Faye Thompson
Director, Delivery Enablement, StarSevenSix
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With more than thirty years of project delivery experience, Faye Thompson serves as a consultant coach, product manager and scrum master. With a focus on an agile mindset and continuous improvement, Faye has had a positive impact in the financial services, healthcare, advertising, marketing, automotive, retail and aviation industries. Passionate about using innovative solutions to drive business value, she trains, mentors and coaches and workgroups as they transform themselves into highly engaged and energized teams.
Faye also enjoys serving on the board of directors for the Central Ohio Agile Association, on the Core Program Committee of the Women in Agile Launching New Voices initiative, and as President of the Women in STEMM Alumni Society of The Ohio State University. She spends her free time volunteering as an emergency medical responder and public affairs coordinator for the American Red Cross.
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Area of Expertise
Embracing the Wave: Exploring the Transformative Potential of AI in Product Management
Artificial Intelligence (AI) has emerged as a groundbreaking technological frontier, offering a wide array of transformative capabilities across various industries, including product management. This talk will provide an introductory exploration of the immense potential of AI and its impact on product management.
We will begin with an overview of the major AI types, including generative AI, machine learning, natural language processing, and computer vision. Attendees will gain a foundational understanding of each, their underlying principles, and their unique contributions to product management. By grasping the fundamental concepts, product managers and will understand AI's power to drive innovation, streamline processes, and deliver exceptional products.
Throughout the presentation, the ethical considerations surrounding AI implementation in product management will be emphasized. We will discuss responsible AI usage, including addressing biases, ensuring transparency, and safeguarding user privacy, thereby fostering trust and ethical decision-making.
Real-world examples, case studies, and practical applications of AI in product management will be shared. Attendees will leave equipped with a set of considerations for integrating AI technologies into their organizations. By embracing AI's capabilities, organizations can leverage its power to shape their products, deliver exceptional user experiences, and thrive in an increasingly AI-driven landscape.
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Notes for Review Team:
This is a talk format, with opportunity for Q&A. I have been using these newer technologies in my day-to-day coaching, consulting and product management work for over 2 years, and want to bring my experiences and learnings to the agile and product communities.
With all of the hype around AI, people feel as though they are behind the curve, and they feel overwhelmed by the tidal wave of information. They are sorting through what can be useful and meaningful in their contexts, and how they can use these technologies effectively and safely. This session provides that primer for them, demystifying terminology and getting them started on understanding how these technologies can improve the quality of their product management.
The session as outlined below, has been delivered twice before in this timeframe, and once as an hour-long session.
Talk Outline:
I. Introduction
A. Overview of the talk
B. Importance of understanding AI in product management
II. Basics of AI
A. Definition of artificial intelligence
B. Major types of AI:
1. Generative AI
2. Machine learning
3. Natural language processing
4. Computer vision
III. Generative AI and its Impact on Product Management
A. Explanation of generative AI
B. Autonomous idea generation, prototyping, and design
C. Advantages of generative AI in accelerating decision-making and rapid iteration
D. Real-world examples
IV. Machine Learning in Product Management
A. Understanding machine learning
B. Optimizing user analysis and market research through machine learning algorithms
C. Leveraging predictive modeling for data-driven decision-making
D. Relevant examples and applications
V. Natural Language Processing in Product Management
A. Introduction to natural language processing
B. Automation of customer interactions and sentiment analysis
C. Extracting insights from conversations, social media, and product reviews
D. Impact on user understanding and product improvement
VI. Computer Vision and Product Management
A. Explaining computer vision technology
B. Visual recognition, image analysis, and object detection
C. Enhancing quality control, visual search, and user experience optimization
D. Real-world use cases and benefits
VII. Ethical Considerations in AI Implementation
A. Importance of ethical practices
B. Addressing biases and ensuring transparency
C. Protecting user privacy
D. Ethical decision-making in product management
VIII. Practical Applications and Best Practices
A. Sharing practical examples and case studies
B. Actionable strategies for integrating AI into product management processes
C. Cultivating a culture of innovation and agility
IX. Conclusion
Prior Feedback:
• Well worth the time. I learned much new information about the state if AI and where it is headed.
