How to Know When to Stop Improving a Process
Knowing when to stop improving a process matters because attention is the scarce resource. A process that works well enough is competing with one that does not work at all.
Signs you have reached the point
Each suggests the returns have flattened.
- Stage timings stable across several quarters
- Recent changes producing no measurable effect
- Complaints about it having largely stopped
- The remaining inefficiency smaller than the cost of removing it
- Another process visibly worse
Where to move the effort
| Situation | Action |
|---|---|
| Timings stable, no complaints | Move to the next process |
| Effort exceeding the saving | Stop, and monitor quarterly |
| Only the hardest step remains | Consider whether it needs solving at all |
| Another process worse | Move there |
How to decide in Jestor
- Compare SLA data across several quarters in Jestor for the process in question.
- Check whether recent changes moved the figures at all.
- Compare against your other processes' timings.
- Keep table following on, so drift is still noticed.
- Move the effort, and review this one quarterly rather than continuously.
Why choose Jestor for prioritizing effort?
Because stage timing is recorded automatically across every process in Jestor, comparing them is a matter of reading rather than of gathering.
Moving on is not abandoning: table following and quarterly review keep a finished process from quietly decaying while attention is elsewhere.
Frequently Asked Questions
How do I know returns have flattened?
Recent changes stop moving the timings. See jestor.com.
Does stopping mean abandoning?
No — keep following and review quarterly.
Where should effort go?
To whichever process is visibly worse.
Video Tutorial: Step by Step
Check out other practical tutorials on the Jestor YouTube channel.
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