Quality Assurance vs Quality Control

This topic is part of the SG Systems Global regulatory & operations glossary.

Updated December 2025 • QA vs QC Roles & Responsibilities • QA, QC, Operations, Regulatory, IT

Quality Assurance (QA) vs Quality Control (QC) is one of the most important distinctions in regulated manufacturing. Quality Assurance designs and governs the system that ensures products are consistently made right: policies, procedures, training, risk management, deviations, CAPA, change control (MOC), supplier oversight, and release decisions. Quality Control performs the tests and inspections—on materials, intermediates, and finished goods—that provide objective evidence of conformance. QA sets the rules and reviews the evidence; QC generates much of that evidence.

“QA is the architect and referee; QC is the measurement team on the field. If either is weak, the score doesn’t mean much.”

1) Definitions – QA vs QC in Practical Terms

In practical, inspector-friendly language:

• Quality Assurance (QA) – All the planned and systematic activities implemented within the quality system to provide confidence that requirements for quality will be met. QA is proactive and system-oriented.
• Quality Control (QC) – The operational techniques and activities that are used to fulfill requirements for quality. QC is reactive and product/sample-oriented.

QA asks “Do we have the right system, and does it work?”; QC asks “Does this material, batch, or device meet its specification?”

2) Scope – System vs Sample

Quality Assurance scope includes:

• Design, maintenance, and improvement of the Quality Management System (QMS).
• Authoring, controlling, and training on SOPs and work instructions.
• Qualification of suppliers, equipment, utilities, and computerized systems.
• Governance of deviations / nonconformances, CAPA, and MOC.
• Batch / lot disposition and release or rejection decisions.
• Internal audits, management review, and regulatory inspection readiness.

Quality Control scope includes:

• Sampling and testing of raw materials, intermediates, and finished goods.
• Environmental and utilities monitoring (micro, particulates, etc.).
• In-process measurements (pH, weight checks, torque, dimensions, assay, purity).
• Calibration and verification of analytical instruments and test equipment.
• Data interpretation vs specifications and trending of analytical results.

QA decides how tests must be done and what they mean; QC executes those tests and reports the results within that framework.

3) Examples – QA Tasks vs QC Tasks

Quality Assurance examples:

• Approving master batch records and device master records before use.
• Reviewing and approving validations and qualifications (process, cleaning, CSV).
• Reviewing completed eDHR/eBR and QC data before batch release.
• Leading investigations for critical deviations and complaints and owning CAPA.
• Running the Quality Assurance Process and Management Review.

Quality Control examples:

• Testing incoming raw materials against COA and internal specs.
• Running in-process tests and recording results in LIMS / MES.
• Performing final release tests on finished goods (assay, ID, purity, sterility, function).
• Executing stability studies according to protocols.
• Maintaining reference standards, reagents, and calibration schedules for instruments.

In simple terms: QC runs the assays and checks; QA decides if, given all the data and context, the batch is fit for use and the system needs to change.

4) Independence & Organizational Relationships

Most regulations expect a defined, independent QA function:

• QA is typically an independent unit with authority to block release and stop production where quality is at risk.
• QC may report into QA, but often operates as a specialized lab or inspection department.
• Operations owns production; QA does not “run the line” but can veto or condition its operation.

When QA and QC roles are blurred or subordinated entirely to operations, you usually see slow-drip quality failures and nasty surprises in audits.

5) Regulatory & Standards View (ISO 13485, GMP, etc.)

Standards and regulations frame QA and QC differently:

• ISO 13485 / ISO 9001: describe requirements for the QMS (QA domain) and control of monitoring and measuring devices (QC domain).
• GMP / GxP: refer to independent Quality Units (QA) with authority over batch release, and QC labs responsible for testing and environmental monitoring.
• Device & pharma regulations: explicitly require QA oversight of documentation, validation, complaints, and recalls, while QC provides much of the test data feeding those decisions.

Inspectors will often ask “Who is QA?” and “Who is QC?” separately—and then test whether your day-to-day behavior matches your org chart and procedures.

6) Data & Records – QA vs QC Responsibilities

QC data responsibilities typically include:

• Generating accurate, traceable test results with full Data Integrity (ALCOA+).
• Maintaining analytical methods, reagents, and instrument calibration records.
• Ensuring LIMS / instrument data are complete and audit-trailed (Audit Trail (GxP)).

QA data responsibilities typically include:

• Owning the QMS records (SOPs, training, deviations, CAPA, MOC, audits, risk files).
• Reviewing and approving QC data in the context of batch records and risk.
• Ensuring digital systems (QMS, MES, WMS, LIMS, ERP) are validated and controlled.

QC owns the raw measurements; QA owns the narrative and decisions built on those measurements.

7) QA vs QC in Investigations & CAPA

In a robust investigation model:

• QC often detects issues first (OOS/OOT, failed in-process checks, abnormal trends).
• QA coordinates the investigation, ensures root cause analysis is structured, and owns the Corrective and Preventive Action Report.
• QC contributes technical inputs (method performance, instrument status, sample handling) and may implement CA/PA within the lab.
• QA ensures system-wide changes (SOP, risk, validation, training) happen and are effective.

