I have a fascinating conversation with Evan Campbell in this episode. Evan brings an unusually broad perspective to organizational transformation, drawing on a career that spans the U.S. Army Special Forces, telecommunications, software development, entrepreneurship, Lean consulting, and executive leadership. He is also the author of Adapt to Win, a book focused on helping organizations turn strategy into execution while developing the adaptability required to compete in a rapidly changing world.

Our conversation begins with a deceptively simple question: Why are so many organizations bad at executing their strategies? Companies spend millions developing sophisticated strategies, yet those strategies frequently fail to translate into meaningful changes in how work gets done. Evan argues that the problem often isn't the strategy itself; it's strategy deployment. By the time strategic intent travels from executives through layers of management to the people actually doing the work, the signal has often become distorted, fragmented, or lost entirely.

Evan also offers a useful test for whether an organization really has a strategy: Where do we play, and how do we win? If leaders across the organization provide dramatically different answers, or if the strategy consists entirely of statements nobody could reasonably disagree with, then the apparent alignment may be little more than superficial consensus. Real strategy requires choices, and choices necessarily mean deciding what the organization will not do.

We explore this through Evan's experiences inside large organizations, including an IT organization overwhelmed by more work than it could effectively process. Rather than confront excessive work in process and unstable delivery, leadership wanted to repair relationships with dissatisfied stakeholders. Evan uses the example to illustrate a recurring transformation failure: organizations often want consultants to address the symptoms of a broken system without changing the system producing those symptoms.

The conversation eventually turns toward AI and the latest wave of digital transformation. We see many of the same patterns that appeared during outsourcing, Agile, DevOps, and previous transformation movements. Organizations can easily mistake adopting a technology or creating a new department for actually transforming how they operate. AI may dramatically reduce the effort required to produce software, but that doesn't eliminate constraints. Understanding requirements, architecture, validation, strategic prioritization, and determining whether we're building the right thing become even more important.

Ultimately, this episode is about much more than strategy frameworks, OKRs, Lean, or AI. It's about building organizations capable of learning and adapting. Technology will continue to change, constraints will move, and today's transformation will eventually be replaced by another. The organizations most likely to thrive will be those that can understand their systems, make deliberate strategic choices, learn from results, and continuously adapt how they invest their limited resources.

Show Notes:

• Evan's book, Adapt to Win: https://adapttowin.co/ Also available on Amazon, Barnes & Noble, and other major retailers.
• Adaptivity Group (Evan's consulting firm): https://www.adaptivitygroup.com/
• Evan's YouTube Channel: https://www.youtube.com/@AdapttoWin-Book

I have a conversation with Katie Anderson, Rob Park, and Glenn Wilson in this episode as we reflect on an experience that is difficult to replicate from a book, conference, or classroom: going to Japan to see the principles behind Lean, continuous improvement, and Toyota firsthand.

Katie, author of Learning to Lead, Leading to Learn, leads immersive learning experiences in Japan, and Rob, Glenn, and I have joined her on different cohorts. Together, we explore what happens when ideas from W. Edwards Deming, Lean, Toyota, DevOps, and continuous improvement move beyond concepts we understand intellectually and become something we can actually see, experience, and bring back into our own work.

Rob describes seeing an Andon in action and watching a team leader immediately work alongside an employee to solve a problem. Glenn connects that experience directly to DevOps and software security, asking what it would mean if technology organizations genuinely responded to problems rather than allowing defects and vulnerabilities to accumulate. However, some of the most lasting lessons came from places they didn't necessarily expect. From watching children take responsibility for cleaning their school to experiencing Japanese approaches to purpose, community, long-term thinking, and improvement, we discovered why simply copying Toyota's practices misses something important. Glenn returned more curious and less prescriptive with his clients. Rob similarly moved away from arriving as the expert with the answer and toward helping teams discover their own path to improvement.