• Good content, good stories.
Good, high-level overview of the field of AI and how it can interact with product management. The way you presented it was the right level of correct and grokable for the audience that you were speaking to. It's refreshing to hear an AI talk that doesn't exclusively focus on LLMs these days
Roadmap for a Product Career
Looking for your next career challenge, and not sure in which direction you should head? Let's explore some of the paths available in the business analysis and product world.
In this interactive workshop, we will use a career planning canvas to identify where we are today, and to begin to consider where we might like to go next. Then we'll discuss typical roles associated with these disciplines, the skillsets needed for each, and some ways to grow and strengthen those competencies. Participants will leave with a starter roadmap of next steps to take toward fulfilling their career aspirations.
From Chaos to Clarity: Roadmaps That Deliver
Building a product roadmap isn’t just about plotting features on a timeline—it’s about creating clarity, alignment, and focus in the face of competing priorities. In this session, I’ll share real-life experiences using now–next–later roadmaps to connect strategy to execution. You’ll see how to move from idea to action while ensuring that goals, strategies, objectives, and measurements stay tightly aligned. Through practical examples, I’ll demonstrate how roadmaps can serve as both a communication tool and a decision-making framework, helping teams prioritize what matters most and adapt as conditions change.
Learning Objectives
By the end of this session, participants will be able to:
1. Differentiate between traditional feature-based roadmaps and outcome-driven now–next–later roadmaps.
2. Apply roadmap techniques to translate strategic goals into prioritized strategies that balance short-term needs with long-term vision.
3. Evaluate competing product opportunities using measurable objectives to guide prioritization and stakeholder alignment.
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This session addresses one of the most persistent challenges in product development: connecting high‑level strategy to day‑to‑day execution. While many talks focus on backlog management or feature delivery, this session emphasizes outcome‑driven roadmapping as a leadership tool for alignment, prioritization, and measurable impact. By grounding the discussion in real‑world examples, it provides attendees with practical techniques they can immediately apply to their own organizations. Reviewers can expect this session to resonate with both product leaders and practitioners who need to balance competing priorities while keeping teams focused on delivering value.
Outline
- Introduction & Context
• Frame the challenge: too many ideas, not enough clarity
• Contrast traditional feature-based roadmaps with outcome-driven now–next–later roadmaps
- Why Roadmaps Matter
• Roadmaps as alignment tools: connecting vision, goals, and measurable outcomes
• Real-life examples of roadmaps I have used and the conversations they drove
- Building a Now–Next–Later Roadmap
• Step-by-step walkthrough of the framework
• Demonstration of moving from idea → goal → strategy → objective → measures
• Highlighting how to balance short-term wins with long-term strategy
- Prioritization in Practice
• Techniques for evaluating competing initiatives
• Using objectives and measurements to guide trade-offs
• Saying “no” to good ideas to focus on the right ones
- From Roadmap to Action
• Translating roadmap priorities into execution plans
• Ensuring stakeholder alignment and communication
• Example of how a roadmap became a living decision-making tool
- Wrap-Up
Busy Isn't Valuable: Seeing and Measuring the Flow of Value
Most organizations are busier than ever, yet customers still wait months for the outcomes they asked for. The problem usually isn't effort. It's flow.
Work spends most of its life waiting in queues, handoffs, and approvals that no one sees. Value Stream Management (VSM) makes that waiting visible and measurable.
In this hands-on workshop, you will map a value stream from idea to customer outcome, separate working time from waiting time, and calculate flow efficiency. Many teams discover that only a small fraction of elapsed time is active work. We'll introduce flow metrics, show where BAs and PMs uniquely shape value streams, and practice spotting the bottlenecks that matter.
You'll leave with a completed map, a flow efficiency number, and a step-by-step guide to mapping one value stream in your own organization.
