The Knowledge System Podcast

Michael Carr
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The Knowledge System Podcast explores how leaders can use systems thinking to create lasting organizational improvement. It translates the ideas of W. Edwards Deming and other thought-leaders into practical strategies for building smarter, more effective systems. posts.knowledgesystem.com

  1. 3H AGO

    Five-minute Deming: Copying competitors

    When pressure rises, leaders look sideways. A competitor simplifies an offer, tightens pricing, or adopts a new tool—and suddenly it feels irresponsible not to follow. After all, they’ve already tested it. The market seems to respond. What’s the harm in borrowing what works? W. Edwards Deming warned that this instinct is more dangerous than it looks. Copying competitors feels like learning, but it isn’t. It replaces understanding with imitation—and over time, it quietly erodes the capabilities that create lasting advantage. Looking sideways feels sensible Competitive awareness is often praised as strategic discipline. Leaders are taught to benchmark, compare, and react. When growth slows or margins tighten, this behavior intensifies. Decisions increasingly begin with familiar questions: What are they offering? How are they pricing? What tools are they using? Deming didn’t argue that leaders should ignore the outside world. He argued something more subtle—and more demanding: examples without theory don’t teach improvement. When you copy a result without understanding the system that produced it, you’re not learning. You’re guessing. The temptation to guess is strongest when results are hard to observe directly. Success is shaped by hidden conditions: workflow design, skills, decision rights, feedback loops, and constraints. Those don’t appear in a competitor’s marketing or pricing sheet. What does appear are surface features—offers, promises, and positioning—and those are the easiest things to imitate. A familiar story Alex ran a mid-sized professional services firm with smart people, loyal clients, and a solid reputation. For years, growth had been steady. Then sales began to slow. Deals dragged. Clients hesitated. At the same time, a competitor started winning work with a clean, packaged offering. Fixed scope. Fixed price. Confident messaging. Prospects mentioned it repeatedly. “Everyone keeps bringing them up,” Alex said in a leadership meeting. “Clients say, ‘They make it simpler.’ We’re losing deals we used to win.” The pressure to respond was immediate. “They’re just repackaging what everyone else does,” Morgan replied. “We could roll this out in a month.” “If clients want simple, let’s give them simple,” Alex agreed. “Same structure. Same price points. We can’t afford to look complicated.” The firm moved fast—new packages, new website copy, new proposal templates. From the outside, they looked competitive again. Inside, things unraveled. “Delivery’s struggling,” Morgan said a few weeks later. “The teams keep escalating scope questions. The package assumes things we don’t actually control.” “But that’s how they sell it,” Alex replied, gesturing toward the competitor’s brochure on the table. “Yes—but we don’t know how they deliver it.” Deming warned about this exact trap: copying the visible example while ignoring the invisible system. The firm had copied the promise, not the capability. The packaging assumed standardized work, predictable inputs, and stable handoffs—none of which the firm had invested in. Projects began running over. Staff felt squeezed between rigid promises and messy reality. Clients noticed the growing gap between what was sold and what actually showed up. “We fixed the sales problem,” Alex finally admitted, “and created a delivery problem.” That pause mattered. Instead of doubling down—tightening enforcement, blaming teams, or discounting harder—Alex asked a different question: What theory are we operating under? What did they believe actually created value for clients? And what system was required to deliver that value reliably? The firm began studying its own work. Where projects slowed. Where rework came from. Which clients benefited most, and why. They ran small tests before changing external promises—clarifying scope boundaries, simplifying internal handoffs, and making client responsibilities explicit. “The competitor’s package wasn’t wrong,” Morgan observed. “It just wasn’t ours.” Over time, the firm rebuilt its offering around outcomes it could actually deliver. Sales stabilized—not because the firm looked like everyone else, but because its promises finally matched its system. Where leaders go wrong Most leaders don’t copy competitors out of laziness. They do it out of urgency. Comparison feels like action. It provides cover. If everyone is moving in the same direction, the risk feels shared and defensible. The trouble is that copying shifts attention away from the system that produces results. It encourages leaders to manage appearances instead of capability. Organizations become skilled at changing what they say—new offers, new pricing, new tools—while leaving how work actually gets done largely untouched. Deming captured this dynamic with a sharp observation: “What would some people do without their competitors?” When competitors become the primary reference point, learning stalls. Decisions become reactive. Improvement turns into imitation rather than inquiry. What would some people do without their competitors?— W. Edwards Deming There’s a second cost that’s easier to miss. As Deming also noted, “The fact is that the customer expects only what you and your competitor have led him to expect. He is a rapid learner.” Copying competitors doesn’t just follow the market—it trains it. Expectations ratchet upward, margins compress, and organizations find themselves competing harder while improving less. In that environment, leaders can feel busy and responsive while the system itself remains fragile. The work becomes harder, not because people lack effort or skill, but because the organization hasn’t invested in understanding how results are actually produced. Actionable Takeaways Moving beyond imitation doesn’t require ignoring competitors. It requires changing how their ideas are used—and what questions leaders ask first. * Start with aim. Be explicit about who you serve, what problem you solve, and what “better” means over time. Without a clear aim, competitor behavior quietly becomes your strategy. * Turn examples into hypotheses. Instead of copying what worked elsewhere, ask why it might work—and what conditions would need to be true in your system for it to succeed. Treat every borrowed idea as something to test, not adopt. * Study the delivery system first. Offers, pricing, and positioning are system decisions. If you change the front end without strengthening the back end, you create stress—not improvement. * Use theory to learn. Deming said, “Experience teaches nothing… Without theory there is no learning.” Improvement requires prediction, testing, and reflection—not imitation. A simple test helps ground this thinking. Before approving a competitor-inspired change, ask what capability must improve for the promise to be kept. If you can’t name it, you’re not improving the system—you’re decorating it. Closing Copying competitors feels safe because it spreads the risk. If everyone’s doing it, it can’t be wrong—right? Deming challenged that comfort. When leaders stop borrowing answers and start building knowledge about their own work, something shifts. Learning replaces imitation. Confidence grows from understanding, not comparison. Real competitive advantage comes from knowing your system well enough to improve it deliberately. When improvement becomes steady and capability compounds over time, the focus moves away from keeping up—and toward building something others struggle to copy. Experience teaches nothing… without theory there is no learning.— W. Edwards Deming This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    8 min

