One of the core QMS principle enumerated in the ISO13485 is the Plan-Do-Check-Act (PDCA) cycle. The cycle requires that you set indicators for processes, monitor and analyze data.
There are three sets of tools you can use for effective data analysis that can drive continual improvement.
1. Basic “7 QC tools”
| Tool | Typical data sets | How it helps continual improvement (examples) |
| Check sheets | Complaints, in‑process defects, incoming inspection, service reports, PMS event logs | Structures raw data capture at the source so trends and Pareto analysis are reliable; simplifies frontline contribution to feedback and PMS processes required by 8.2.1 and 8.2.2. |
| Pareto chart | Complaints categories, defect types, audit findings, CAPA causes, supplier NC types | Identifies the “vital few” problems causing most impact , helping prioritize CAPA, design changes, or training. |
| Histogram | Process measurements (dimensions, torque, sterilization parameters), test results, delivery times | Shows distribution vs. specs, helping decide if process is capable or needs adjustment, aligning with 8.2.5/8.2.6 monitoring and 8.4 analysis of data. |
| Control charts (SPC) | Critical process parameters, in‑line product characteristics, environmental controls, AQL data | Enables early detection of process drift before nonconformities or complaints, supports validated processes and continual process improvement. |
| Scatter diagram | Relationships such as temperature vs. defect rate, supplier lot age vs. failures, training hours vs. audit NCs | Quantifies correlations and supports evidence‑based changes to processes, environment, or supplier controls. |
| Cause–effect (Ishikawa) | Recurring complaint modes, major CAPAs, audit major NCs, supplier systemic issues | Structures root‑cause analysis so corrective actions address true causes (methods, materials, people, environment, design), as expected in 8.5.2. |
| Stratification/run charts | Complaints by region or product family, NCs by shift or machine, PMS signals by use condition | Reveals patterns that would be hidden in aggregated data, guiding targeted improvements (e.g., specific country, lot, operator group). |
2. Risk and root‑cause tools
ISO 13485 expects a risk‑based approach across QMS processes and to use feedback/PMS data as input into risk management.
| Tool | Typical data sets | How it helps continual improvement |
| FMEA (Design & Process) | Complaints, PMS incidents, process NC data, supplier failures, field service data | Uses RPN or similar metrics to focus controls on highest‑risk failure modes; feedback from real‑world data is looped back to re‑score and improve controls. |
| Fault Tree Analysis (FTA) | Serious field events, recalls, MDR/MDV reports, major nonconformities | Works backwards from a top event (e.g., serious injury) through logical causes, identifying where design, labeling, training, or supplier control must be strengthened. |
| 5 Why / structured RCA | Any significant CAPA: serious complaints, repeat audit NCs, frequent process deviations | Ensures CAPAs remove systemic causes rather than just correcting symptoms; supports 8.5.2 effectiveness verification. |
| Risk matrix & heat maps | Combined risk profiles across products, suppliers, processes, markets | Helps management review focus on high‑risk areas when deciding improvement actions, resources, and post‑market study priorities. |
3. Process and performance analysis
These tools connect internal process data with outcomes such as complaints, PMS, and CAPA effectiveness.
| Tool | Typical data sets | How it helps continual improvement |
| KPI dashboards & scorecards | Customer complaints, OTD, scrap/rework, first‑pass yield, CAPA closure time, supplier PPM, field failure rates | Provide routine visibility of QMS effectiveness to management; trigger deep‑dive analysis when thresholds are exceeded as required by 5.6 and 8.4. |
| Trend & regression analysis | Time‑series of complaint rates, PMS events, audit NC rate, CAPA recurrence, process metrics | Detects emerging issues early and quantifies impact of changes (e.g., new supplier, new sterilization cycle); supports decisions on additional controls or design updates. |
| Capability analysis (Cp/Cpk, Ppk) | Critical dimensions, process outputs tied to safety or performance | Demonstrates process capability for validated processes, supports justification that process changes or improvements maintain device safety and performance. |
| Multi‑variable comparison (stratified reports) | Complaint rates by product, region, lot, UDI, indication, or user group | Supports medical‑device‑style PMS, helping detect device‑use or population‑specific risks and guiding labeling, training, or design changes. |