical Process

Solution identification represents the transition from problem space to solution space, involving two key components:

• Developing solution concepts or prototypes
• Validating these potential solutions with customers

What makes this activity unique is its relative simplicity and consistency – regardless of organization size, industry, or methodology, the core process remains largely the same.

The Validation Component

The heart of solution identification lies in customer validation. Product managers must:

• Present potential solutions to customers
• Gather feedback on solution concepts
• Verify that proposed solutions effectively address the validated problem

Unlike other product management activities that vary significantly based on organizational context, solution identification maintains its fundamental approach whether you’re working at a startup or an enterprise company like MasterCard.

Building the Foundation for Product Vision

This activity serves as a bridge between problem validation and product vision development. By identifying and validating solutions before creating a product vision, product managers ensure they’re building on solid ground rather than assumptions.

The straightforward nature of solution identification shouldn’t diminish its importance – it’s a critical step that transforms validated problems into potential products. Its success relies heavily on the thoroughness of the preceding market research phase while setting the stage for subsequent product positioning and vision development.

3. Product Positioning

A Common Pitfall in Vision Development

Nishant highlighted a lesson from his early career: the mistake of creating a product vision before completing market research.

The Correct Sequence

The proper approach to product positioning involves:

1. Understanding the market space
2. Validating the problem
3. Assessing implementation feasibility
4. Developing the product vision

Components of Product Positioning

A well-positioned product should include:

• Clear product vision
• Initial feature set
• Value proposition
• Preliminary go-to-market strategy
• Concise documentation

Documentation and Modern Tools

Product positioning represents the first step in formal product documentation, serving as:

• A foundation for detailed technical breakdowns
• The basis for epics and stories in Agile tools like Jira
• A reference point for future development decisions

Generative AI has become valuable in this phase by:

• Enhancing PR (Product Requirements) documentation
• Suggesting features based on competitive analysis
• Providing narrative structure for product stories

Internal vs External Focus

While primarily focused on internal alignment, product positioning can serve both internal and external purposes:

• Internal: Getting leadership support and aligning teams
• External: Early market validation and customer feedback, similar to Amazon’s “working backwards” approach

This positioning phase creates the foundation for all subsequent product development activities, making it important to get right through proper sequencing and thorough documentation.

4. Product Roadmapping

Once product positioning is established, product managers move into the more action-oriented activity of roadmapping. This planning phase requires careful consideration of multiple contextual factors that significantly impact how roadmaps should be developed and managed.

Agile vs. Waterfall Approaches

The methodology used has a significant impact on roadmap development:

Agile Roadmapping

• Uses flexible roadmaps with varying confidence levels:
  • 3 months: Concrete, high-confidence plans
  • 6 months: Medium confidence projections
  • 9 months: Low confidence forecasting
• Allows for frequent adjustments based on market and customer demands
• Prioritizes adaptability over predictability

Waterfall Roadmapping

• Features more solid, predictable roadmaps
• Offers clearer communication of delivery dates to customers
• Less flexible to change

B2B vs. B2C Considerations

Market focus significantly influences roadmap development and release strategies:

B2B Products

• Less frequent releases
• Focus on core feature delivery
• May conflict with traditional Agile principles of frequent releases
• Emphasis on completing essential functionality before release

B2C Products

• More frequent releases
• Greater focus on user experience improvements
• Regular updates to address UI/UX issues
• Continuous enhancement approach

As Nishant points out from his experience at MasterCard, B2B products often don’t require the same frequency of releases as B2C products. Once core features are delivered and customers are satisfied, there’s less need for constant updates focused on minor UI/UX improvements.

Key Considerations for Product Managers

When developing product roadmaps, product managers should:

• Consider their specific business context (B2B vs. B2C)
• Align roadmap structure with development methodology
• Balance customer needs with development capabilities
• Maintain appropriate levels of flexibility based on market type

Understanding these contextual factors helps product managers create more effective roadmaps that better serve both their organization and their customers.

5. Requirements Engineering

Following roadmap creation, requirements engineering emerges as a crucial activity where product strategy meets technical execution. This phase highlights the important distinction between product manager and product owner roles, particularly in Agile environments.

Historical Evolution of Roles

Nishant provided valuable historical context about how these roles evolved:

• Pre-2001: Only product management existed
• 2001: Agile Manifesto introduced the Product Owner role
• Initial Scrum methodology focused solely on Product Owners
• Later frameworks like SAFe introduced clearer distinction between roles

Role Distinctions

Product Owner

• Specific to Agile methodologies
• Focuses on development team interaction
• Transforms leadership vision into engineering tasks
• Handles detailed story breakdown and sprint planning

Product Manager

• More outbound-focused role
• Works with cross-functional teams
• Handles market-facing responsibilities
• Manages broader product strategy

Organizational Impact

How these roles are implemented varies by organization size:

• Large Companies: Often maintain separate roles for Product Manager and Product Owner
• Small Companies: Usually combine roles into a single position
• Startups: Often rely on founders for product management with dedicated Product Owners

Key Challenges

The separation of roles can create:

• Communication gaps between external and internal focus
• Potential misalignment between strategy and execution
• Need for careful coordination between roles

As requirements engineering continues to evolve, organizations must carefully consider how to structure these roles to maintain effective product development while avoiding communication gaps and ensuring clear accountability.

6. Product Verification

In discussing product verification, Nishant highlighted how this crucial activity has transformed dramatically with the adoption of different development methodologies, particularly in the software industry.

Methodology Differences

Traditional Waterfall Approach

• Relied heavily on User Acceptance Testing (UAT)
• Testing conducted after complete development
• Single verification phase at project end
• Higher risk of late-stage discoveries

Modern Agile Approach

• Eliminates traditional UAT
• Implements continuous validation through sprint demos
• Customer feedback gathered during development
• Story-level validation within each sprint

Industry-Specific Considerations

The approach to product verification varies significantly by industry:

Software Industry

• Moved away from traditional UAT
• Embraces continuous validation
• Allows for rapid iterations
• Enables quick course corrections

Physical Products

• Still largely follows sequential processes
• Cannot easily deliver products in pieces
• Exploring ways to implement Agile principles
• Uses prototyping cycles for validation

Key Benefits of Modern Verification

The evolution to continuous verification offers several advantages:

• Earlier detection of issues
• Reduced risk of major problems late in development
• More frequent customer feedback
• Greater flexibility to make adjustments

As Nishant notes, this transformation in product verification represents a fundamental shift in how products are validated, moving from a single checkpoint to an ongoing process integrated throughout the development lifecycle.

7. Customer Insight

According to Nishant’s research, customer insight represents a fundamental shift in how product managers engage with their users throughout the product lifecycle. This shift moves from periodic customer engagement to continuous involvement at every stage of product development.