We also explore the relationship between Deming and Japan. Rather than viewing Deming simply as someone who transformed Japanese management, I reflect on the possibility that Japan transformed Deming as well. Spending time with former Toyota leader Isao Yoshino, who began his Toyota career in 1967, makes that history especially tangible, including his perspective on Deming's influence and the importance of understanding data.

Throughout the conversation, stories from factories, an elementary school, the Toyota museum, the Shinkansen cleaning operation, the 100-Year Calendar, and Japanese daruma dolls reveal why Katie describes these experiences as moving our understanding “from the head to the heart.” The real lesson isn't to imitate Japan or collect another set of Lean tools. It's learning to see differently.

For anyone who has studied Deming, Lean, Agile, DevOps, or continuous improvement and wondered what changes when you experience these ideas where so much of their history was shaped, this conversation offers a glimpse. Katie's next Japan learning experience takes place this November, and enrollment is now in its final days. Details are available at kbjanderson.com/japantrip.

In this episode, I have a conversation with Laksh Raghavan. We dive deep into the origins of cybernetics, second-order systems thinking, and why W. Edwards Deming's philosophy remains as relevant as ever in today's AI-driven world. Laksh, founder of Cybersyn Labs and a systems thinker specializing in cybersecurity and executive coaching, shares how cybernetics provides a powerful framework for understanding organizations, leadership, and digital transformation.

The conversation begins by tracing the roots of cybernetics through Norbert Wiener before moving into the groundbreaking work of Heinz von Foerster, whose concept of second-order cybernetics shifts the focus from simply observing systems to recognizing that the observer is part of the system. Laksh explains that every observation is shaped by our experiences, biases, and mental models, making objectivity impossible without acknowledging the observer. This perspective has profound implications for leadership, collaboration, and organizational decision-making.

We then explore how these ideas connect directly to Deming's System of Profound Knowledge. Organizations often struggle because leaders attempt to implement transformations, whether AI initiatives, DevOps, or cybersecurity programs, without understanding the human system that must adopt them. Rather than imposing top-down solutions, successful leaders cultivate conversations, seek diverse perspectives, and recognize that understanding emerges through interaction rather than command.

The discussion also examines why complexity cannot be managed through rigid control. Using examples from chaos engineering, biological evolution, and Heinz von Foerster's demonstrations of "order from noise," Laksh argues that experimentation, feedback, and variation are essential for innovation. These concepts naturally lead into Stafford Beer's management cybernetics and Ross Ashby's Law of Requisite Variety, illustrating that organizations survive by increasing their capacity to respond to complexity rather than attempting to eliminate it.

Throughout the conversation, Deming's influence is unmistakable. Whether discussing going to the Gemba, embracing continual learning, or recognizing that organizational transformation begins with transformed leaders, Laksh reinforces that lasting change requires epistemic humility, the willingness to admit we may not fully understand the systems we lead. As AI reshapes every industry, the greatest opportunity lies not in adopting new technology, but in developing leaders capable of seeing organizations as living systems where learning, adaptation, and multiple perspectives create enduring success.

Ultimately, this episode reminds us that digital transformation is not primarily a technology challenge; it’s a systems challenge. By combining Deming's teachings with modern cybernetics, Laksh offers a compelling vision for building organizations that are more resilient, adaptive, and fundamentally human.

Laksh's LinkedIn: https://www.linkedin.com/in/laraghavan/

I have a conversation with Balaji Reddie in this episode. We dive deep into W. Edwards Deming’s seminal perspectives on quality, exploring how Deming’s ideas continue to shape modern management, systems thinking, and organizational transformation. Balaji shares his personal journey into quality management, including a remarkable family connection to Japan and a Deming Prize-winning company that sparked his lifelong fascination with Deming’s work.

The discussion examines why Deming’s teachings remain both powerful and challenging. Balaji explains that, unlike many quality thinkers who provided step-by-step methods, Deming focused on helping leaders understand why systems behave the way they do. This distinction leads to a rich conversation about the relationship between Deming and Joseph Juran, with Balaji highlighting how Deming inspired transformational thinking at the leadership level while Juran provided practical management structures that helped organizations implement quality initiatives.