  2. FEB 11

    Five-minute Deming: Blaming the worker

    When leaders hear that most problems belong to the system, it can sound like an accusation—or worse, an invitation to lower standards. So nobody’s lazy? Nobody incompetent? That reaction is understandable. It’s also costly. The real question isn’t whether individuals ever contribute to problems. It’s whether leaders are aiming their time and energy at the place where improvement actually lives. Today we’ll explore why blaming workers feels decisive, why it so often misses the mark, and how a clearer way of thinking leads to better results. Why blaming the worker feels obvious W. Edwards Deming never asked leaders to take anything on faith. He asked them to study evidence. Yet his ideas are frequently dismissed as naïve because they seem to collide with lived experience. Leaders have seen missed deadlines, chronic rework, and visible disengagement. They’ve had hard conversations. They’ve replaced people—and sometimes things really did improve. So when Deming says that most problems belong to the system, it can sound like an absolutist claim that denies reality. It isn’t. What Deming challenged was a habit of mind: explaining outcomes by pointing at people instead of understanding the conditions that shape their work. When the same problems repeat across teams and across individuals, he argued, we are not observing human failure. We are observing a system doing exactly what it was built—and allowed—to do. To see how this misunderstanding plays out, consider a familiar manufacturing setting. Reconsidering where problems come from Midwest Components manufactures precision parts for heavy equipment. Late orders have become routine. Scrap rates swing from week to week. Supervisors are worn down by constant firefighting. At the center of it are two leaders. Jack, the plant manager, came up through operations. He prides himself on knowing the floor and holding people accountable. Maria, the operations director, was brought in to stabilize performance and reduce chronic volatility. Jack is blunt about his frustration. “Look,” he says, “I don’t buy this idea that it’s all the system. I’ve been here twenty years. I know when someone just doesn’t care.” Maria doesn’t dispute that people matter. “I’m not saying people don’t matter,” she says. “I’m asking a different question. If we swap operators between lines and the problems stay with the line, what are we really seeing?” They review six months of data together. Late orders spike predictably at month end when schedules compress. Scrap jumps whenever a specific alloy lot is introduced. Training records show three operators rushed onto a new machine with minimal setup instruction. Jack pushes back. “So what,” he asks, “nobody’s accountable?” Maria draws a distinction. Accountability isn’t the same as blame. The patterns they’re seeing don’t belong to one person. They belong to how work is planned, supplied, and taught. This is the pivot Deming insisted on. In Out of the Crisis, he wrote, “The supposition is prevalent the world over that there would be no problems in production or in service if only our production workers would do their jobs in the way that they were taught. Pleasant dreams. The workers are handicapped by the system, and the system belongs to management.” That statement isn’t a moral judgment. It’s a diagnostic one. The supposition is prevalent the world over that there would be no problems in production or in service if only our production workers would do their jobs in the way that they were taught. Pleasant dreams. The workers are handicapped by the system, and the system belongs to management.— W. Edwards Deming Maria reframes the discussion in plain language. “First,” she says, “are things running the way they usually do? If they are, blaming the worker for random ups and downs doesn’t fix anything. Second, if something truly unusual happened—something you don’t normally see—then we treat it as a special cause and deal with it directly.” They chart downtime and defects. Most of what they see sits inside predictable limits. One incident stands out clearly: a machine was deliberately bypassed after a safety interlock failed. Jack agrees immediately. “That one’s on the person,” he says. Maria agrees too. “Yes,” she says. “And because it’s clearly unusual, we can handle it firmly and directly—without pretending it explains everything else that’s been happening.” Deming was explicit about this balance. “I should estimate that in my experience most troubles and most possibilities for improvement add up to proportions something like this: 94% belong to the system (responsibility of management) 6% special.” That six percent matters. It includes negligence, misconduct, and genuine inability. But treating ninety-four percent as if it were six is expensive. I should estimate that in my experience most troubles and most possibilities for improvement add up to proportions something like this: 94% belong to the system (responsibility of management) 6% special.— W. Edwards Deming As Midwest Components changes its approach, conversations on the floor change as well. Supervisors stop asking who screwed up and start asking what conditions made outcomes likely. Training is stabilized. Scheduling is smoothed. Supplier variation is addressed. The one true special-cause issue is resolved and doesn’t need to be recycled as a warning story. Performance improves—not because people suddenly became better, but because the system stopped working against them. Where leaders get stuck Most of us don’t blame workers because we enjoy it. We do it because it feels decisive. Someone must have caused the problem, and identifying that person creates a sense of action. But when results are driven by the system, this habit quietly backfires. We demand explanations for normal ups and downs. We reward and punish based on noise. Fear increases. Stories replace learning. Leaders stay busy while the underlying causes remain untouched. There’s also a subtler trap. When we believe outcomes are mainly about individual effort, we start to see disengagement as a personal flaw instead of a signal. We miss opportunities to redesign work so that success is the natural outcome, not a heroic one. Deming warned against this explicitly when he urged leaders to eliminate slogans and exhortations. They create adversarial relationships, he argued, because the bulk of the causes of low quality and low productivity lie beyond the power of the workforce. The result isn’t higher standards. It’s frustration on both sides. Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. Actionable Takeaways The alternative to worker blame is not indulgence. It’s discipline. * Stop demanding explanations for routine variation. When things are running the way they usually do, stories won’t help. Improvement comes from changing the system, not interrogating individuals. * Make the distinction between common and special causes explicit. Leaders and supervisors should know the rules. When evidence shows the system produced the result, leadership owns the fix. When evidence shows a true special cause, address it directly and respectfully. * Redesign supervision around enablement. The job is not to motivate people to care more. It’s to make it possible for people to succeed through clear methods, adequate training, sensible workload, and timely feedback. * Treat pride of workmanship as a leadership responsibility. When barriers are removed instead of blame being assigned, problems surface earlier—when they are smaller, safer, and cheaper to fix. These actions don’t lower standards. They raise them—by aiming effort where it actually matters. Closing Deming didn’t ask leaders to deny what they’ve seen. He asked them to look more deeply at it. Yes, some problems are caused by individuals. Far more are created by systems that quietly shape behavior, day after day, often without anyone intending harm. There is something profoundly hopeful in this. Systems can be redesigned. Conditions can be improved. People who appear disengaged often surprise us when the work finally makes sense and success is possible. “The greatest waste in America is failure to use the abilities of people,” Deming warned. When leaders shift from blame to understanding, organizations don’t get softer. They become more humane, more capable, and more effective. The greatest waste in America is failure to use the abilities of people.— W. Edwards Deming This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    8 min

