Collect at least 5 measurements before improving…

When This Fires

• Before attempting to improve any workflow — ensure you have enough data to distinguish variation types
• When a single bad execution makes you want to redesign the whole process
• When a workflow's performance seems inconsistent and you're not sure if that's normal
• Complements Measure actual elapsed time over 3-4 cycles before… (measure before optimizing) with the specific statistical reasoning for the measurement threshold

Common Failure Mode

Reacting to single data points: one bad workflow execution triggers a redesign. This is Deming's "tampering" — adjusting a stable process in response to common-cause variation, which actually increases variation rather than reducing it. The single bad execution may have been well within the process's normal range. Without baseline measurements, you can't know.

The Protocol

(1) Before improving any workflow, collect at least 5 measurements of its key metric (elapsed time, error rate, output quality). (2) Calculate the range: what's the highest and lowest measurement? This is your process's natural variation band. (3) For future executions, ask: "Is this measurement inside or outside the natural range?" Inside → common-cause variation. Don't react to individual data points; improve the system if the whole range is unacceptable. Outside → special-cause variation. Investigate what specific event caused this outlier and remove it. (4) Only redesign the workflow when the entire common-cause range is unacceptable — meaning even the best executions don't meet your standard. (5) After any improvement, collect 5 new measurements to establish the new baseline. Don't assume the improvement worked — verify it statistically.