Level 4: Quantified
Data-driven — decisions backed by trends.
Your quality system is data-driven and demonstrably in control. The path to Level 5 runs through predictive analytics and a fully closed-loop continuous improvement culture.
What a level is not
The five levels are SPEQ’s progression, labelled synthesis. They are not the FDA’s Quality Management Maturity rating scale, no regulator assigns them, and reaching one is not a compliance status.
A quality system rarely sits at one level everywhere. This is the character of each of the twelve GxP domains when it is operating at Level 4 — and the move that lifts it to the next.
Change and document performance is measured and trended; management review acts on the metrics.
TO ADVANCE →Close the loop — use trends to prevent the next change problem and manage document knowledge across the lifecycle.
CAPA and risk performance is quantified and reviewed; recurrence and effectiveness are managed numbers.
TO ADVANCE →Shift from corrective to predictive — use trends and QRM to prevent events, not just close them.
Process capability and continued verification are trended; decisions are evidenced by data.
TO ADVANCE →Move toward continuous verification and real-time control where the economics and risk justify it.
EM data is trended and the state of control is a managed number; early drift is acted on.
TO ADVANCE →Move toward rapid/real-time methods and predictive contamination control.
The organisation gap-analyses against upcoming requirements and prepares before the deadline.
TO ADVANCE →Engage — contribute to consultations and shape the requirements, not just meet them.
Centralised and statistical monitoring detect signals early; KRIs drive action.
TO ADVANCE →Move toward predictive quality — design quality into the protocol and anticipate risk.
QA and laboratory data are trended; systemic issues are managed, not repeated.
TO ADVANCE →Move to predictive quality — anticipate data and compliance risk from trends.
Distribution performance is trended; weak lanes and recurring excursions are managed proactively.
TO ADVANCE →Move toward real-time, predictive cold-chain control.
Safety performance is quantified; benefit-risk and signal metrics drive proactive action.
TO ADVANCE →Move toward proactive safety science — anticipate risk from real-world and trial data.
Data-integrity performance is measured; review findings and events are trended and acted on.
TO ADVANCE →Design integrity in — reduce the manual review burden with better system controls.
Engineering performance is measured; system reliability and verification data drive improvement.
TO ADVANCE →Integrate engineering into the full product/process lifecycle for predictive reliability.
Quality culture is measured through observable behaviours; leaders manage it as a system.
TO ADVANCE →Build a learning organisation where psychological safety turns every problem into improvement.