  3. FEB 4

    Five-minute Deming: Pay vs. performance

    Most leaders believe pay is the lever that keeps people accountable. Tie raises to individual performance, and people will work harder. Untie them, and standards will slip. That belief feels especially strong in operations where timing matters—where a late start cascades into lost output, overtime, and frustration. But what if the very tools meant to enforce accountability are quietly making the system worse? W. Edwards Deming spent much of his career challenging a deeply held management assumption: that individual performance can be measured, ranked, and rewarded in a way that reliably improves results. His critique was not philosophical. It was grounded in how real work actually happens. Deming was blunt about the damage caused by this assumption. He wrote that “evaluation of performance, merit rating, or annual review” is a management disease—one that builds fear and undermines cooperation instead of improving results. A deadly disease: evaluation of performance, merit rating, or annual review— W. Edwards Deming In most organizations, especially those that operate in shifts, results are produced by systems—by schedules, handoffs, training, equipment readiness, and staffing decisions. When leaders focus compensation on judging individuals instead of improving systems, fear replaces learning, and supervisors become referees instead of leaders. This tension is often dismissed as a white‑collar concern. But the opposite is true. The more tightly coupled the work, the less individual performance explains outcomes—and the more management decisions shape results. That reality plays out clearly at Sunrise Acres, a large egg farm running multiple barns across three shifts. When measurement isn’t enough Sunrise Acres depends on precision. Every shift change affects feeding schedules, sanitation routines, and downstream quality. When crews start late, the consequences ripple through the day. Miguel, the operations manager, is exhausted by the problem. “We track everything,” he says. “Names. Minutes late. Warnings. We even tie raises to attendance—and it still doesn’t stick.” Late starts keep happening. Sarah, the farm’s general manager, doesn’t argue with him. “What if the problem isn’t the people?” she asks. “What if it’s the way the day starts?” Together, they walk the process from parking lot to first task. The issues surface quickly. The time clock is deep inside the barn. Protective equipment is stored in multiple locations. New hires aren’t clear on relief coverage. Buses arrive with built‑in variability. And supervisors are stretched thin at shift change. No one would blame a single hen for a flock problem. Seeing the system end to end makes it clear that punctuality has been treated like a character trait, even though the system makes being on time unnecessarily hard. They make practical changes: moving the clock closer to the entrance, pre‑staging PPE kits, adding a short overlap for handoffs, and using visual start‑time cues. A bilingual lead helps direct arrivals. Attendance improves almost immediately. One employee, Rosa, is still late. Instead of issuing another warning, Miguel follows Sarah’s lead and starts a conversation. Rosa explains that her childcare opens at the same time her shift begins. A small schedule adjustment and cross‑training resolve the issue completely. What becomes clear is that most lateness was common‑cause—built into the system. A few cases required individual action, but only after the system barriers were removed. When raises come due, Miguel hesitates. “So… no merit scores?” Sarah is explicit. Base pay is set by role and market. Raises come through skill blocks—what people are trained and qualified to do. Any shared upside is tied to farm‑level performance. Attendance expectations remain firm, and willful noncompliance is addressed directly. What they abandon is the fiction that a yearly rating caused punctuality. Deming warned that “evaluation of performance, merit rating, or annual review” builds fear and rivalry while demolishing teamwork. He also cautioned that it is “unfair, as it ascribes to the people in a group differences that may be caused totally by the system that they work in.” At Sunrise Acres, supervisors stop keeping secret tallies and start removing barriers in the work. Training accelerates. Turnover slows. Late starts drop—and so do the hidden costs that came with them. [Performance-based pay] is unfair, as it ascribes to the people in a group differences that may be caused totally by the system that they work in.— W. Edwards Deming Where managers go wrong Most leaders don’t rely on merit pay because they enjoy ranking people. They do it because it feels like control—especially when schedules slip or output falters. Deming warned that this instinct leads managers to confuse numbers with knowledge. When results vary, rating people feels decisive, even when the variation comes from the system itself. When attendance problems show up, the instinct is to tighten enforcement, add documentation, or raise the stakes. But in tightly coupled systems, this approach confuses accountability with judgment. It treats variation created by schedules, transportation, training gaps, and process design as individual failure. We tell ourselves that without performance‑based pay, standards will collapse. In practice, the opposite often happens. Fear drives people to protect themselves rather than surface problems. Supervisors spend their time policing instead of improving the work. This doesn’t mean ignoring behavior. Deming never argued for permissiveness. He argued against blaming people for problems built into the system. True accountability comes after leaders have done their part: designing work so success is possible, and making expectations clear and achievable. [Performance-based pay] nourishes short-term performance, annihilates long-term planning, builds fear, demolishes teamwork, nourishes rivalry and politics.— W. Edwards Deming Actionable Takeaways Stepping back from merit pay does not mean stepping back from leadership. It means redirecting leadership toward the work itself. * Separate pay from judgment. Set base pay by role and market. Use clear skill progression for raises—certifications, cross‑training, demonstrated capability. If you share gains, do it at the system level so people improve together. * Design attendance into the process. Map the start of a shift the same way you would any critical operation. Remove friction, clarify handoffs, and make expectations visible. Measure patterns and causes, not personalities. * Be clear about accountability. When behavior remains willful after support and system fixes, address it directly and promptly. Don’t outsource leadership to a rating form. When pay decisions are predictable and fair, they stop dominating attention. That frees leaders to focus on what actually improves results—building capable people and reliable systems. All anyone asks for is a chance to work with pride.— W. Edwards Deming Closing The question was never whether people should be accountable. The question was whether pay and ratings are the right tools to achieve it. Deming argued that pay systems should be predictable and fair, writing that “the people of a group that form a system will all be subject to the company’s formula for raises in pay.” That idea runs counter to merit pay—but it aligns closely with how real systems actually work. At Sunrise Acres, removing merit pay didn’t weaken standards. It strengthened them. By focusing on system design instead of individual judgment, leaders created conditions where showing up on time was no longer a battle to be fought, but a normal part of professional work. When systems are designed well, people don’t need to be threatened into compliance. They can take pride in doing the work right—because the work finally works for them. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    9 min