Evolution of Customer Engagement

Historically, customer engagement was limited to specific points in the process:

• Early problem validation
• Initial solution validation
• Requirements gathering
• Final product verification

Modern Approach: Continuous Customer Engagement

Today’s best practices involve customers at every stage:

Market Space Phase

• Problem validation
• Market need confirmation
• Initial concept feedback

Solution Space Phase

• Solution validation
• Feature prioritization
• Concept testing

Development Phase

• Value delivery verification
• Ongoing feedback collection
• Feature refinement

Production Phase

• Complete product evaluation
• User satisfaction surveys
• Continuous enhancement feedback

Key Message for Product Managers

Nishant emphasizes one critical point for all product managers: Stay close to customer as much as possible and as early as in the process. This continuous engagement ensures:

• Better alignment with customer needs
• Reduced risk of building unwanted features
• Faster identification of problems
• More successful product outcomes

In the software world particularly, this continuous customer insight loop enables ongoing product enhancement and ensures the product continues to meet evolving customer needs.

8. Financial Analysis

Nishant described financial analysis as one of the more challenging product management activities, with significant variations between different organizational contexts. This activity encompasses business case development, pricing strategies, and ongoing financial validation.

Organizational Differences

Small Companies

• Business cases often handled by founders or CEO
• Limited PM involvement due to confidentiality
• Focus typically on single product financials
• Less formal financial analysis processes

Large Companies

• Major responsibility for product managers
• Second only to cross-functional collaboration in complexity
• Requires coordination across multiple departments
• Complex pricing and costing calculations

Components of Financial Analysis

A comprehensive financial analysis includes:

• Product pricing strategy
• Engineering cost calculations
• Marketing expense projections
• Sales cost estimations
• Complete business case development

Evolution of Business Cases

Business case development is a continuous process that evolves through several stages:

Early Stage

• Total addressable market assessment
• Initial revenue projections
• Preliminary pricing strategy

Development Stage

• Cost identification with development teams
• Refined revenue projections
• Updated business case calculations

Market Testing

• Validation of initial projections
• Adjustment of revenue expectations
• Refinement of business case based on real data

Key Considerations

Product managers should understand that:

• Financial analysis is not a one-time activity
• Business cases require continuous refinement
• Market feedback may significantly impact initial projections
• Success metrics need regular validation and adjustment

As Nishant notes, while initial projections are important, the true test comes when products hit the market, often requiring significant adjustments to the business case based on real-world performance.

Conclusion

Software product management is far more nuanced and context-dependent than many realize. Nishant’s research-backed framework of 19 key activities provides clarity for product managers struggling to define their roles and responsibilities. Whether working in large enterprises or small startups, understanding how these activities adapt to different organizational contexts is necessary for success.

Today’s successful product managers must maintain ongoing dialogues with customers, constantly refine their business cases, and adapt their strategies based on real-world feedback. As the field continues to evolve, those who understand these core activities and how to adapt them to their specific context will be best positioned to create successful products that truly meet customer needs while delivering business value.

Useful links:

• Check out Nishant’s articles on Google Scholar:
  • The Software Product Manager’s Framework
  • The Impact of Generative AI in Software Product Management
  • The Role of AI Product Managers

Innovation Quote

“Innovation is a dynamic process that applies scientific thinking to transform customer problems into valuable business opportunities.”   – Nishant Parikh

Application Questions

1. How could you adapt your market research approach based on your organizational context? Consider the differences between how large and small companies conduct research – if you’re in a large organization, how could you better leverage existing research resources and break down silos? If you’re in a smaller organization with limited resources, how could you conduct meaningful research on a budget?
2. How would you describe the current balance between your product manager and product owner responsibilities? Whether these are separate roles in your organization or combined in your position, what steps could you take to improve the handoff between strategic product management and tactical development work, especially with the assistance of AI tools?
3. Looking at your current customer engagement practices, how could you evolve from periodic touchpoints to more continuous customer involvement throughout your product lifecycle? What specific opportunities exist in your product development process to gather more frequent customer feedback?
4. How could your team improve its approach to business case development and financial analysis? Consider how you currently update financial projections throughout the product lifecycle – what triggers could you establish for reviewing and refining your business case based on new market information or customer feedback?
5. How could you better align your roadmapping approach with your specific business context (B2B vs. B2C)? If you’re currently using an Agile methodology but serving B2B customers, what adjustments could you make to better balance frequent releases with your customers’ needs for stability?

Bio

Nishant A. Parikh is a dynamic professional with a diverse academic background and extensive experience in computer science and product management. Graduating with a Bachelor’s degree in Computer Science from Gujarat University in 2005 and an MBA from Webster University in 2020, Nishant combines technical expertise with business acumen. Currently serving as the Director in Product Management at Mastercard, he drives strategic direction and spearheads the development of innovative software solutions. Passionate about the field, Nishant has immersed himself in research at Capitol Technology University since 2022, exploring the challenges, trends, and solutions in product management. As an avid writer, he shares his insights, addressing the multifaceted issues faced by product managers. Nishant’s visionary leadership, industry knowledge, and commitment to innovation make him a driving force in shaping the future of software product management.

Thanks!

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.

Why product managers need to stop the stupid

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TLDR

Innovation expert Doug Hall reveals why most organizations struggle with innovation despite recognizing its importance. Through his experience running Eureka! Ranch and Dexter Bourbon Distillery, Hall discovered that successful innovation requires a bottom-up transformation focusing first on empowering frontline employees to fix inefficiencies (“stop the stupid”), then enabling middle managers to improve systems, and finally allowing leadership to pursue bigger strategic innovations. This three-level approach has shown to increase innovation value by 28% versus the typical 50% decline seen in traditional top-down approaches.

Key Topics:

• The Innovation Paradox: While 80% of CEOs say innovation is critical, only 20% believe their organizations are good at it
• Employee Innovation Barriers: 37% don’t see innovation as their job, 29% don’t know what to do about it
• Middle Management Challenge: Managers waste 3.5 hours daily dealing with mistakes and system flaws
• System vs. People Problems: 78% of issues come from flawed company systems, only 22% from employee mistakes
• The “Stop the Stupid” Approach: Start with empowering employees to fix immediate inefficiencies before pursuing larger innovations
• Three-Step Framework: 1) Teach innovation fundamentals, 2) Build confidence through early wins, 3) Develop systems thinking
• Measurable Impact: Organizations can achieve 4 improvement actions per employee per month
• Cultural Transformation: Focus on intrinsic motivation rather than external incentives

The Innovation Paradox in Organizations: Why Companies Struggle to Innovate

Doug shared that when you look at any survey of CEOs, more than 80% will say that innovation is crucial for their organization’s future success. However, when asked about their organization’s current innovation capabilities, the numbers flip dramatically – only about 20% believe their organizations are effectively innovating.

Doug illustrated this disconnect with a story from his consulting work. His team had just presented breakthrough solutions to a problem that a CEO had previously deemed impossible. Rather than excitement, the CEO’s response was, “Huh, wow. I guess you did figure it out. Now what do I do? I guess I gotta do it.” The disappointment in the executive’s voice revealed a deeper truth about organizational resistance to innovation.

