CEO and Co-founder Of Goldratt Research Labs Decision Scientist, Theory of Constraints Expert, Author, App Developer, Investor, Social Entrepreneur
❗ Common Misconceptions About Theory of Constraints ... and What to Do Instead. After decades of applying and teaching TOC, I’ve noticed some recurring misconceptions that often lead organizations down the wrong path. ❌ Misconception #1: “Everything that’s a problem is a constraint.” In casual language, we tend to label anything problematic or limiting as a “constraint.” But in Dr. Goldratt’s original explanation of TOC he defined a constraint as a RESOURCE that is: a) needed to achieve the system goal, and b) you don’t have enough of it to achieve that goal. It is NOT a policy, or behaviour or metric. These can cause resource constraints. They are the problems we must solve to have enough of each resource - whether its demand, internal capacity, supply, cash, or management attention And If we ignore any resource constraints when making commitments, we create a chaotic system with interactive constraints: shifting bottlenecks, unreliable commitments, and confusion about where to focus. ✅ Action Step: If you believe a resource is the ONE constraint to focus on next, test it. Find a way to better exploit (avoid wasting) or elevate it. If the system produces more goal units, it was the constraint. If not, it wasn’t. Then repeat — this is the essence of TOC's 5 Focusing Steps. 1. Identify the constraint(s), 2. Decide how to Exploit and not waste it, 3. Subordinate everything else (change any conflicting policy, metric or behaviour) 4. Elevate it 5. Go back to Step 1 — don’t let inertia cause a constraint. 🧠 Game-changer: Digital Twins are the only reliable way to test constraint hypotheses fast, low-cost, and low-risk under real-world conditions. Simulate improvements before committing scarce resources. ❌ Misconception #2: “Balancing capacity is to most efficient way to meet demand.” This trap appears efficient — e.g., setting all processes to the same output rate (10 units/hr) or same Takt-Time (6 min). But it’s a mirage. ⚠️ Reality: Balanced systems are fragile under real-world variability in demand and supply. Yes, we should reduce variability where possible — but we also have to protect the system against what remains with time, inventory, capacity and/or cash buffers. 🎯 TOC Insight: Is your constraint moving all the time? If yes, you have a chaotic system. ✅ Action Step: You need a deliberately unbalanced system with a “V-shaped" capacity profile: 1. Decide where you want the constraint (the drum)—beginning, middle, or end. 2. Use that resource’s capacity to make reliable commitments — don’t overcommit. 3. Build protective capacity before/after it, to prevent its starvation or blockage. Final Thought: 💡 The goal of TOC is NOT to increase Throughput — it’s to increase flow with the lowest cost and investment, so your system can achieve more and more of its goal. I’d love to hear what other misconceptions you've see or questions you might have about TOC. #TheoryOfConstraints #Goldratt #DigitalTwins