  4. JAN 28

    Five-minute Deming: Awards & public recognition

    Public recognition is one of the most familiar tools leaders use to motivate people. It feels generous. It feels human. It feels like an easy way to say, “This matters here.” But recognition is never just a moment of appreciation. It is a signal that lingers. Over time, it teaches people what the organization truly values, what kind of work is safest to pursue, and what quietly carries risk. In interdependent work—where outcomes are shaped by systems, not individuals—that lesson compounds. Recognition keeps teaching long after the applause fades. Recognition is a system choice Most leaders don’t design awards because they enjoy competition. They do it to build energy, reinforce values, and show that effort is noticed. Public recognition feels like a low-cost, low-risk way to encourage performance. What often goes unexamined is how recognition behaves inside a system. When awards are scarce and visible, they begin to function like ranking—even when leaders explicitly reject that intent. People adapt quickly. They gravitate toward work that gets attention. They protect credit. They deprioritize work that is essential but less visible, such as mentoring, prevention, and improving methods. W. Edwards Deming urged leaders to look past intentions and examine effects. His concern was not appreciation itself, but the habit of confusing outcomes with merit in environments where outcomes are shaped largely by the system. When leaders reward results without studying the conditions that produced them, they unintentionally teach people to manage visibility instead of improving the work. To see how this dynamic unfolds—and how it can be redirected—consider what happened inside one professional services firm. When recognition becomes ranking Brightline Advisory is a mid-sized professional services firm whose work depends on collaboration, shared methods, and careful coordination across teams. After a demanding year marked by heavy workload and rising attrition, leadership introduced a monthly public recognition program called Bright Star. Each month, one individual would be publicly celebrated for strong performance. At first, the program landed exactly as intended. People appreciated the acknowledgment. Leaders felt they were reinforcing the right behaviors. Over time, however, the meaning of the recognition began to change—not because anyone altered the rules, but because the system itself was teaching a lesson. Sarah, who led one of the delivery groups, noticed the shift before it showed up in reports or metrics. She brought her concerns to Tom, a managing partner. “At first people seemed energized,” she said. “But after a while, something shifted—and not in a good way.” She wasn’t describing morale problems. She was describing how work was unfolding. Knowledge sharing slowed. Junior consultants hesitated to ask for help. Conversations about who would present results grew tense. Work that attracted attention felt safer than work that prevented future problems. Tom kept returning to intent. “We weren’t trying to rank anyone,” he said. “We just wanted to acknowledge great work.” “I know,” Sarah replied. “That’s what makes this tricky. It lifted up a few—and it changed what everyone else feels they have to do to be seen.” Nothing in Bright Star instructed people to compete. But recognition was scarce and highly visible. In an interdependent system, that combination quietly invites comparison. People adjust their behavior to the signal, not the slogan. Deming warned leaders about this pattern. “Abolish ranking and the merit system,” he wrote. In its place, he urged leaders to “manage the whole company as a system.” What follows from ranking is not better performance, but predictable distortion. Abolish ranking and the merit system.Manage the whole company as a system.— W. Edwards Deming As months passed, leaders began to see what Sarah had been describing. Certain projects drew disproportionate attention. Riskier work was avoided. Helping another team felt like a tradeoff against personal visibility. The conversation changed when leadership stopped debating whether Bright Star was motivating and asked a different question: What is this recognition teaching people to do? That question slowed things down. Instead of choosing winners more carefully, leaders began studying variation—project mix, timing, staffing, and handoffs. They began to see that Bright Star rewarded outcomes without improving the system that produced those outcomes. Only then did the solution emerge. The monthly award was retired. In its place, teams began sharing what they were learning: improvements to methods, prevention practices, and collaboration. Recognition shifted away from status and toward understanding how good work was produced. Over time, the effects became visible. Knowledge moved more freely. Cooperation increased. Results stabilized—not through competition or heroics, but through better system design. As Deming put it, leaders must “remove barriers that rob people … of their right to pride of workmanship.” Remove barriers that rob people … of their right to pride of workmanship.— W. Edwards Deming Where managers often get tripped up When we look at stories like this, it’s tempting to say the original recognition program was “wrong.” That framing isn’t very helpful. What usually happens is that we underestimate how powerful recognition really is. We treat it as encouragement rather than as system design. We assume people will hear praise as appreciation, not as instruction. In interdependent work, people are constantly scanning for signals about what is safe, what is valued, and what advances their standing. When recognition is scarce and public, it inevitably creates comparison—even if we never use the language of rank. We also tend to over-attribute results to individuals. When outcomes look good, we reward the visible contributor without asking how much of that outcome was shaped by project mix, timing, staffing, or client behavior. That makes recognition feel fair in the moment while quietly distorting behavior over time. None of this comes from bad intent. It comes from managing people instead of managing the system they work in. Deming’s reminder was simple and uncomfortable: most performance belongs to the system. Recognition that ignores that reality will eventually work against us. Actionable takeaways So how can leaders design recognition that strengthens the system instead of distorting it? * Map your recognition ecosystem. Examine all forms of recognition—formal and informal—and ask what behaviors they encourage, and what they crowd out. * Separate appreciation from ranking. Express gratitude freely, but avoid designs that create winners and losers in interdependent work. * Recognize methods, not just outcomes. Highlight prevention, mentoring, improved handoffs, and practices others can reuse. * Treat results as inputs for study. When outcomes are strong, ask “By what method?” and spread that learning without attaching status. * Design for pride of workmanship. Invest in systems that make good work the norm, not something that requires heroics to achieve. When recognition works this way, it becomes part of how the organization learns and improves. Closing Awards feel generous. Public praise feels motivating. That is exactly why leaders need to treat recognition as a system choice, not a gesture. In interdependent work, recognition can strengthen cooperation or quietly undermine it. When leaders align recognition with learning and system improvement, appreciation becomes more than applause—it becomes a foundation for lasting performance. Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    8 min