This resistance manifests in various ways:

• Departments operating in silos resist changes that affect their established processes
• Middle managers hesitate to support innovations that might impact their performance metrics
• Frontline employees don’t see innovation as part of their role
• Existing systems and procedures inadvertently suppress new ideas

Doug explained why simply having good ideas isn’t enough. Successful innovation requires addressing deeper organizational dynamics and systems that either enable or inhibit change. As we explored in our conversation, resolving this paradox requires a fundamental shift in how organizations approach innovation, starting not with grand strategies but with empowering employees to make small, meaningful improvements in their daily work.

Breaking through this paradox requires recognizing that innovation isn’t just about generating new ideas – it’s about transforming how organizations think about and implement change at every level. This understanding forms the foundation for a more effective approach to organizational innovation.

The Problem with Traditional Innovation Approaches: Why Good Ideas Often Fail

Doug shared a startling insight from three separate studies that crystallizes why traditional innovation approaches often fall short. When organizations take an innovative idea into development, its forecasted value typically declines by 50% before launch.

The Innovation Value Loss Problem

A truly disruptive idea will challenge multiple departments in an organization. A genuinely innovative product might require:

• Changes to the supply chain
• Different manufacturing equipment
• New customer service processes
• Alternative sales channels
• Modified operational procedures

When these departmental challenges arise, organizations typically respond by compromising the original idea. As Doug put it, “It’s like you’re managing the death of ideas.” Each department makes small compromises to fit within existing systems until the final product barely resembles the original innovative concept.

The Hidden Organizational Barriers

Through our discussion, Doug revealed how organizational silos create powerful resistance to innovation:

Performance Metrics Conflict

Manufacturing departments hesitate to support innovations that might lower their productivity metrics.

Departmental Isolation

In many corporations, departments operate as separate units where promotion and income depend on making their individual department heads happy, not on supporting cross-functional innovation.

System Constraints

Standard Operating Procedures (SOPs) and existing systems often can’t accommodate truly innovative ideas without significant modification.

The Traditional Approach Trap

Most organizations try to overcome these barriers through:

• Special innovation teams
• Suggestion boxes
• Innovation training programs

However, Doug found these approaches usually fail because they don’t address the underlying system issues. Traditional innovation approaches weren’t working because they ignored a fundamental truth: most employees face daily operational challenges that make innovation feel like an extra burden rather than an opportunity.

A New Framework: Starting with Employee Engagement

Understanding the Real Barriers to Innovation

The data Doug shared revealed two primary barriers preventing employee participation in innovation:

• 37% of employees don’t see innovation as part of their job
• 29% don’t know what to do even if they wanted to innovate

These statistics point to a clear problem: organizations aren’t making innovation accessible and actionable for their employees.

The “Stop the Stupid” Revolution

This insight led to a radical shift in approach. Instead of pushing employees to create breakthrough innovations, Doug’s team started by addressing the daily frustrations and inefficiencies that drain employee energy and enthusiasm.

For example, at his distillery, while Doug was excited about developing new custom bourbon experiences, his employees were more concerned about immediate challenges like:

• Back pain from lifting heavy crates
• Inefficient paperwork processes
• Workflow bottlenecks
• Equipment issues

Building Momentum Through Small Wins

The power of this approach became clear as employees started solving these immediate problems. By focusing on improvements within their sphere of influence, employees:

• Gained confidence in their problem-solving abilities
• Developed practical innovation skills
• Experienced intrinsic satisfaction from making meaningful improvements
• Built collaborative relationships across departments

From Frustration to Innovation

This employee-first approach transforms how organizations think about innovation. Rather than treating innovation as a special initiative, it becomes part of everyone’s daily work. The results speak for themselves – organizations implementing this approach see an average of four improvement actions per employee per month.

More importantly, this foundation of employee engagement creates an environment where larger innovations can thrive. When employees feel empowered to solve problems and improve systems, they become natural allies in implementing bigger strategic changes.

The Three-Level Organizational Transformation: Creating a Culture of Innovation

Through his work at Eureka! Ranch and his own experiences running a bourbon distillery, Doug has developed a practical framework for transforming how each level contributes to innovation.

Level 1: Frontline Employees

The transformation begins at the front lines, where employees are closest to daily operations. Instead of imposing top-down innovation mandates, organizations need to:

• Provide basic innovation and problem-solving tools
• Set clear boundaries for decision-making authority
• Support immediate improvements within teams
• Celebrate small wins that eliminate inefficiencies

Level 2: Middle Managers

One of the most striking statistics Doug shared was that middle managers waste an average of 3.5 hours daily dealing with problems. Breaking this down:

• 78% of issues stem from flawed company systems
• 22% come from employee mistakes
• Most time is spent on reactive problem-solving

The solution involves transforming middle managers from reactive problem-solvers into system improvers. This means:

• Teaching managers to identify system-level issues
• Empowering them to implement systemic solutions
• Shifting focus from blame to improvement
• Creating clear protocols for change implementation

Level 3: Leadership

At the leadership level, the transformation focuses on enabling rather than directing innovation. Leaders need to:

• Set appropriate vision and strategy
• Avoid compromising innovation goals to fit current capabilities
• Support system-wide improvements
• Remove organizational barriers to change

The Power of Alignment

When these three levels work together, organizations can achieve remarkable results. For example, one B2B company Doug worked with saw their marketing department transform from one of the lowest-rated departments to generating 100 times more leads within three months of implementing this approach.

The key is understanding that each level plays a distinct but interconnected role in innovation:

• Frontline employees drive immediate improvements
• Middle managers enable system-level changes
• Leaders create the environment for transformation

This three-level alignment creates a foundation for sustainable innovation, where improvements build upon each other rather than getting stuck in organizational resistance.

Implementation Framework: Making Innovation Work at Every Level

After decades of helping companies innovate and running his own bourbon distillery, Doug has distilled his process down to fundamental steps that any organization can follow.

Step 1: Teach Innovation Fundamentals

The first step focuses on giving everyone the basic tools they need to innovate. Doug has simplified complex innovation principles into accessible tools. This includes:

• Basic problem-solving techniques
• Simple formats for communicating ideas
• Clear methods for identifying system issues
• Frameworks for evaluating potential improvements

Step 2: Build Confidence Through Early Wins

The second step involves what Doug calls the “stop the stupid” phase. Organizations should:

• Focus first on obvious inefficiencies
• Address longstanding employee frustrations
• Create visible improvements quickly
• Celebrate small victories

For example, at Doug’s distillery, they transformed a painful box-lifting process by simply redesigning how boxes were assembled around products rather than lifting products into pre-made boxes.

