Metrics, Not Audits, Should Lead Vendor Accountability
By Irwin Hirsh, Q-Specialists AB
At each stage of biologic drug development, the objective of vendor risk management is the same: replace “oversight by periodic inspection” with risk-based controls, meaningful metrics, and decision triggers that keep work under control — even when business realities force trade-offs and external conditions shift faster than governance routines typically do.
Here, I propose a life cycle model from selection and qualification through routine oversight, change management, escalation, and exit.
Why This Matters More Than Ever
Outsourcing has moved the biopharma “factory floor” outside the company. For virtual and lightly staffed organizations, product quality, supply reliability, and the credibility of regulatory commitments are increasingly determined by partners. Vendor management is therefore not an administrative quality process; it is strategy execution — because if your partner network cannot deliver the work, your strategy cannot be realized.
At the same time, decision cycles are compressing. Accelerated development and approval pathways, complex global supply chains, and frequent organizational change leave less time to detect and resolve problems. Risk rarely arrives as a single dramatic event. It typically accumulates quietly, through drift, weak communication pathways, unmanaged change, and misaligned incentives, then surfaces as a failure: an OOS, a failed batch, or a regulatory delay.
Audits Are Essential But Insufficient On Their Own
Many companies respond to issues by leaning harder on audits. Audits are essential but episodic. They cannot provide continuous assurance that contracted work remains under control, changes are governed, or early signals are acted on.
Audits must target the high-risk areas highlighted by routine oversight signals, confirming that controls are working or revealing why they are not. When the sponsor maintains a current operational view of vendor risks and shortcomings, each audit can focus on the failure modes most likely to threaten the product, process, or regulatory commitments. Follow-up should extend beyond audit CAPA: trend recurring observations as signals and close them through governance actions, quality agreement amendments, or change control expectations.
Transition: From Disconnected Activities To Structured Reasoning
To move from compliant but disconnected activities to a value-adding oversight system, vendor management must be treated as structured reasoning. The hierarchy-of-metrics approach presented below, explored in depth in the first article of this series, provides the backbone: it connects strategic outcomes to a small set of decision-driving signals and then to the critical success factors and diagnostics that reveal drift early enough to intervene.
In the next article, I show how to operationalize this logic so that audits, quality agreements, metrics, and governance forums function as one coherent process, enabling timely decisions and sustained control of the outcomes for which the business is accountable.
From Strategy To Signals — The Vendor Metrics Hierarchy
Many organizations can demonstrate oversight activity — audits completed, business reviews held, scorecards populated — yet still experience quality surprises, unstable supply, and late discovery of unmanaged change. The failure mode is not a lack of data. It is a lack of structured reasoning: metrics are collected but not consistently used to drive decisions.
A governance metric, leading or lagging, must enable action. It should trigger a review, constrain a decision, or reallocate attention and resources. If it does none of these, it is reporting noise — visible work that does not improve control.
The hierarchy: how strategy becomes action
The hierarchy of metrics approach links strategic outcomes to the signals that show whether vendor control is holding, creating a common language across functions.
- Strategic goals: the outcomes an outsourced network must deliver.
- KPIs: a small set of network-level measures leadership can steer by.
- OKRs/targets: near-term outcomes by vendor tier, program, or life cycle phase.
- Critical success factors (CSFs): “must-be-true” conditions for control.
- Diagnostic metrics: early signals that reveal drift and clarify root cause.
Governance tips
- Manage a few high-quality signals, not many lower-quality ones.
- Treat the hierarchy as a decision system, not a dashboard exercise.
- For each metric, define an owner, a definition, and an expected response when it moves.
Strategic goals for outsourced biopharma networks
In an outsourced model, vendor oversight goals are business outcomes that determine whether the company can deliver its commitments. For example:
- Regulatory reliability: sustained inspection readiness; predictable conformance to dossier and GMP.
- Supply reliability and continuity: predictable delivery and release performance; resilience to disruption.
- Change agility with control: change fast enough to support development and supply, without unmanaged variability.
