thinking-theory-of-constraints

1# Theory of Constraints
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3A throughput-limited system has one binding constraint. Improve only that constraint; local optimization of non-constraints wastes effort and often grows WIP.
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5## When to Use
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7- Latency or throughput goal where one stage dominates time or rate.
8- Work piles up before one stage; downstream idles.
9- Adding capacity/workers elsewhere does not raise end-to-end output.
10- Need ordered plan: exploit cheaply before spending to elevate.
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12## When NOT to Use
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14- Load is spread; no stage dominates—use systems for interactions.
15- Problem is correctness/fault, not flow rate—debug the fault.
16- Bottleneck hops every run due to coupling/contention without a stable stage—systems or concurrency design, not five focusing steps.
17- Constraint already known and a cheap fix is ready—apply it without ceremony.
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19## Procedure
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211. **Define the flow and goal.** Name the unit of work (request, job, PR, record) and the metric that matters (end-to-end rate or latency).
222. **Identify the constraint with evidence.** Compare stages on utilization, queue/wait, and throughput. Constraint signals: near-100% use, longest queue, lowest stage rate, work piles here, more input does not raise system output. Prefer measured rates over opinions. If two candidates tie, pick the one whose improvement would raise system throughput first.
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