Additional Information for Evaluators
Why this session. BAs and PMs are often measured on output: stories written, features shipped. VSM shifts the conversation to outcomes and end-to-end flow, which is where these roles add the most value.
The idea for this was borne from the IIBA Columbus September session. The participants there noted they are leaning in more to VSM, while also being measured on their AI tool usage. It sounded as though the community could use guidance on both VSMs, as well as how to incorporate AI into their daily routines better.
I am submitting 2 distinct workshop ideas that are designed to be delivered independently; however, together they could be a great package for anyone seeking a deeper dive into VSM, flow and practical applications of AI. If you find that the package serves the program, it would be better for this session to be first, followed by the one that incorporates AI.
What makes it distinctive. The central moment is a reveal. Participants calculate the flow efficiency of a familiar process and usually find that waiting dwarfs working. That number reframes how they think about improvement, and it is easy to repeat back at work.
Learning Objectives
1. Explain how wait time and handoffs, rather than individual effort, drive delays in delivering value.
2. Calculate flow efficiency from a value stream map's work and wait times.
3. Differentiate the five flow metrics and select the one that answers a given business question.
4. Prioritize bottlenecks by their impact on end-to-end flow time and recommend a first improvement.
5. Construct a value stream map for an idea-to-outcome process in their own organization.
Becoming an Integral Influencer: How Business Analysts and Product Managers Can Shape Change
In today’s organizations, influence often matters more than authority. Business analysts and product managers often hold the insights that can transform outcomes, yet can struggle to gain traction with stakeholders. This session introduces the Integral Model as a powerful lens for influence—helping you see the whole system, speak to every perspective, and design strategies that inspire alignment and action. Walk away with practical tools and a new mindset for becoming an “integral influencer” in your own organization
Learning Objectives:
1. Analyze stakeholder dynamics using the Integral Model’s four quadrants to identify gaps in influence strategies.
2. Apply the quadrant framework to real-world business analysis and product management scenarios to design more holistic approaches to stakeholder engagement.
3. Evaluate the effectiveness of past or current influence attempts by diagnosing which quadrants were emphasized or neglected.
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Outline
1. Opening & Context
○ Why influence matters more than authority for BAs/PdMs
○ Quick reflection: when have you struggled to get buy-in?
2. The Problem of One-Dimensional Influence
○ Over-reliance on data or culture alone
○ Need for a whole-system perspective
3. Introducing the Integral Model
○ Four quadrants overview (UL, UR, LL, LR)
○ Visual diagram to anchor the concept
4. Quadrant Deep Dive
○ Upper Left: Mindsets, values, motivations
○ Upper Right: Behaviors, data, measurable outcomes
○ Lower Left: Culture, shared meaning, team dynamics
○ Lower Right: Systems, processes, structures
○ Real-life examples will be highlighted for each quadrant
5. Interactive Exercise: Map Your Influence Challenge
○ Participants identify a current influence challenge
○ Use quadrant handout to map stakeholders, values, data, culture, and systems
○ Pair share: Which quadrant have you been neglecting?
○ Group debrief: 2–3 volunteers share insights
○ Key message: Influence grows when you see the whole system
6. Practical Tools
○ Stakeholder mapping by quadrant
○ Influence checklist: Have I addressed all four?
○ Language flexing: data-driven, values-driven, storytelling, process-fit
7. Case Study Walkthrough
○ Example of failed influence attempt
○ Show how it neglected quadrants
○ Reframe through all four for success
8. Key Takeaways
○ Influence is multi-dimensional
○ The Integral Model is both diagnostic and design tool
○ Ask: Which quadrant am I neglecting?
9. Closing & Call to Action
○ Apply the model in your next stakeholder interaction
○ Reflect afterward on which quadrants you emphasized or missed
Accelerating the Wrong Things: AI and the Value Stream Reality Check
Teams have adopted AI to write user stories, summarize meetings, and draft code. Yet many leaders are asking a hard question: why hasn't delivery sped up? The answer lies in the value stream. When most of a work item's life is spent waiting, making the working steps faster barely moves the needle.