Step 3: Develop Systems Thinking

The final step moves from individual improvements to systematic change. This involves:

Making Systems Visible

• Identify key organizational systems
• Map process flows and dependencies
• Understand cross-departmental impacts

Focusing on Key Metrics

• Choose single, clear metrics for each system
• Avoid conflicting performance measures
• Track improvement impacts systematically

Understanding Error Types

• Distinguish between system errors (94%) and worker errors (6%)
• Focus on fixing processes rather than blaming individuals
• Address root causes rather than symptoms

Creating Sustainable Change

What makes this framework powerful is its focus on building internal capability rather than relying on external consultants or temporary initiatives. Organizations implementing this approach can expect:

• Four improvement actions per employee per month
• 28% increase in innovation value (versus traditional 50% decline)
• Higher employee engagement and satisfaction
• Sustained innovation capability

Results and Impact: Measuring Innovation Success

Doug described the tangible results organizations achieve when they transform their approach to innovation. The metrics he shared demonstrate why this bottom-up, system-focused approach delivers dramatically different outcomes from traditional innovation methods.

Measurable Transformation

The contrast in results is striking:

Metric Traditional Approach New Framework Innovation Value 50% decline during development 28% increase in value Employee Engagement Limited participation 4 improvements per person monthly Implementation Success Ideas compromised to fit systems Systems improved to support ideas

Real-World Success Stories

The impact extends across various types of organizations:

• A B2B company’s marketing department increased lead generation 100x in three months
• Manufacturing teams eliminated chronic efficiency problems
• Service organizations dramatically improved customer satisfaction
• Doug’s own distillery became one of the fastest-growing and most innovative in the industry

Cultural Transformation

Beyond the numbers, organizations experience fundamental shifts in how they operate:

• Employees become naturally proactive in solving problems
• Managers spend less time fighting fires
• Departments collaborate more effectively
• Innovation becomes part of daily work rather than a special initiative

Long-Term Benefits

Organizations implementing this approach see sustained improvements in:

• Employee retention and satisfaction
• Operational efficiency
• Innovation implementation success
• Cross-functional collaboration
• Strategic capability

Getting Started

This transformation doesn’t require massive resources or restructuring. Instead, it starts with simple steps:

• Empower employees to solve problems within their sphere
• Give managers tools to improve systems
• Create clear boundaries for decision-making
• Focus first on eliminating obvious inefficiencies

The key is starting with small, achievable improvements that build confidence and capability for bigger innovations. As organizations prove they can successfully implement positive changes, they create momentum for larger transformations.

Conclusion

Transforming organizational innovation isn’t about generating more ideas or launching special initiatives. It’s about creating an environment where positive change can happen naturally at every level. By starting with employee-driven improvements, building middle management capabilities, and enabling leadership to pursue bigger strategic innovations, organizations can break free from the traditional innovation paradox where great ideas lose value during implementation.

The path forward is clear: empower employees to “stop the stupid” in their daily work, give managers tools to improve systems rather than just fight fires, and allow leaders to set ambitious goals without compromising them to fit current capabilities. When organizations align these three levels and follow a systematic implementation framework, they can achieve the holy grail of innovation – sustained, positive change that builds value rather than eroding it. The result isn’t just better products and services, but a more engaged workforce and a more adaptable organization ready to tackle future challenges.

Useful links:

• Check out Doug’s book, Proactive Problem Solving on Amazon or at an independent bookseller near you
• Learn more about Eureka! Ranch
• Learn more about Dexter Bourbon
• Learn more about PDMA

Innovation Quote

“Stop the Stupid.”  – Doug Hall

Application Questions

1. How could you adapt the “stop the stupid” approach to your product development process? Consider what daily inefficiencies or frustrations your team encounters that, if eliminated, would free up energy and enthusiasm for innovation.
2. How could your team reframe its innovation strategy to focus on building confidence through small wins before tackling larger transformational projects? What would be the equivalent of “fixing the broken box” in your product organization?
3. When you think about your last few product innovations that lost value or momentum during development, how much of that decline was due to system constraints versus individual mistakes? How could you start addressing those systemic barriers?
4. How could you empower your product team members to identify and solve problems within their sphere of influence? What boundaries and decision-making frameworks would you need to put in place to make this successful?
5. How could you apply the concept of “common cause vs. special cause” errors to your product development process? Consider where your team might be blaming individuals for what are actually system-level problems.

Bio

Doug Hall is on a relentless, never-ever ending quest to enable everyone to think smarter, faster and more creatively.  His learning laboratories over the past 50+ years have included 10 years at Procter & Gamble where he rose to the rank of Master Inventor shipping a record 9 innovations in a 9 months and 40+ years as an entrepreneur including as founder of the Eureka! Ranch in Cincinnati Ohio – where he and his team have invented and quantified over 20,000 innovations for organizations such as Nike, Walt Disney, USA Department of Commerce, American Express and hundreds more.  Doug’s newest book,  out in December, PROACTIVE Problem Solving, was inspired by his experiences founding and leading a fast-growing manufacturing company, the Brain Brew Bourbon Distillery. Despite the COVID pandemic, Brain Brew grew from shipping a few thousand cases to shipping over 100,000 cases a year by enabling employee engagement. 

Thanks!

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.

A custom ChatGPT model that helps accelerate product innovation

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TLDR

In this episode, I interview Mike Hyzy, Senior Principal Consultant at Daugherty Business Solutions. He explains how to conduct an AI-powered design sprint that transforms product concepts into clickable prototypes in just hours instead of weeks. Using a custom ChatGPT model combined with collaborative team workshops, product teams can rapidly move from initial customer insights to validated prototypes while incorporating strategic foresight and market analysis.

Key Topics:

• Strategic foresight approach to product development, focusing on customer needs 2-5 years ahead
• Triple diamond decision framework for analyzing problems, customers, and markets
• Integration of team collaboration, AI assistance, and external validation
• Rapid wireframe and UI design generation using ChatGPT and DALL-E
• Creation of interactive prototypes using CodePen for immediate testing
• Custom AI model prompts and best practices for design sprint facilitation
• Early go-to-market strategy integration in the product development process
• Practical implementation of AI tools to accelerate product innovation

Introduction

Imagine taking a product concept from initial customer insight to clickable prototype in just a few hours. That’s exactly what I witnessed at PDMA’s recent Inspire Innovation Conference, where Mike Hyzy demonstrated a groundbreaking approach to AI Design Sprints that’s revolutionizing product development acceleration.

By combining strategic foresight, a custom ChatGPT model, and collaborative workshop techniques, Mike led how six teams to achieve what typically takes weeks of work in just under three hours. As a product management professor and practitioner, I’ve seen many methodologies for speeding up innovation, but this approach was different – transforming ChatGPT into a virtual team member that accelerates every phase of the development process, from initial concept through digital product prototyping, while ensuring teams focus on solving tomorrow’s customer needs rather than just today’s problems.

In this episode, Mike will take us through the steps he led product teams through during his AI Design Sprint workshop.

The Critical Role of Strategic Foresight in Product Innovation

At the beginning of the workshop, Mike explained the importance of strategic foresight. He emphasized a fundamental shift in how we should approach product development. Instead of focusing solely on today’s customer problems, product teams need to look 2-5 years into the future. This strategic foresight approach to product development isn’t just about making predictions – it’s about understanding how customer needs and market conditions will evolve over time.