- Life cycle readiness: robust knowledge transfer; readiness for PPQ/CPV and scaling transitions.
- Cost of poor-quality containment: prevention of avoidable investigations, batch loss, rework, and escalation costs.
These goals remain stable even as programs and vendors change, and they should anchor what you measure, review, and escalate.
KPIs: signals leadership can use
KPIs sit one level below strategic goals. They should be few, consistently defined, and strong enough to drive leadership decisions. KPIs focus attention, guide resource allocation, and trigger escalation.
| KPI | What it signals |
|---|---|
| Right-first-time release readiness | Whether disposition is predictable without last-minute fixes |
| Investigation and CAPA effectiveness | Whether issues are resolved to root cause and do not recur |
| Change control health | Whether changes are governed and do not introduce instability or drift |
| On-time critical deliverables | Whether execution reliably meets milestones that gate your program |
| Quality agreement alignment | Whether responsibilities and expectations are defined and current before execution |
These KPI examples are illustrative. What matters is the pattern: a small set of KPIs with clear definitions, assigned owners and forums, an agreed baseline, and a predefined response when performance drifts.
CSFs and diagnostic metrics: early warning and root cause
CSFs define the conditions that must remain true for outsourced work to remain in control.
Diagnostic metrics provide the routine signals that show whether those conditions are holding, and where they are not, early enough to intervene.
The table below links CSFs to diagnostics and the oversight actions they enable.
| CSF (what must hold) | Diagnostic signals (to monitor) | What it enables |
|---|---|---|
| Changes are identified before execution and assessed using risk-based criteria. |
|
Targets audits and governance on change pathways where drift is being introduced |
| Roles and deliverables are unambiguous typically defined in QAA |
|
Reveals structural misalignment Triggers targeted QAA amendments and clarifies handoffs before work proceeds |
| Data integrity expectations are explicit, verified, and sustained for records and systems in scope |
|
Confirms whether evidence is reliable and targets verification of the record controls that matter most |
| Communication is fast enough to act before impact |
|
Pinpoints where late discovery is created and triggers actions to restore flow before schedule or quality impact |
Three metric levels, one control system
- KPIs show that performance is drifting.
- CSFs define what must hold to prevent drift.
- Diagnostics show whether it is holding, early enough to intervene.
Used together, they let the sponsor address hazards as weak signals and process drift, before they surface as deviations, supply disruption, or regulatory impact.
This is also what makes on-site audits more valuable: diagnostics focus audits on the highest-risk areas, guiding what evidence to examine and which control hypotheses to confirm or disprove.
Risk-based intensity: same framework, different depth
Use the same metrics hierarchy for every vendor, but apply more depth where risk is higher.
Increase oversight intensity when:
- Criticality/scope is high (sterile manufacturing vs. indirect services)
- Life cycle phase risk is high (tech transfer, scale-up)
- Performance signals worsen (history and current trends)
- Continuity risk rises (financial health, ownership change, regional/geopolitical instability)
This avoids two failures:
- Over-control everywhere (noise and fatigue)
- Under-control where it matters (blind spots in high-consequence work)
With the metrics hierarchy defined, the next step is to apply it across the vendor life cycle. In the next part of this article, I'll propose a practical strategy for deploying quality assurance agreements and sponsor-led vendor oversight systems. I'll also break down the dominant risks to manufacturing and the controls to mitigate them.
About The Author:
Irwin Hirsh has 30 years of pharma experience with a background in CMC encompassing discovery, development, manufacturing, quality systems, QRM, and process validation. In 2008, Irwin joined Novo Nordisk, focusing on quality roles and spearheading initiatives related to QRM and life cycle approaches to validation. Subsequently, he transitioned to the Merck (DE) Healthcare division, where he held director roles within the biosimilars and biopharma business units. In 2018, he became a consultant concentrating on enhancing business efficiency and effectiveness. His primary focus involves building process-oriented systems within CMC and quality departments along with implementing digital tools for knowledge management and sharing.