  5. JAN 21

    Five-minute Deming: The Deming chain reaction

    Most leaders feel pressure in the same places. Costs creep up. Capacity feels tight. Customers wait longer than they should. Staff are busy, sometimes exhausted, and still the results don’t seem to move. The natural response is familiar. Push productivity. Raise targets. Add oversight. Ask people to move faster. It feels responsible. It looks like leadership. And yet, very often, it quietly makes things worse. W. Edwards Deming offered a different way to think about improvement—one that runs counter to that instinct. In Out of the Crisis, he described what he called the chain reaction: a cause‑and‑effect sequence that begins not with cost or productivity, but with quality. Deming was clear that this was not a motivational idea. It was an explanation of how systems actually improve. If you improve quality, Deming said, “The result is a chain reaction—lower costs, better competitive position, happier people on the job, jobs, and more jobs.” Each outcome depends on the one before it. Miss the starting point, and the rest of the chain never really takes hold. The result [of improving quality] is a chain reaction—lower costs, better competitive position, happier people on the job, jobs, and more jobs.— W. Edwards Deming The logic behind the chain At first glance, Deming’s chain reaction looks almost too simple: improve quality, and good things follow. But Deming was not offering encouragement or aspiration. He was offering a way of thinking that depends on sequence. The chain reaction works only when its links unfold in the right order. It starts with quality. When quality improves, costs come down—not because someone demanded savings, but because waste leaves the system. Deming described the mechanism plainly: “Improvement of quality transfers waste of man‑hours and of machine‑time into the manufacture of good product and better service.” In practice, this shows up as less rework, fewer mistakes, and fewer delays and snags. Time that was once spent fixing problems is freed to do useful work. Improvement of quality transfers waste of man‑hours and of machine‑time into the manufacture of good product and better service.— W. Edwards Deming As that waste leaves, capacity returns. Only then does productivity improve—not because people are working harder, but because the system is able to work as intended. Over time, better quality and lower total cost translate into better value. Trust strengthens. Performance stabilizes. The organization can stay viable—or, in mission‑driven settings, continue to serve. Jobs become easier to protect, and growth becomes possible. The meaning of quality In many organizations, the word quality is narrowed to outputs, results, or compliance measures. Deming’s meaning was broader and explicitly managerial. He tied quality to meeting the needs of the customer, present and future, and placed responsibility squarely with leadership. Quality, in Deming’s sense, is not about effort. It is about how the work itself is designed. Operationally, quality shows up as reliability. The work arrives ready. Prerequisites are clear and present. Information is complete. Handoffs do not require rescue. The process is capable of producing a good result without looping back on itself. When those conditions are not met, the system creates rework—and that rework is where cost and capacity quietly disappear. Watching the chain reaction at work Riverview Health System’s specialty clinic had an eight-week wait for new appointments. Pressure was mounting. Access needed to improve, but headcount was frozen. Maria, the clinic operations director, saw the same pattern week after week. The clinic was full. The staff were busy. And the backlog wasn’t moving. “Everyone is working flat out,” she said during a Monday review. “But the waiting list isn’t changing.” Instead of asking people to work harder, Maria asked a different question: where is the system creating rework? She and the medical director agreed to look more closely. “Let’s stop guessing,” he said. “Let’s count how often work comes back.” For two days, the team tracked repeat work. They categorized callbacks, delays, and corrections tied to referral defects, missing prerequisites, authorization issues, unclear orders, and documentation rework. When they reviewed the results, the answer was unmistakable. “Nearly a third of our calls aren’t new demand,” Maria said quietly. “They’re cleanup.” That made the starting point clear. Quality had to be addressed at the entry point. They focused on new rheumatology referrals. The core problem wasn’t clinical judgment. It was incomplete information. Intake staff chased labs. Nurses re-triaged. Visits ran late because prerequisites were missing. “If we fixed this upstream,” the medical director observed, “the whole day would change.” The team redesigned the referral process. Required fields were clarified. Prerequisites were explicit. If something was missing, the visit wasn’t scheduled; a clear request went back immediately. Within weeks, the day felt different. “The phones are quieter,” one scheduler noted. “We’re not constantly fixing things.” Phone calls dropped. Reschedules declined. Visits started on time more often. Costs fell because rework fell. As correction work faded, capacity returned. With the same staffing level, the clinic completed more work that stayed complete. Access improved. The waiting list began to shrink. Productivity improved—not because people were pushed harder, but because failure demand no longer consumed capacity. Over time, reliability strengthened trust with referring practices and patients. Performance stabilized. Leaders could plan instead of firefighting. Jobs were protected not through cuts, but through predictability. The improvement didn’t come from working harder or managing tighter. It came from choosing the right starting point—and then letting the rest of the chain do its work. Once quality was addressed upstream, the system began to change on its own. Rework fell, capacity returned, and productivity followed without being forced. What looked at first like a stubborn access problem turned out to be a design problem, and fixing that design made improvement both durable and calm. Putting the chain reaction to work Under pressure, it’s tempting to start the chain in the middle. Lower costs become mandates. Productivity becomes a target. But cost and productivity are outcomes of a system. When leaders pressure outcomes without improving the system that produces them, rework grows, delays lengthen, and capacity shrinks. This is why Deming insisted on quality as the starting point. Without it, the later links have nothing solid to stand on. The chain reaction becomes practical when leaders shift where they put their attention. Rework is a good place to begin. Treated as noise, it’s frustrating. Treated as data, it’s revealing. Rework shows where the system isn’t capable and where quality is breaking down upstream. That perspective reshapes how quality is defined. Instead of abstract goals, quality becomes observable. What does “ready” actually mean at the entry point? What conditions must be present so work flows forward instead of circling back? With those questions in view, improvement naturally moves upstream. Ambiguity is reduced. Prerequisites stabilize. Handoffs become clearer. Downstream teams no longer have to compensate for what the system failed to provide. Progress then appears in a predictable order. Callbacks decline. Reschedules ease. Overtime falls. These are early signs that cost is coming down because rework is leaving the system. As capacity returns, productivity follows. Seen this way, the chain reaction isn’t a technique. It’s a discipline of starting points. As Deming warned, “A bad system will beat a good person every time.” A bad system will beat a good person every time.— W. Edwards Deming Actionable takeaways These are not tactics to apply all at once. They are starting points—ways to begin aligning daily management decisions with the logic of the chain reaction. * Measure rework, not effort. For a short window—one or two days—track how often work loops back: clarifications, missing inputs, avoidable exceptions, reschedules, callbacks, and other “cleanup.” Treat the count as a map of where the system is failing, not a scorecard on people. * Define “quality” as entry-point reliability. Make “ready” explicit: required information, prerequisites, and clear handoffs. Build these conditions into the process (templates, required fields, checklists, upstream agreements) so downstream teams don’t have to rescue the work. * Follow the chain in order. Look first for fewer snags—less rework, fewer interruptions, fewer delays. Then watch capacity return. Only after that should you expect productivity and results to improve. Resist the temptation to start in the middle. Taken together, these actions help leaders stay anchored to the first link. They keep attention where improvement actually begins, even when pressure pushes hard in the opposite direction. Start the chain reaction Deming’s chain reaction isn’t about doing more. It’s about starting in the right place. When leaders improve quality, they remove the causes of rework and delay that quietly drain their systems. Capacity returns. Productivity improves as a consequence, not a demand. Stability becomes possible. Once this way of thinking takes hold, it’s hard to unsee. Cost and productivity stop looking like levers to pull and start looking like outcomes to be earned. If improvement is the aim, hold the line on the first link. Quality first. Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bon