Mike shared a sobering statistic that highlights why this forward-thinking approach matters: 42% of companies cite “no market need” as their main reason for failure. This happens when teams solve today’s problems without considering how those needs might change by the time their product actually launches. As I’ve seen in my own product management experience, the traditional product development cycle can take months or even years. By the time we launch, the market may have moved on from the problem we originally set out to solve.

The Triple Diamond Framework Components

To address this challenge, Mike introduced the Triple Diamond Decision Framework, a structured approach that helps teams look ahead while making concrete decisions. Here’s how the framework breaks down:

1. Jobs to be Done Diamond
   • Explore future customer problems and needs
   • Identify emerging pain points
   • Converge on the most critical future needs
2. Customer Analysis Diamond
   • Map potential future customer segments
   • Analyze evolving customer behaviors
   • Focus on the most promising future customers
3. Market Analysis Diamond
   • Investigate market trends and opportunities
   • Evaluate potential market sizes
   • Select the most viable future markets

What makes this framework particularly powerful in an AI design sprint is how quickly teams can move through each diamond. Mike explains that traditional market analysis might take weeks of research, but with AI assistance, teams can gather initial market insights, including total addressable market (TAM) and serviceable market data, in minutes rather than weeks.

The key to success with this approach lies in the balance between divergent and convergent thinking at each stage. Teams start by thinking broadly about all possible needs, customers, or markets, then use data and insights to narrow down to the most promising opportunities. Mike emphasizes that this isn’t about rushing through the process – it’s about using AI tools to accelerate the research and analysis phases so teams can spend more time on creative problem-solving and validation.

This strategic foresight foundation sets the stage for the entire AI design sprint process. By starting with a future-focused mindset and using AI to accelerate market research, teams can avoid the common trap of building products for yesterday’s problems while ensuring they’re creating solutions that will still be relevant when they reach the market.

Three Key Elements That Power AI-Powered Design Sprints

In this episode, Mike outlines how the success of an AI design sprint relies on the synergy between three core elements. Rather than simply replacing traditional methods with AI tools, this approach creates a powerful combination of human creativity, artificial intelligence, and real-world validation.

1. Team Collaboration

The foundation of every successful AI design sprint starts with effective team collaboration. As I observe during the workshop, the magic happens when small groups work together to explore ideas and challenge assumptions. Mike explains that having multiple perspectives around the table leads to insights that neither AI nor individual team members would discover alone.

For example, during our workshop session, when one team member mentioned the need for pricing tiers in their product concept, it triggered a deeper discussion about what would motivate users to upgrade from a free version to a paid tier. This kind of nuanced thinking emerges naturally from team interactions.

2. AI Tool Integration

The integration of AI tools, particularly through Mike’s custom ChatGPT model, serves as a catalyst for rapid product development. Here’s how AI enhances the process:

• Accelerates market research and data gathering
• Identifies potential blind spots in thinking
• Suggests alternative approaches and solutions
• Generates rapid prototypes and iterations
• Provides structured frameworks for decision-making

What makes this element particularly powerful is how the AI tool becomes like another team member, offering insights and suggestions while the human team maintains control over creative decisions and strategic direction.

3. External Validation

The third critical element involves getting feedback from outside the immediate team. During the workshop, Mike structures this through team-to-team interactions, where each group presents their concepts to another team for feedback. In a real-world setting, this would involve:

Validation Level Purpose Timing Initial Feedback Quick reality check on concepts Early in the sprint Feature Validation Confirm priority features Mid-sprint Prototype Testing User experience validation Late sprint

What makes this three-element approach particularly effective is how each component complements the others. The team’s creative energy feeds into the AI tool’s capabilities, while external validation helps refine and improve the outputs from both human and AI contributions.

Mike emphasizes that the real power comes from the rapid iteration possible when these three elements work together. Teams can quickly move from initial concept to validated prototype, with each element providing different types of input and validation along the way. This combination helps ensure that the final product concept isn’t just technically feasible but also genuinely meets market needs.

Breaking Down the AI Design Sprint Process

In this episode, Mike walks us through the step-by-step process of conducting an AI-powered design sprint. In his workshop, teams used Mike’s custom ChatGPT model, AI Design Sprint. What’s particularly impressive is how this approach compresses what traditionally takes weeks into just a few hours, while still maintaining the rigor needed for effective product development.

Discovery Phase

The discovery phase sets the foundation for the entire sprint. Mike structures this phase into distinct segments, each building on the previous one:

1. Initial Idea Generation

The first prompt for ChatGPT tells it that you’re going to use the triple diamond decision framing to explore needs, customers, and markets. You’ll work through it one stage at a time, starting with the discovery stage. It directs ChatGPT to read your input and ask corresponding questions. You’ll finish one section before moving on to the next one.

The AI tool supports this process by:

• Providing prompting questions to spark discussion
• Suggesting potential angles teams might have missed
• Organizing ideas into structured formats
• Documenting key insights for later reference

During the workshop, my team worked on the question, How do I use the space I have in my yard to create a garden? During the Discovery phase, once we told ChatGPT our initial ideas, its asked us the questions:

• Who would benefit from this product?
• What are their needs?

We typed our answers into ChatGPT, which used them to build a customer persona.

2. Needs Analysis

Once initial ideas are captured, teams dive deeper into understanding customer needs. The AI assistant helps accelerate this process by:

Analysis Type AI Support Team Input Customer Pain Points Market research synthesis Real-world experience validation Unmet Needs Pattern recognition Context and nuance addition Future Needs Trend analysis Industry expertise application

Definition Phase

Moving into definition, teams begin to shape their solution. Mike shows how the AI tool helps teams:

Synthesize Key Insights

• Compile user insights from discovery
• Identify core opportunities
• Define essential functionality

Prioritize Features

• Create MVP feature sets
• Identify secondary features
• Tag nice-to-have additions

Development Phase

The development phase is where the AI-powered approach really shines. Mike demonstrates how teams can rapidly move through:

1. Wireframing

Using the AI tool’s connection to DALL-E, teams can generate wireframes for each feature. What’s remarkable is how quickly teams can iterate on these designs. Mike shows us how to:

• Generate individual screens for each feature
• Refine layouts based on team feedback
• Maintain consistency across the interface

2. UI Design

The sprint moves from wireframes to more detailed UI designs. Teams can specify:

• Color schemes (like “Earth tones similar to Whole Foods”)
• Design patterns (such as Google’s Material Design)
• Typography and spacing preferences

3. Interactive Prototype

The final step involves creating a clickable prototype using:

• HTML generated by the AI tool
• CSS for styling
• JavaScript for interactivity

Mike shows how teams can use CodePen as a free platform to bring these elements together into a working prototype. This allows for immediate testing and validation of the user experience.

What makes this process particularly valuable is its flexibility. While Mike guides us through all these steps, he emphasizes that teams can adjust the focus based on their specific needs. Some teams might spend more time in discovery, while others might need to iterate more on the prototype phase.

