Protocol
Recheck the bottleneck after improvement
Removing one constraint usually reveals another.
When it fits
- When an improvement succeeds and the team assumes the same constraint remains forever.
When to avoid it
- Queueing equations have specific assumptions. Use them for directional reasoning and measurement design, not as exact forecasts for arbitrary multi-stage knowledge work.
Why it matters
After throughput changes, repeat flow measurement and locate the new accumulation or starvation point before applying the old optimization again.
Steps
- Confirm throughput changed.
- Measure new WIP and waits.
- Locate the new limiting stage.
- Retire controls that only served the old constraint.
An example
Automating validation shifts the constraint from data checks to final business approval; more validation optimization no longer improves end-to-end flow.
Check your result
The next improvement target is based on current flow evidence, not yesterday's bottleneck.
Keep this limit in mind
- Queueing equations have specific assumptions. Use them for directional reasoning and measurement design, not as exact forecasts for arbitrary multi-stage knowledge work.
Connected ideas
Useful withDecompose around likely change, not the org chart
Evidence and sources
Provides context
Kingman's heavy-traffic result underlies a queueing approximation in which waiting increases sharply with utilization and with variability in arrivals and service.
It is a single-server heavy-traffic approximation and should be used as directional intuition, not as an exact prediction for arbitrary multi-stage work.
The Single Server Queue in Heavy Traffic · Research note metadata and established heavy-traffic formulation