    8 min

  6. JAN 14

    Five-minute Deming: Drive out fear

    Fear is expensive. It doesn’t appear on financial statements, but it shows up everywhere else—late reporting, hidden problems, padded numbers, quiet compliance, and people doing just enough to stay out of trouble. W. Edwards Deming captured the effect in a single line: “Fear invites wrong figures.” When fear is present, organizations don’t see reality clearly, because reality feels unsafe to report. Many leaders treat fear as a cultural or interpersonal issue. Deming did not. In Out of the Crisis, he was explicit: “Drive out fear, so that everyone may work effectively for the company.” He described fear as a management problem—created, reinforced, and sustained by the way the system is designed. Until fear is addressed at the system level, improvement efforts may stall, no matter how capable or well‑intentioned the people involved may be. Drive out fear, so that everyone may work effectively for the company.— W. Edwards Deming Fear is rational—and systemic People don’t hide problems because they lack integrity. They hide problems because the system has taught them what happens when they speak up. Fear is rational. When the cost of surfacing a problem is higher than the cost of hiding it, people adapt. They delay. They soften the message. They adjust the numbers. Over time, the organization becomes exactly as honest as the system allows it to be. This is why Deming warned that many of the most important figures managers need are unknown or unknowable. When fear governs behavior, the data itself becomes unreliable—not because people are dishonest, but because honesty feels dangerous. A familiar pattern Consider an organization running behind schedule. Elena, a frontline operator, notices a subtle change in how a process is behaving. Nothing dramatic. Output is still within spec. But something feels off. Stopping the process might turn out to be unnecessary—and attract criticism. Letting it run might result in scrap or rework later. Either way, the risk feels personal. “If I stop it and nothing’s wrong, I’ll get blamed,” she thinks. “If I don’t stop it and it fails, I’ll get blamed worse.” So the process keeps running. Hours later, failure occurs. Scrap spikes. Downtime stretches longer than it would have if the issue had been addressed earlier. Later, James, a senior leader, asks why no one spoke up sooner. “Why didn’t we hear about this earlier?” he asks. The answer is predictable: people have been burned before. This isn’t a failure of motivation or training. It’s a predictable outcome of the system: people do what keeps them safe. Deming warned that fear suppresses information long before it shows up as failure, because people learn to survive within the system they are given. What changes when fear is removed Now imagine a different response. James changes the way he responds when problems surface. Instead of asking who made the wrong call, James asks what signals were present and how the system made responding risky. “Where did the first signal show up,” James asks, “and what did we make risky about acting on it?” They make it explicit, then demonstrate through their actions, that surfacing problems early will not be punished. The next time a similar signal appears, the process stops sooner. The issue is confirmed. Downtime is brief. Loss is limited. Nothing changed about the equipment. Nothing changed about the people. What changed was the risk calculation in their heads. When the system punished early signals, those signals disappeared. When the system protected early signals, learning sped up. As Deming cautioned, without trust, people cannot work together to improve the system, no matter how skilled they are. Fear as a competitive issue This is where fear stops being a cultural concern and becomes a strategic one. Organizations that surface problems early learn faster than organizations that hide them. Over time, speed of learning—not size, not technology, not even experience—becomes the real competitive advantage. Teams that operate without fear adapt faster, recover sooner, and avoid repeating the same mistakes. That advantage compounds quietly but relentlessly, because competitors can copy tools and processes, but they struggle to copy systems that consistently tell the truth. Here’s how you can eliminate fear Driving out fear does not require grand programs or slogans. It requires consistent management behavior, especially in moments when problems surface. * Establish a non‑punitive escalation rule.Make it explicit that surfacing a problem early will never be punished. Write it down. Repeat it often. Most importantly, enforce it through your reactions when bad news appears. * Change the first question leaders ask.Replace “Who did this?” with “What in the system made this likely?” The first sentence out of a leader’s mouth teaches everyone what is safe. * Use a simple learning review after problems occur.After any defect, delay, or stoppage, ask what signal appeared, what decision was made, and what the system made easy or hard in that moment. A simple daily learning review captures what abnormality was observed, when the earliest signal appeared, what risk people perceived at the time, and what will be changed so the right action feels safe next time. The point of driving out fear Fear doesn’t disappear because leaders say the right words. It disappears when people see—again and again—that telling the truth is safer than hiding it. In every organization, improvement begins as a small signal: a question, a hesitation, a quiet sense that something isn’t quite right. When fear is present, those signals are swallowed. When fear is removed, they become the starting point for learning. Driving out fear isn’t about being kind or permissive. It’s about creating the conditions where people can contribute what they actually know, not just what feels safe to say. It’s about shifting energy away from self‑protection and toward shared purpose. Fear is a management choice, whether intentional or not—and so is its absence. Deming was clear that fear undermines pride of workmanship, because people cannot take pride in work they are afraid to speak honestly about. When fear governs, people brace themselves and problems arrive late. When fear is driven out, people speak sooner, learn faster, and take pride in getting things right. That is the point of driving out fear. It’s the moment when people stop bracing themselves and start bringing their whole selves to the work—and when improvement stops being forced and starts becoming something people believe in. All anyone asks for is a chance to work with pride.— W. Edwards Deming Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    7 min