A significant portion of the conversation explores the history of post-war Japan. Balaji recounts how Deming’s message resonated with Japanese leaders not only because of his statistical expertise, but because he offered hope, direction, and a compelling vision for national and industrial renewal. The discussion challenges simplistic narratives about the “Japanese miracle,” emphasizing the role of Japanese industry leaders who embraced these ideas and adapted them to their own context.

The episode also dives into Deming’s System of Profound Knowledge. Balaji explains the interconnected nature of systems thinking, variation, theory of knowledge, and psychology, emphasizing that these concepts cannot be understood in isolation. He offers practical interpretations of control charts, variation, learning, prediction, and continuous improvement, illustrating how Deming’s philosophy extends far beyond manufacturing into any complex system.

Toward the end of the conversation, John and Balaji connect Deming’s ideas to emerging technologies such as AI and agentic systems. They discuss how Deming’s principles around systems, responsibility, variation, and learning may become even more relevant as organizations increasingly rely on autonomous technologies. The episode concludes with reflections on education, leadership, and the enduring importance of understanding systems rather than merely managing outcomes.

Links:
Balaji Reddie's LinkedIn - https://www.linkedin.com/in/deming/

I have a conversation with Kendra MacDonald in this episode. As CEO of Canada’s Ocean Supercluster, Kendra is helping reshape how industries, governments, researchers, and technologists collaborate around one of the planet’s most important and least understood systems: the ocean. We dive deep into how emerging technologies like AI, autonomous systems, and quantum computing are transforming the ocean economy, while also exploring the organizational and leadership challenges that come with innovation at scale.

Kendra explains how the Ocean Supercluster was created as a national effort to accelerate commercialization, strengthen collaboration, and modernize ocean industries through technology. The conversation expands beyond marine innovation into broader themes of systems thinking, digital transformation, and the importance of solving business problems before deploying technology. Drawing from her background at Deloitte and her work advising organizations on technology adoption, Kendra shares why so many AI initiatives struggle, not because of the tools themselves, but because organizations fail to align culture, governance, and operational goals.

We also explore the tension between innovation and governance, challenging the common belief that controls slow progress. Kendra argues that thoughtful governance, risk management, and cross-functional collaboration actually accelerate innovation by creating trust and reducing downstream failures. The discussion touches on AI risk in high-consequence environments, autonomous shipping, data trust, digital twins, predictive maintenance, and the growing role of AI in optimizing maritime operations.

One of the most compelling parts of the conversation centers on the future of quantum computing and its potential impact on ocean science, logistics, climate prediction, and biodiversity discovery. Kendra and John reflect on how industries can prepare now for technologies that may radically reshape optimization and decision-making in the coming decade.

The episode ultimately becomes a broader reflection on interconnected systems, oceans, organizations, technology ecosystems, and society itself. Kendra offers a powerful reminder that the ocean is not simply a coastal issue, but a global infrastructure system affecting supply chains, climate resilience, communications, energy, and food security. It’s a thoughtful discussion about innovation stewardship, systems thinking, and the responsibility of leaders to build technology strategies grounded in purpose and long-term impact.

I have a conversation with Farhan Sheikh in this episode. We dive deep into W. Edwards Deming’s System of Profound Knowledge and explore how its principles can be applied to modern software development and AI-assisted coding.

Farhan shares his unique journey from developer to QA leader, where he applied Deming’s philosophy, particularly variation, theory of knowledge, and systems thinking, to transform how teams approach quality. Rather than relying on inspection at the end, he emphasizes building quality into the process through better test design, tighter feedback loops, and collaboration between testers and developers.

A central theme is Farhan’s “Darmok” approach: using structured examples and test cases to guide AI systems like Claude, instead of relying heavily on prompts. By feeding AI consistent, well-sequenced patterns, he demonstrates how teams can reduce variation in AI-generated code and achieve more reliable outcomes. This mirrors Deming’s principles, controlling variation and improving systems rather than reacting to defects.

