The ISO 22400 KPIs that best support work-order visibility are the ones that connect planned work, actual execution, resource status, output quantity, and quality results. In practice, that usually means KPIs such as production order progress, schedule adherence, throughput rate, production lead time, equipment availability, utilization, setup-related measures, quality ratio, scrap ratio, and rework ratio. ISO 22400 helps standardize KPI definitions, but it does not by itself create reliable work-order visibility.
In many plants, especially brownfield regulated environments, the work order originates in ERP, the routing and execution details may live in MES, product definition may come from PLM, and defects or dispositions may be managed in QMS. The KPI is only useful if those systems share consistent order, operation, part, revision, resource, and timestamp data.
| KPI or KPI family | How it supports work-order visibility |
|---|---|
| Production order progress | Shows how much of the order or operation has been completed against the planned quantity or routing sequence. |
| Schedule adherence | Shows whether the order, operation, or resource is tracking to the planned start, finish, or due date. |
| Throughput rate | Shows actual output over time and helps identify whether the order is moving at the expected pace. |
| Production lead time or cycle-time-related KPIs | Shows elapsed time through release, execution, queue, inspection, rework, and completion steps, depending on how the site captures events. |
| Queue time, wait time, or delay-related measures | Helps distinguish active processing from waiting for material, inspection, tooling, engineering, quality disposition, or capacity. |
| Availability, allocation ratio, utilization, and OEE-related measures | Show whether equipment or labor constraints are affecting order execution. These do not explain order status unless they are linked to the specific operation or resource used by the order. |
| Setup ratio or setup-time-related measures | Shows whether changeover or preparation time is consuming planned capacity and delaying order progress. |
| Quality ratio, scrap ratio, rework ratio, and yield-related measures | Explain the gap between produced quantity and acceptable completed quantity. This is essential where inspection, MRB, or rework can block order closure. |
ISO 22400 defines KPI concepts and formulas; it is not a transaction model for work orders. A dashboard can claim to show ISO-aligned KPIs and still provide poor visibility if confirmations are late, manual, incomplete, or disconnected from the actual routing.
The most common failure mode is treating ERP order status as execution truth. ERP may know that an order is released, partially confirmed, or closed, but it often does not know whether an operation is physically waiting at a machine, blocked by inspection, short material, under quality hold, or being reworked unless MES, QMS, maintenance, and material systems feed those events back in a controlled way.
For these KPIs to support credible work-order visibility, the site usually needs:
Full system replacement is usually unrealistic as a first response. In aerospace-grade and similarly regulated operations, replacement can create qualification burden, validation cost, downtime risk, integration complexity, and traceability disruption. A more practical approach is often to map the critical work-order states first, identify which system owns each event, and then align ISO 22400 KPI definitions to the data that can be captured reliably.
The useful question is not only “Which ISO 22400 KPI should we use?” It is also “Which order events can we trust, at what latency, from which system, under change control?” Without that answer, the KPI may look standardized but still be operationally misleading.
Whether you're managing 1 site or 100, Connect 981 adapts to your environment and scales with your needs—without the complexity of traditional systems.
Whether you're managing 1 site or 100, C-981 adapts to your environment and scales with your needs—without the complexity of traditional systems.