  7. JAN 7

    Five-minute Deming: The danger of sub-optimization

    Every organization—whether a small consultancy or a global enterprise—is a web of interdependent parts. Yet most are managed as if each department, team, or individual were a separate machine to be tuned in isolation. Targets are set, bonuses awarded, and dashboards celebrated—all without asking how those local victories affect the system as a whole. W. Edwards Deming warned that this “sub-optimization” is one of management’s most costly blind spots: the parts can perform beautifully while the enterprise itself underperforms. To see what this looks like in practice—and how to escape it—consider the story of a professional services firm that learned the hard way that optimizing individual parts can quietly destroy the whole. When every team wins—and the company loses At a growing professional services firm—busy, modern, and full of smart people—something didn’t add up. Each department was celebrating its own success. Operations had reduced delivery time by 25 percent, and the sales team had exceeded its revenue targets. On paper, things looked great. Yet, customers were increasingly dissatisfied. Complaints about rushed projects, inconsistent service, and miscommunication were rising. Internally, tension brewed between departments. The operations manager, Marcus, pointed to his metrics. “We’ve hit every efficiency target,” he said. The client services lead, Lila, countered that customer satisfaction was slipping. The sales director, Tom, defended his team: “Our job is to bring in business. Maybe operations needs to adjust.” Each spoke with conviction, each confident they were doing their job well. But as Deming explained, the performance of any part or person in an organization can only be understood in terms of its contribution to the system’s overall aim. In other words, when departments pursue their own metrics without understanding how their work affects the rest of the organization, they may be “winning” locally while the company loses as a whole. Deming warned that “Left to themselves, components become selfish, competitive, independent profit centers, and thus destroy the system.” He defined a system as “a network of interdependent components that work together to accomplish the aim of the system.” Each part of an organization—sales, operations, finance, customer support—relies on the others. Success requires harmony, not competition. Left to themselves, components become selfish, competitive, independent profit centers, and thus destroy the system.— W. Edwards Deming Seeing the process to improve it At the firm, the realization came slowly. The leadership team began to map how work actually flowed from one department to another. Sales commitments became project delivery constraints. Delivery schedules shaped customer satisfaction. Customer feedback influenced sales renewals. For the first time, everyone could see that their work didn’t exist in isolation. Deming once noted, “If people do not see the process, they cannot improve it.” If people do not see the process, they cannot improve it. — W. Edwards Deming Once the team visualized their interdependencies, conversations shifted from blame to curiosity. They began asking, “What is the aim of our entire system?” rather than “How can my team hit its number?” Together, they agreed that the true aim was not merely to increase short-term output or revenue, but to deliver reliable, high-quality service that built long-term relationships. Transforming through cooperation With this shared aim, they adjusted their incentives and measures. Sales began setting expectations based on delivery capacity, not just closing speed. Operations shifted from rushing projects to focusing on consistency and quality. Client services joined early in the process to anticipate customer needs before issues arose. Six months later, the firm’s revenue per client had grown by nearly twenty percent, but the deeper transformation was cultural. Complaints dropped sharply. Referrals increased. Employees reported less frustration and more pride in their work. As Marcus put it, “We didn’t work harder—we just stopped working against each other.” Managing the system, not the people Deming famously said, “A system must be managed. It will not manage itself.” Systems do not improve through pressure or exhortation, but through understanding and design. When leaders focus only on optimizing subsystems—each department, team, or metric—they unintentionally sub-optimize the whole. True improvement requires managing interdependence, not independence. The lesson is timeless and universal: when a business, school, or agency learns to see itself as one system with a shared aim, performance improves naturally. The parts no longer compete; they collaborate. And the result is not just better numbers, but greater stability, learning, and joy in work. Actionable Takeaways * Draw the system. Create a simple flow diagram showing how work moves across departments. Clarity reveals waste, rework, and misalignment. * Redefine success. Evaluate each team’s performance by how it contributes to the organization’s overall aim, not by isolated metrics. * Remove local targets that conflict with the system. If a goal drives one group to optimize at the expense of others, it’s the wrong goal. * Foster cooperation over competition. Encourage departments to solve problems together rather than negotiate boundaries. * Lead with purpose. The role of management is to optimize the whole system—helping every component work together for customers, employees, and the organization’s future. When an organization learns to see itself as one system, improvement becomes continuous and sustainable. That, Deming would remind us, is not just better management—it’s a competitive advantage. A system must be managed. It will not manage itself. — W. Edwards Deming Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    5 min

  8. JAN 1

    Five-minute Deming: Why improve if everything's great?