Best Practices for Implementing AI Design Sprints

Drawing from his experience leading multiple AI-powered design sprints, Mike shares key tips and strategies to help teams maximize the value of this approach. These implementation guidelines ensure teams can effectively combine human creativity with AI capabilities while maintaining focus on creating valuable products.

AI Interaction Best Practices

Mike emphasizes the importance of structuring your interaction with AI tools effectively. Here’s how to get the best results:

Practice Purpose Example One Stage at a Time Maintain focus and clarity Complete market analysis before moving to features Clear, Specific Prompts Get targeted responses “Create separate wireframes for each feature” Regular Progress Saving Preserve work across sessions Save summaries after each major phase

Prototype Development Guidelines

When it comes to creating prototypes, Mike shares several key strategies:

Wireframe Creation

• Request separate screens for each feature
• Be specific about design preferences
• Iterate based on team feedback

Code Structure

• Keep HTML, CSS, and JavaScript organized
• Use CodePen for quick testing
• Maintain consistent naming conventions

Feedback Integration

• Capture team input immediately
• Make rapid adjustments
• Test changes in real-time

Go-to-Market Integration

One of Mike’s most valuable insights is the importance of thinking about go-to-market strategy early in the process. He recommends:

• Developing marketing messages during the sprint
• Creating 30-second elevator pitches
• Testing value propositions with other teams
• Planning launch strategies alongside development

Time Management Tips

To keep the sprint moving efficiently, Mike suggests:

• Use 10-minute focused sessions for each activity
• Set clear objectives for each sprint segment
• Build in quick breaks between major phases
• Allow flexibility for deeper exploration when needed

Common Pitfalls to Avoid

Through his experience, Mike has identified several challenges teams should watch out for:

• Getting stuck in endless iterations without moving forward
• Relying too heavily on AI without human insight
• Skipping validation steps to save time
• Forgetting to save progress between sessions

What I find particularly valuable about Mike’s approach is how he balances efficiency with effectiveness. While the AI-powered sprint can move quickly, he ensures teams don’t sacrifice quality for speed. He emphasizes that the goal isn’t just to create a prototype faster – it’s to create a better product by allowing teams to explore more options and gather more feedback in less time.

Making AI Design Sprints Work: Key Success Factors

In this episode, Mike shares the critical elements that determine the success of an AI-powered design sprint. As I observe during the workshop, these factors make the difference between simply using AI tools and truly transforming the product development process.

Team Dynamics

The human element remains crucial even in AI-powered sprints. Mike identifies several key team factors:

Factor Impact Implementation Balanced Input Ensures diverse perspectives Mix of technical and business roles Cross-functional Expertise Enriches solution development Include design, tech, and product skills Collaborative Spirit Drives rapid iteration Encourage building on others’ ideas

Strategic Foresight Integration

Mike emphasizes that successful teams consistently maintain a future focus throughout the sprint:

Market Evolution

• Consider technological trends
• Anticipate changing customer needs
• Factor in competitive landscape shifts

Solution Longevity

• Design for future scalability
• Plan for evolving user expectations
• Build in adaptation capabilities

Validation Approach

Effective validation proves crucial for sprint success. Mike recommends:

• Test concepts with other teams during the sprint
• Use AI insights to challenge assumptions
• Maintain a balance between human feedback and AI analysis
• Document validation findings for future reference

Tool Mastery

Understanding how to effectively use AI tools makes a significant difference. Mike shares these best practices:

• Start with simple prompts and build complexity
• Save successful prompts for future use
• Learn from how the AI responds to different input styles
• Maintain a library of effective prompt patterns

Outcome Focus

Successful teams keep their eyes on meaningful outcomes:

Outcome Type Success Indicator Product Concept Clear value proposition validated by feedback Market Fit Identified target market with validated need Technical Feasibility Realistic implementation path defined Business Viability Compelling business case established

What makes these success factors particularly powerful is their interconnected nature. Mike demonstrates how each element supports the others, creating a robust framework for innovation. The combination of human creativity, AI capabilities, and structured validation helps teams not just move faster, but also make better decisions throughout the product development process.

Real Results: Workshop Outcomes and Next Steps

In this episode, Mike shares the impressive results from the PDMA workshop, demonstrating how AI-powered design sprints can transform product development. The outcomes show both the immediate value and long-term potential of this approach.

Workshop Achievements

The teams in the workshop accomplished several key deliverables in under three hours:

Deliverable Traditional Timeline Sprint Timeline Market Analysis 2-3 weeks 15-20 minutes Feature Definition 1-2 weeks 30 minutes UI Design 1-2 weeks 45 minutes Interactive Prototype 1-3 weeks 60 minutes

Practical Applications

Mike explains how teams can apply this methodology in different contexts:

Startup Environment

• Rapid concept validation
• Quick pivot capability
• Efficient resource use

Enterprise Setting

• Innovation acceleration
• Cross-team collaboration
• Risk reduction through rapid testing

Product Enhancement

• Feature validation
• User experience improvement
• Competitive response

Next Steps for Implementation

For teams looking to implement AI-powered design sprints, Mike recommends:

• Start with a small, focused project to build team confidence
• Use the provided custom ChatGPT model as a starting point
• Document and adapt the process for your organization’s needs
• Build a library of successful prompts and approaches

Long-term Benefits

Beyond the immediate sprint outcomes, Mike highlights several lasting advantages:

• Improved team collaboration patterns
• Enhanced decision-making processes
• Better integration of strategic foresight
• More efficient resource utilization
• Faster time to market for new products

Future Possibilities

Looking ahead, Mike sees several exciting possibilities:

• Integration with more sophisticated AI tools
• Enhanced prototype generation capabilities
• Improved market analysis accuracy
• More automated validation processes

What makes these outcomes particularly compelling is their practical nature. As I observe during the workshop, teams aren’t just creating theoretical concepts – they’re developing viable product solutions that could move directly into development. The combination of speed and quality demonstrates why AI-powered design sprints represent a significant evolution in product development methodology.

Mike emphasizes that while the technology is impressive, the real value comes from how it enables teams to spend more time on creative problem-solving and less time on routine tasks. This shift in focus helps ensure that the increased speed of development doesn’t come at the expense of innovation or product quality.

Conclusion

As this episode demonstrates, AI-powered design sprints represent a significant leap forward in product development methodology. Mike’s approach successfully combines the creative power of human teams with the efficiency of AI tools, enabling product managers to compress weeks of work into focused sessions while maintaining high-quality outcomes. The custom ChatGPT model he’s created, coupled with structured team activities and validation steps, provides a practical framework that any product team can implement.

What makes this methodology particularly valuable is its focus on future needs and market evolution. Rather than simply accelerating existing processes, these AI-powered design sprints help teams create better products by enabling rapid iteration, comprehensive market analysis, and meaningful validation. As Mike shows us, the future of product development isn’t just about working faster – it’s about working smarter by leveraging AI to enhance human creativity and strategic thinking.