In this interactive workshop, we'll use Value Stream Management to find where AI genuinely changes outcomes. You'll place AI interventions on a realistic value stream map, calculate their effect on end-to-end flow time, and see why targeting wait states, handoffs, and decision delays often beats automating tasks. We'll also use flow metrics as an honest test of AI ROI and examine new risks, such as review backlogs created by AI-generated work.
You'll leave with a practical framework for deciding where AI belongs in a value stream, and the numbers to defend that decision.
Additional Information for Evaluators:
Why this session. Most AI content for BAs and PMs focuses on personal productivity with prompts and tools. This session addresses the question organizations are now facing after adoption: whether AI is improving delivery or just activity or 'busyness'. It gives practitioners a measurable, defensible way to direct AI investment.
The idea for this was borne from the IIBA Columbus September session. The participants there noted they are leaning in more to VSM, while also being measured on their AI tool usage. It sounded as though the community could use guidance on both VSMs, as well as how to incorporate AI into their daily routines better.
I am submitting 2 distinct workshop ideas that are designed to be delivered independently; however, together they could be a great package for anyone seeking a deeper dive into VSM, flow and practical applications of AI.
Learning Objectives:
By the end of this session, participants will be able to:
1. Explain why reducing active work time has limited effect on flow time when wait time dominates.
2. Calculate the projected change in flow time and flow efficiency from a proposed AI intervention.
3. Compare AI interventions that target active work with those that target wait states and handoffs.
4. Assess an AI investment's impact using flow metrics rather than activity or output measures.
5. Design a prioritized set of AI interventions for a value stream, including controls for the risks they introduce.
Articulating Value to Stakeholders
Many of us participate in periodic reviews of the work that our development teams have completed in the form of a sprint review. Sometimes it can seem difficult to articulate the value that has been delivered when that work product doesn't seem 'flashy' or 'exciting'. Too often, this prompts us to fall back to into old patterns of status review. Join us as we examine some different ways to represent value, while getting the feedback we need to adjust and inform our work going forward.
Beyond the Code: Systems Thinking and Influence for Software Engineers
The most influential engineers are not necessarily the ones who write the best code -- they are the ones who understand how technology, people, culture, and organizational structures interact to create outcomes.
Software developers and engineers are trained to solve complex technical problems, yet many of the challenges that determine project success are not technical at all. Architecture decisions stall despite clear benefits. Modernization efforts create unexpected resistance. Teams continue accumulating technical debt even when everyone recognizes the problem.
What if the real issue isn't the technology, but an incomplete view of the system?
This session introduces the Integral Model, a practical framework for expanding systems thinking beyond software and architecture into the human and organizational dynamics that shape engineering outcomes. Participants will learn to analyze challenges through four interconnected dimensions: individual mindsets, observable behaviors, team culture, and organizational structures. By gaining a more complete understanding of the systems surrounding their work, engineers can become more effective influencers, change agents, and technical leaders regardless of role or title.
Through interactive exercises, attendees will learn how to diagnose why technical initiatives succeed or fail, identify hidden constraints, and design influence strategies that drive meaningful change. Whether you're advocating for architectural improvements, increasing adoption of engineering practices, leading platform initiatives, or preparing for a Technical Leadership role, this session will provide new tools for seeing the whole system and increasing your impact.
Participants will leave with practical techniques they can immediately apply to influence technical decisions, improve collaboration, and create better outcomes across both technical and organizational systems.
Cultivating Space for Learning
Software development is a highly creative endeavor. To do it successfully requires space for collaboration and experimentation. Providing an environment in which people have room to think, and the safety to try, learn and adapt is key.
If you are in an environment that doesn't take full advantage of learning opportunities, or even discourages time for learning altogether, this highly-interactive session is for you.
We will discuss the conditions needed to provide the greatest opportunity for learning and continuous improvement. Through guided activities, participants will examine the current conditions in their own team environments, and leave the session with an action plan to cultivate spaces where teams can grow and thrive.
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