    On paper, the year looked exceptional. Demand was strong. The numbers were up and to the right. Everyone was happy. Inside the organization, the mood was confident, even relaxed. From the outside, it looked like success. That is exactly the moment W. Edwards Deming warned leaders about. He once observed, “It is easy to manage a business in an expanding market, and easy to suppose that economic conditions can only grow better and better.” His point was not that success is a problem, but that success can quietly disguise weakness. It is easy to manage a business in an expanding market, and easy to suppose that economic conditions can only grow better and better.— W. Edwards Deming A very good year To see what Deming meant, consider a nonprofit serving families through food assistance and job‑readiness programs. It had been a banner year. A new corporate partnership boosted funding. A positive media story brought in volunteers. Enrollment climbed. The board was pleased. Staff morale was high. At a routine leadership meeting, the updates sounded exactly like you would expect in a good year. Marcus, who oversaw operations, went first. “We’re serving more families than ever,” he said. “The handoffs are smoother, the wait is shorter, and volunteers are showing up.” Elena, the executive director, added the development update. “Donors are leaning in,” she said. “We’re ahead of plan, and the support feels steady—for now.” All of it was true. And yet Elena felt a quiet tension she couldn’t shake. It wasn’t fear. It wasn’t urgency. It was a question that didn’t quite fit the celebratory tone of the room: Are we improving… or are we just busy? Deming would have recognized that moment instantly. When conditions are favorable, results can improve even if the underlying system stays weak. A strong economy, a generous donor cycle, or a surge of goodwill can lift outcomes without strengthening capability at all. The tailwind trap Strong results tell leaders what has happened. They do not explain why it happened, or whether it will happen again. In an expanding environment, ordinary management can look exceptional. Leaders can easily mistake momentum for capability and luck for skill. The danger is not celebrating success—it is assuming success proves the system is sound. Deming warned that decline rarely announces itself. It arrives like dusk, so gradually that people don’t notice it happening. One day the numbers soften. Then variation increases. Then firefighting becomes normal. By the time leaders recognize the pattern, the room to maneuver has largely disappeared. Elena sensed that risk, even though nothing appeared broken. Instead of asking for bigger goals or tighter targets, she asked a different kind of question. “If things got tighter next year,” she said, “if funding dipped or demand spiked, what would we wish we’d strengthened while we still had room to breathe?” The room went quiet—not because the question was threatening, but because it was unfamiliar. Marcus answered first. “Cross-training,” he said after a pause. “Right now, a few people are holding too many threads.” That one sentence revealed more about the system than any dashboard had. When performance depends heavily on a handful of individuals, results can look excellent right up until someone gets sick, leaves, or burns out. At that point, the organization discovers it has not built a system; it has built a reliance. Elena heard it clearly. This wasn’t a staffing issue. It was a design issue. From outcomes to capability Deming taught that an organization doing well is in the best position—and has the greatest obligation—to improve. When survival pressure is low, leaders have something rare: the capacity to learn. In a crisis, organizations default to urgency. Controls tighten. Pressure increases. Short‑term output becomes the priority. Sometimes that response is unavoidable. But Deming warned that improvement driven by pressure usually optimizes for speed, not learning, and leaves the system weaker in the long run. Good times create a different opportunity. They allow leaders to shift attention away from celebrating outcomes and toward strengthening capability. A company that is doing well is in an excellent position to improve management, product, and service, and moreover has the greatest obligation to improve. A company that is on the rocks can only think of survival short-term.— W. Edwards Deming Up to this point, Elena and Marcus had been talking about results. The question now was how to see the system underneath those results. Elena wanted to know whether the organization understood what actually made the work hold together—and whether it could keep holding together when conditions shifted. A small experiment Rather than launching a major initiative, Elena proposed a modest experiment. For several weeks, the team would track a few measures of capability—not outcomes. They chose three: the time from first contact to receiving help, the rate of rework caused by missing or unclear information, and the time it took to onboard a new volunteer. Marcus frowned slightly. “Those numbers are going to move around week to week.” “Exactly,” Elena said. “If it’s normal noise, we won’t chase it. If there’s a real cause, we’ll go fix the cause.” That distinction—between a normal wobble and a meaningful change—is central to Deming’s thinking. Most organizations do the opposite. A rough week triggers pressure. A complaint triggers correction of people. A delay triggers urgency. Deming warned that overreacting to everyday variation can make systems worse, not better. Within weeks, patterns began to emerge. Delays clustered on Mondays. Rework spiked after a partner changed a form. Volunteer onboarding slowed dramatically whenever one staff member was out. None of this showed up in the headline numbers. Funding was still strong. Participation was still high. But the system was quietly revealing where it was brittle. Instead of setting new targets, the team improved the system. They cross‑trained a role that had become a bottleneck. They standardized intake so rework didn’t depend on who answered the phone. They simplified onboarding so volunteers weren’t stranded when one person was unavailable. The changes were unremarkable on the surface, but their effect was profound. The work became more predictable. Learning accelerated. Capacity grew. The organization became less dependent on heroics and more resilient by design. Why Deming matters most in good times Deming once said that a healthy organization is in the best position to improve, and has the greatest obligation to do so. The nonprofit’s experience made that idea tangible: improvement was not driven by fear or crisis, but by foresight. This is why Deming matters most when things are going well. Good times provide the margin to learn, to see the system clearly, and to strengthen it before conditions change. In any industry, organizations compete not just for customers or funding, but for resilience. They compete against complacency, against the belief that what worked this year will work next year, and against the slow drift of brittleness that success can conceal. Actionable takeaways If you want to use good times wisely, start small and keep it practical. Here are five moves that translate Deming’s insight into day-to-day leadership. * Pick one or two capability measures. Choose measures that reveal how strong the system is (flow, rework, onboarding, lead time), not just outcomes. * Review enough data to see patterns. Look at performance over time so you can distinguish a normal week-to-week wobble from a meaningful change. * Ask the “tightened conditions” question regularly. What would you wish you had strengthened if funding dipped, demand spiked, or staffing changed? * Improve the system, not the slogans. Crosstrain bottlenecks, standardize handoffs, and simplify steps where the process is brittle. * Treat improvement as stewardship. Use favorable conditions not to relax, but to strengthen the system that carries the aim forward. Taken together, these steps turn momentum into resilience—so you’re not relying on good conditions to keep getting good results. A closing thought Good times are a gift. They are also a test. They test whether leaders can resist the comfort of applause and invest instead in capability. They test whether organizations can strengthen their systems when they do not have to, so they can endure when they must. Deming’s message is not to be afraid. It is to be wise. If things are going well today, you have something precious: room to learn. Use it. It is easy to date an earthquake, but not a decline.— W. Edwards Deming Thanks for reading The Knowledge System! Subscribe for free to receive new posts and support my work. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit posts.knowledgesystem.com

    6 min
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The Knowledge System Podcast explores how leaders can use systems thinking to create lasting organizational improvement. It translates the ideas of W. Edwards Deming and other thought-leaders into practical strategies for building smarter, more effective systems. posts.knowledgesystem.com

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