Useful links:

• Check out Mike’s Custom AI Model for the AI Design Sprint
• Connect with Mike on LinkedIn
• Check out Mike’s website
• Check out Mike’s Substack
• Check out Mike’s book, Gamification for Product Excellence
• Learn more about PDMA

Innovation Quote

“Product innovation is about having the foresight, which is not about creating solutions for problems that we know exist today, but about anticipating challenges and opportunities that might emerge in the future.” – Mike Hyzy

Application Questions

1. How could your team integrate strategic foresight into your current product development process? Consider which aspects of your market and customer needs are most likely to evolve in the next 2-5 years.
2. How could you use AI tools to accelerate the parts of your product development process that currently take the most time? Think about areas like market research, competitive analysis, or prototype creation.
3. Looking at your most recent product development initiative, how could the triple diamond framework have helped you better validate the market need before investing in development?
4. How could your team structure a compressed design sprint using these AI-powered techniques while still ensuring you get meaningful validation from actual customers or stakeholders?

Bio

Mike Hyzy is a senior principal consultant at Daugherty Business Solutions.  He advises executive teams on AI, innovation and strategic product management, combining data-driven insights with cutting-edge technology to drive transformational change. Previously he has been a product management consultant and has held senior product management roles. 

Thanks!

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.

How product managers can move from ideas to action

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TLDR

In this episode, I speak with Atif Rafiq about how senior product leaders approach strategy development and execution. Atif brings valuable insights from a recent PDMA executive workshop where leaders discussed their real-world challenges with strategic decision making and innovation strategy.

Key topics from our discussion:

• Main challenges product leaders face when developing strategy
• A practical framework for exploring product opportunities
• How AI tools can help with strategic decision making
• The importance of early-stage product work
• Ways to improve alignment across organizations
• Real-world example using a subscription service concept

Introduction

In this episode, I’m interviewing Atif Rafiq, who recently led an executive workshop at the PDMA conference, where senior leaders discussed challenges they face, including navigating ambiguity and making decisions with more clarity. In this episode, he shares some insights from that workshop and his experience in product leadership. Atif has spent 25 years working in both Silicon Valley and Fortune 500 companies, including leadership roles at Amazon, McDonald’s (as their first Chief Digital Officer), Volvo, and MGM Resorts. He has developed a systematic approach to problem-solving that forms the basis of his book, Decision Sprint: The New Way to Innovate into the Unknown.

Key Challenges in Strategic Product Leadership

During our discussion, Atif identifies three main challenges that senior leaders face when developing and implementing product strategy:

1. Alignment Challenges

Organizations often struggle to get everyone moving in the same direction:

Challenge Area Impact Common Problem Problem Understanding Teams interpret issues differently Resources going to wrong priorities Stakeholder Views Departments focus on different goals Competing objectives and metrics Customer Focus Too much focus on one perspective Missing business or operational needs

2. Input and Collaboration Issues

Atif explains that product leaders often struggle to gather useful input and work effectively across teams. Common problems include:

• Meetings that don’t collect all needed information
• Difficulty managing different department viewpoints
• Challenges combining input from multiple sources
• Time pressures that cut short important discussions

3. Experimentation Challenges

While many organizations value testing ideas, Atif notes several common issues:

• Starting experiments before understanding the problem
• Running tests without clear goals
• Weak links between test results and business strategy
• Racing through testing without proper planning

Purposeful Exploration: A Better Approach

In our discussion, Atif introduces “purposeful exploration” – a structured way to investigate and test product opportunities. This method helps organizations find balance between rushing into solutions and getting stuck in endless discussions.

Key Elements of Purposeful Exploration

Element Purpose Activities Problem Definition Get clear about the challenge Talk to stakeholders, analyze data, study market Question List Identify what we need to learn Team workshops, AI-assisted research Testing Strategy Check our assumptions Small pilots, focused tests, data gathering Making Sense of Results Draw useful conclusions Analysis, recommendations, team alignment

Real-World Example: Coffee Subscription Service

During the workshop, Atif walked the senior leaders through an exercise to get buy-in for a coffee subscription service at McDonald’s. Three different groups crafted a problem statement related to this idea and then identified key questions they needed to answer. This example demonstrates how to balance different business needs when exploring a new product idea.

Strategic Questions to Consider

The teams identified key questions, including:

Business Area Key Questions What to Explore Revenue Impact Will subscribers visit more often and buy food? Visit patterns, additional purchases Operations Can stores handle increased coffee orders? Service speed, staff needs Customer Value How does this work with loyalty programs? Digital integration, easy redemption Business Model What makes this profitable? Pricing levels, program guidelines

Next, each group shared their questions with the others, and they used AI to compare the breadth and depth of the questions.

Key Insights from the Example

• Success depends on getting customers to visit more and buy additional items
• Testing needs to happen in stages to manage operational complexity
• Digital platform integration affects customer adoption
• Program rules must work for both customers and the business
• Workshop participants found they could work much faster when combining team expertise with AI capabilities

Upstream Product Work

Atif emphasizes the importance of early work—the foundation-setting activities before product development starts. He notes that this phase often determines success or failure.

Essential Early Activities

Activity Purpose Result Problem Definition Get clear about the challenge Shared understanding Question List Identify unknowns Focus areas Team Alignment Build agreement Clear direction Resource Planning Ensure enough support Available resources

Ritual: An AI Tool to Support Strategic Decision-Making

During our discussion, Atif introduces Ritual, a tool he and his team developed to support strategic decision-making processes. Ritual combines workflow management with AI capabilities to help teams move from initial ideas to solid recommendations. The tool reflects Atif’s experience leading organizations through strategic decisions, incorporating features that support building and running explorations, gathering team input, and producing strategy documents.

Workshop participants using Ritual noticed significant improvements in their exploration process, with AI assistance helping teams work up to ten times faster while maintaining quality. The tool helps teams develop strategy memos and recommendation documents that include context, problem statements, goals and constraints, key issues, analysis insights, and final recommendations. While Atif emphasizes that good strategic thinking remains fundamental, tools like Ritual can help teams work more efficiently and maintain consistency in their strategic exploration process.

Putting It Into Practice

Atif recommends these steps for using these ideas:

1. Define Problems Well

• Write down the challenge clearly
• Get team agreement on the problem
• Choose how to measure success

2. Plan Your Exploration

• List key questions
• Design useful tests
• Set clear deadlines

3. Use Tools Wisely

• Add AI where it helps
• Keep human oversight
• Record what you learn

4. Build Team Skills

• Train people in new methods
• Create clear processes
• Set up ways to learn and improve

Conclusion

Throughout our conversation, Atif emphasizes that product strategy works best when teams balance thorough analysis with timely action. The methods and frameworks we discussed can help product leaders work through strategic challenges more effectively.

Remember that improving how you make strategic decisions takes time and practice. Start with small changes, see what works, and adjust your approach based on results.