If QC is doing investigations alone without QA oversight, or QA is writing CAPA with no data from QC, you have a structural problem.

8) Digitalization – QA vs QC in Modern Systems

Digitally, QA and QC often live in different but connected systems:

• QA predominantly in eQMS (documents, training, events, CAPA, MOC, audits, risk).
• QC predominantly in LIMS, instrument software, and sometimes MES (in-process tests, environmental monitoring, release tests).
• Both visible in batch / device histories (eDHR/eBR) and ERP for release status.

The trick is integrating these so QA can see QC data in context, and QC can see QA decisions that affect test priorities, methods, and reporting.

9) Common Misunderstandings & Pitfalls

• “QC is QA.” Treating QC as the entire quality function and ignoring system-level QA responsibilities.
• “QA is just paperwork.” Using QA only to manage documents and audits, not to drive risk-based decisions and system changes.
• No independence. QA reported entirely into operations with no separate authority for release decisions.
• Over-centralized QC. Lab overloaded because it’s used as a crutch for poor process control.
• Data silos. QA cannot easily access raw QC data; QC cannot see CAPA outcomes or risk priorities.

Regulators pick up on these quickly: repeated failures, CAPA with weak root cause, and surprise field issues despite “passing” QC results.

10) How Quality Assurance vs Quality Control Fit with V5 by SG Systems Global

QA backbone with V5 QMS. The V5 Quality Management System (QMS) module is the digital home of QA: it manages document control, training, deviations, CAPA, change control, supplier quality, and risk records. QA uses it to run the Quality Assurance Process with full e-signatures and audit trails aligned to ISO 13485 and GxP.

QC execution via MES, LIMS & eDHR. The V5 MES layer captures in-process tests, checks, and line inspections as part of the electronic batch or device history. Integration with LIMS (via the V5 Connect API) lets QC results flow into eDHR/eBR, so QA can review QC data in context when making release decisions.

Material control & release via V5 WMS. The V5 WMS enforces QA decisions using QC data: lots stay in quarantine until QC tests pass and QA approves; holds, rework, or scrap decisions made in QMS are reflected as status codes at scan points; UDI, lot, and serial traceability link back to both QC results and QA events.

Platform-wide QA/QC visibility with the V5 Solution Overview. The broader V5 Solution Overview joins QA and QC: dashboards show quality events, CAPA, and risk alongside in-process and release-test trends. Auditors can be walked from a QC failure to the associated deviation, CAPA, change control, and the batches and customers affected—across QMS, MES, and WMS.

APIs & analytics via V5 Connect API. With the V5 Connect API, QA vs QC boundaries are clear but data is shared: QC labs can feed test results directly into analytics and SPC tools; QA can analyze CAPA effectiveness, NC rates, and supplier performance across plants and time, all using consistent data models.

Bottom line: V5 lets QA and QC do their distinct jobs—system design vs testing—while staying tightly integrated through shared, audit-ready data across QMS, MES, WMS, LIMS, and ERP.

11) FAQ

Q1. In one sentence, what’s the difference between QA and QC?
Quality Assurance designs and governs the system to prevent defects; Quality Control tests samples to detect defects.

Q2. Can QA and QC be the same team?
In very small organizations one team may cover both, but responsibilities must still be clearly separated on paper and in practice, and QA must retain independence for release and system decisions. As operations grow, separating QA and QC functions is strongly recommended.

Q3. Who should sign batch or lot release?
Typically QA (or the independent Quality Unit) has final authority for release or rejection. QC provides test results and technical conclusions, but QA weighs those results together with deviations, CAPA, risk assessments, and compliance requirements.

Q4. Is QC part of the QMS?
Yes. QC is a key process within the QMS, but it is only one part. The QMS also covers QA processes like document control, change control, CAPA, risk, training, supplier quality, and audits.

Q5. How do we explain QA vs QC to non-technical stakeholders?
A simple analogy: QC is the “inspection and testing” department; QA is the “system and governance” department that designs how work should be done, ensures people are trained, and acts when patterns of failure appear.

Q6. How do digital platforms like V5 help clarify QA vs QC?
V5 QMS gives QA a clear space to manage policies, events, CAPA, and risk; MES + LIMS give QC the tools to manage samples and results. Because these systems are integrated, QA sees QC data in context and QC sees QA requirements embedded in their workflows—making the QA vs QC split clear but collaborative.

Related Reading
• QA & QMS: QA Systems | Quality Assurance Process | Quality Management System (QMS)
• Events & Risk: Deviation / Nonconformance (NC) | Nonconformance Management | CAPA – Corrective & Preventive Action | Risk Management (QRM)
• Data & Execution: Data Integrity | Audit Trail (GxP) | eDHR Software
• V5 Platform: V5 Solution Overview | V5 QMS | V5 MES | V5 WMS | V5 Connect API