The conversation also explores the evolving role of QA. Farhan argues that testers, with their strength in asking critical questions and creating clear examples, are uniquely positioned to become key players in AI-driven development. This shift blurs traditional roles, pointing toward a new kind of multidisciplinary “AI producer” who integrates development, testing, and system-level thinking.

Psychology and leadership emerge as critical factors. Farhan candidly discusses overcoming fear within teams, aligning motivations through data and experimentation, and the importance of leaders enabling systemic change rather than reinforcing silos.

The episode concludes with a powerful reflection: true digital transformation isn’t about adopting AI tools in isolation, but about rethinking the entire system of work through Deming’s lens, focusing on quality, reducing variation, and empowering people to learn and adapt.

In this episode, Glenn Wilson, a cybersecurity expert, joins me to explore how systems thinking can reshape how we approach cybersecurity, vulnerability management, and modern digital systems.

Glenn shares his journey from writing about DevSecOps to pursuing a master’s degree in Systems Thinking in Practice at the Open University. His motivation came from recognizing a troubling contradiction that, despite massive investments in cybersecurity, data breaches, ransomware incidents, and security failures continue to rise. This led him to question whether the industry’s largely reductionist approach misses the broader system dynamics at play.

A central part of the discussion focuses on Stafford Beer’s Viable System Model (VSM), a cybernetic framework for understanding how organizations maintain balance and adapt to their environments. Glenn explains how VSM’s five subsystems can be used to diagnose why cybersecurity systems often fail. Rather than viewing security as a set of tools or controls, Glenn argues it should be understood as a living system embedded within larger organizational and risk systems.

The conversation then expands into cybernetics, emergence, and AI, touching on Norbert Wiener, Ross Ashby’s law of requisite variety, and John Boyd’s OODA framework. Together, we discuss how feedback loops, adaptation, and emergent behavior shape both human organizations and AI-driven systems. Glenn raises an important concern: if organizations don’t adopt systems thinking, increasing automation and AI could amplify weaknesses rather than solve them.

We close by reflecting on the relationship between humans, AI, and complex systems. Glenn emphasizes that AI should be treated as a tool within a larger system, not anthropomorphized as human intelligence. The key challenge ahead is understanding how humans and intelligent tools coexist within systems that are adaptive, emergent, and increasingly complex.

The big takeaway: cybersecurity cannot be improved by optimizing isolated parts. Real progress requires understanding the entire system and our place within it.

In this episode, I have an insightful and wide-ranging conversation with Carol Houle, CEO of Inspire Digital Consulting. We explore her career journey across software development, lean supply chain transformation, cloud, and DevOps, and how these experiences led her to a central conviction: leadership is the primary bottleneck in digital transformation.

Carol traces her roots back to early exposure to TQM and W. Edwards Deming during her undergraduate studies and her work at Pricewaterhouse Consulting in the 1990s, where lean principles were applied to supply chains. As Carol moved into larger leadership roles, a consistent pattern emerged: transformation efforts stalled not because of teams or tools, but because leaders themselves were the constraint. Yet leadership is rarely examined.

Carol introduces her book and the Inspired Leadership Framework, which grew organically over a decade of observation, writing, and experimentation. Drawing from her experience spanning business, she distills leadership into measurable dimensions.

Looking forward, Carol connects leadership quality to the coming era of agentic AI. AI will amplify whatever already exists. Weak leadership, unclear purpose, or misaligned incentives will scale into systemic risk. She introduces the idea of “benevolent AI agents” that help detect bias, misalignment, and deviations from stated intent.

Show Notes:

You can learn more about Inspired Digital Consulting and take the Inspired Leadership Assessment here - https://inspiredigitalconsulting.com/

Carol Houle's LinkedIn - https://www.linkedin.com/in/carolhoule/