May 13, 2026

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 Guest

John 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 Schools
  • Has helped build seven schools and nonprofit organizations
  • Deeply focused on applying Deming’s philosophy to real-world systems

🧭 Conversation Highlights

  • The 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 Knowledge
    • Appreciation 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 Takeaways

  • Most 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 Mattered

  • What 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 & Resources