Measurement Layer

CEO question

How will we know whether the redesigned system is behaving as intended?

Scenario context

The key measure is not average lead time.

The key measure is the percentage of orders quoted and delivered within the customer’s accepted tolerance window.

This matters because the market is no longer rewarding average delivery performance. It is rewarding suppliers who can quote, deliver and repeat performance predictably within tolerance.

Benefit KPI

Lead-time reliability within customer tolerance.

Supporting confirmation measures include delivery performance and promise-date performance.

Assumption sensors

The assumption sensors test whether the design conditions required for the benefit are still holding.

These include:

• release rate versus drum rate

• time-based buffer penetration patterns

• WIP accumulation upstream of the constraint

• queue dispersion downstream of the constraint

• schedule break-in frequency

• frequency of management intervention required to stabilise flow

Tactical signals

Tactical signals show how the system is coping under operating pressure.

These include:

• frequency of expediting

• clustering of expediting

• compensating resource patterns

• overtime patterns

• manual schedule intervention

Measurement logic

KPIs confirm whether the benefit has appeared.

Assumption sensors test whether the conditions required for the benefit still hold.

Tactical signals reveal where the system is compensating before benefit loss becomes visible.

What this layer proves

This layer confirms that measurement is not being used as reporting after the fact.

Measurement becomes the control system that allows the organisation to sense whether the design remains sufficient as operating conditions change.

Verified output

A measurement architecture that connects benefit KPIs, assumption sensors and tactical signals to the DBR release-control design.