154: John Dues: "What Does a System of Profound Knowledge Really Look Like?"

This conversation with John Dues challenges one of the most deeply held assumptions in leadership: that people are the primary drivers of performance.Drawing on W. Edwards Deming’s System of Profound Knowledge, John introduces a radically different lens—one where systems, variation, psychology, and learning cycles shape nearly everything we see in organizations.Erik enters the conversation curious—and leaves with a fundamentally different way of thinking about data, incentives, and what it actually takes to improve performance. 👤 About the GuestJohn A. Dues is the Chief Learning Officer and Chief Operating Officer at United Schools in Columbus, Ohio.Improvement science practitioner and systems thinker Author of Win-Win: W. Edwards Deming, the System of Profound Knowledge, and the Science of Improving SchoolsHas helped build seven schools and nonprofit organizations Deeply focused on applying Deming’s philosophy to real-world systems 🧭 Conversation HighlightsThe System > The Individual. Most organizations operate in silos, optimizing departments instead of the whole. Ironically, this often makes overall performance worse. The 4 Components of Profound KnowledgeAppreciation for a system Knowledge about variation Theory of knowledge Psychology The Data Illusion. Comparing two data points (month-over-month, year-over-year) is often meaningless. The real story lives in patterns over time. Common vs Special Cause Variation. Most performance differences aren’t meaningful—they’re just noise within the system. Why Incentives Backfire. Commission structures and ranking systems often drive behavior that harms the organization as a whole. PDSA Cycles (Plan-Do-Study-Act). Improvement isn’t about big initiatives—it’s about small, fast, iterative experiments. 💡 Key TakeawaysMost results come from the system—not individuals. Deming estimated 95–97% of outcomes are system-driven. Optimizing parts can break the whole. Sales and operations working “perfectly” in isolation can create massive dysfunction together. Measurement must match intent. Measuring for accountability vs improvement leads to completely different behaviors. Data doesn’t tell stories—people do. Data points direction, but context completes the picture. ❓ Questions That MatteredWhat if the problem isn’t your people—but your system? Why are we measuring this—and what are we trying to do with it? Are we reacting to noise or actual signal? What behavior is our system really incentivizing? How do we know what we think we know? 🗣️ Notable Quotes A lot of organizations optimize departments… and make the system worse.” “95% of results are attributable to the system—not the people.” “The story is locked up in the pattern over time.” “Why you measure something determines how people behave.” “You don’t implement fast and learn slow—you learn fast and scale slow.” “Extrinsic motivation can crush the love of learning.” 🔗 Links & ResourcesCheck out John Dues' Book 'Win WinFollow John on LinkedIn