Useful links:

• Check out Atif’s book, Decision Sprint
• Check out Ritual, an AI tool for Purposeful Exploration
• Connect with Atif on LinkedIn and sign up for his Rewire newsletter
• Learn more about the Product Development and Management Association (PDMA)

Innovation Quote

“There are one-way doors and two-way doors.” – Jeff Bezos

Application Questions

1. How could your team spend more time understanding problems before jumping to solutions? What process changes would this require?
2. What steps could your team take to balance customer needs with business requirements when exploring new opportunities?
3. How might your team use AI tools to speed up the early stages of product development while maintaining quality?
4. What changes would help your organization align different departments when exploring new opportunities?

Bio

Atif Rafiq invented a system for problem-solving based on his 25-year career spanning Silicon Valley and the Fortune 500. His ideas proved so impactful as a competitive advantage that they sped his rise at Amazon and later to C-suite positions he held at companies, including McDonald’s as their first Chief Digital Officer, and at Volvo and MGM Resorts.

He wrote DECISION SPRINT: The New Way to Innovate into the Unknown and Move from Strategy to Action based on what he learned leading organizations from a product perspective.

 

Thanks!

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.

A framework for product launch success

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TLDR

In this episode of Product Mastery Now, I interview James Whitman, author of LAUNCH Code and founder of Growth Guidepost. James shares insights from his research studying companies that consistently launch successful products. His LAUNCH Code framework offers a practical approach to product launch management that any organization can implement.

Key Topics Covered:

• The LAUNCH Code: six essential components of successful product launches
• How AI is changing product launches and team dynamics
• Practical strategies for cross-team collaboration
• The Tranche Model for reducing launch risks
• Building a culture that supports successful launches

Understanding the Launch Code Framework

James explains that Launch Code emerged from studying public companies that grew successfully through their product portfolios. These organizations share common practices that form the foundation of the LAUNCH framework:

Component Description Listen to clients Gather and analyze customer feedback systematically Assess the opportunity Evaluate market potential and strategic fit objectively Unify the team Build alignment across departments Navigate the launch Execute go-to-market activities strategically Control the risks Manage and reduce potential issues Hone the process Improve launch practices continuously

Current Challenges in Product Launches

The AI Impact

Organizations are adapting to rapid changes in how AI affects product launches. James shares that many teams are now working with their second or third generation of AI tools, particularly in sales and marketing. This raises important questions about balancing human and machine roles in the launch process and keeping employees engaged when AI takes over some of their work.

Financial Landscape Changes

A significant shift has occurred in venture funding, with more money moving toward AI investments. James describes working with one organization that had five different sales leaders in 18 months due to these pressures. This example revealed a deeper structural issue: The company needed to move up-market from a commoditized position to remain competitive.

Making Better Launch Decisions

James points out common decision-making problems in product launches. He describes what he calls the “Your PowerPoint is better than mine, but you’re wrong” syndrome – where strong presentation skills can override better strategic choices. Instead, organizations need to:

• Focus on finding the best solution rather than winning arguments
• Challenge assumptions constructively
• Build collective ownership of decisions
• Create space for different perspectives

Building Cross-Functional Success

A key insight from our conversation is how product launches require coordination across departments. James shares an example where changing product strategy meant completely rethinking the sales approach. The company needed salespeople who could sell complex solutions instead of commoditized products, showing how product decisions affect the entire organization.

Creating Common Language

James emphasizes the importance of vocabulary in cross-team work. For example, he notes that “discovery” means different things to sales and product teams:

• Sales discovery: Understanding customer needs during the sales process
• Product discovery: Researching market problems and solutions
• Market discovery: Understanding broader market trends and opportunities

Using clear, shared terms helps prevent misunderstandings and builds better collaboration.

Building the Right Culture

Culture plays a vital role in launch success. James points to Atlassian as an example of intentional culture-building that supports product success. Their approach includes:

• Creating systems for cross-team collaboration
• Building trust through consistent practices
• Focusing on employee satisfaction
• Maintaining strong customer connections

Product Led Growth (PLG) in Action

James explains that PLG companies like Zoom, ClickUp, and Pendo demonstrate the Launch Code principles naturally. These organizations:

• Get direct customer feedback through product usage
• Test features with specific user groups
• Make quick adjustments based on data
• Scale successful features systematically

The Tranche Model: A Practical Launch Approach

During our conversation, James shares how LinkedIn uses what he calls the “Tranche Model” for product launches. This approach involves:

• Testing with defined market segments (tranches) of 2 million users
• Learning from each group before expanding
• Making improvements based on real usage data
• Returning to early groups with refined offerings

For smaller markets, James recommends adapting this approach by creating representative samples. For example, if targeting 1,000 CFOs, start with 150 that represent different company sizes and industries.

Managing Launch Risks

James describes several approaches to controlling launch risks:

Risk Area Management Approach Market Reception Use tranche testing to validate before full release Team Alignment Build clear governance and communication structures Resource Management Maintain flexible budgets for quick adjustments Customer Response Monitor early indicators and feedback channels

Testing New Ideas Through Launches

James shares an interesting observation: organizations often find it easier to test new approaches with new products. For example, if a new service guarantee works well during a launch, teams might then apply it to existing products. This makes product launches valuable testing grounds for innovation.

Common Launch Challenges

James identifies several patterns that can reduce launch effectiveness:

• Making assumptions about customer needs without validation
• Leading research participants toward desired answers
• Missing important market signals
• Working in isolated departmental silos
• Resisting changes to established products

Conclusion

In this episode, James Whitman shares valuable insights about creating reliable product launch processes. The LAUNCH Code framework offers a structured approach that organizations can adapt to their needs. By focusing on continuous improvement, cross-functional alignment, and risk management, teams can build sustainable launch practices that support growth through innovation.

Remember that successful launches depend on more than just the product itself—they require careful attention to organizational dynamics, market conditions, and emerging technologies. Organizations that build these capabilities systematically while remaining adaptable position themselves for sustained growth.

Useful links:

• Learn more about LAUNCH Code
• Learn more about PDMA
• Listen to episode 502: Use LAUNCH Code to ease the overwhelm when launching a B2B product – with James Whitman

Innovation Quote

“Build self-correcting mechanisms to dampen issues as they emerge.” – James Whitman

Application Questions

1. How could you apply the Tranche Model in your market? What would appropriate customer segments look like for your products?
2. What mechanisms could improve collaboration between your product, sales, and marketing teams during launches?
3. How could you build early warning systems into your launch process? Which metrics would matter most?
4. What changes to your current launch approach would enable better feedback and continuous improvement?

Bio

James Whitman is the author of LAUNCH Code: A Playbook for Continuous Growth and the founder of Growth Guidepost. He works with corporate leaders to help them make their most important decisions and achieve critical growth objectives. He has held senior positions in public and private organizations, where he successfully established repeatable commercial practices, launching dozens of products, building high-performing teams, and scaling organizations.

Thanks!

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.

Elevating product strategy through advanced competitive intelligence Watch on YouTube TLDR In this episode of Product Mastery Now, I interview Jay Nakagawa, Director of Competitive Intelligence at Dell Technologies and a 25-year product management veteran. Our discussion reveals proven methods for understanding competitors and developing effective product strategies. Jay shares practical tools and frameworks product […]