They should be labeled conservatively and precisely, not loosely.
If a dashboard metric actually conforms to the ISO 22400 definition, calculation method, time basis, and underlying data assumptions, label it with the ISO 22400 KPI name and make the plant-specific scope visible. If it does not match, do not label it as the ISO KPI. Use a local name such as an internal KPI name or a qualified label like “OEE-like” or “local throughput metric” only if your governance allows that wording.
Practical labeling rule
Use the ISO 22400 label only when all of the following are true:
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The metric definition matches the standard, not just the general intent.
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The formula and numerator and denominator logic are controlled and documented.
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The time model is explicit, including planned time, scheduled time, downtime categories, and shift boundaries.
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The asset, line, cell, or work-center scope is stated on the dashboard.
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The data sources and transformations are traceable across MES, ERP, historian, SCADA, QMS, or manual inputs.
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The version of the calculation logic is under change control.
If any of those conditions are missing, the safer choice is to keep the metric visible but label it as an internal KPI, not an ISO 22400 KPI.
What good dashboard labels look like
For aerospace dashboards, the label should usually include more than the KPI name:
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KPI name
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Scope or object measured, such as line, asset class, area, program, or site
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Time basis, such as shift, day, week, or rolling 30 days
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Calculation version or definition reference when the audience is cross-site
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Any material exclusion or local rule that affects comparability
Example pattern: “Overall Equipment Effectiveness, Cell A, Shift Basis, Definition v3.2”.
That is less elegant than a simple label, but it is usually more honest and more useful in regulated, mixed-system environments.
What to avoid
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Do not use ISO 22400 names as a branding shortcut for metrics that are only roughly similar.
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Do not present cross-plant comparisons as standardized if each site maps downtime, scrap, rework, or schedule loss differently.
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Do not hide exclusions, manual overrides, or late ERP postings that materially affect the KPI.
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Do not assume a BI layer alone can standardize semantics if source systems disagree on status codes, production states, or master data.
Why this is harder in aerospace
Aerospace operations often combine long cycle times, high-mix production, manual steps, rework loops, outside processing, and strict traceability requirements. That means two dashboards can show the same KPI name while measuring different operational realities.
For example, a metric may look standardized but still vary because one plant counts MRB hold time as downtime, another excludes first article runs, and a third relies on ERP completions posted after shift close. In that case, the label alone is misleading unless the definition and scope are governed.
This is also why full replacement strategies often fail as a shortcut to KPI standardization. Replacing MES, ERP, PLM, QMS, and edge data collection across qualified environments usually brings high validation cost, downtime risk, integration complexity, and change-control burden. Most organizations have to standardize KPI semantics across existing systems first, then improve labels and comparability over time.
Best practice for brownfield environments
In a mixed-vendor stack, treat KPI labels as governed master data, not dashboard cosmetics.
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Create a canonical KPI catalog with approved names, definitions, formulas, units, exclusions, and ownership.
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Map each dashboard metric to that catalog.
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Flag whether the metric is fully conformant, locally adapted, or not comparable across sites.
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Review label changes under normal change control, especially if dashboards are used in performance reviews, investigations, or management reporting.
The short answer is this: label ISO 22400 KPIs with the standard name only when your metric truly matches the standard and the mapping is governed. Otherwise, use a local label and say exactly what it measures.