Why Pre-Run Checks Catch Hardware Faults and Miss the Real Failure Modes
Your pre-run checks pass, the instrument reports ready, and the run still fails at a rate no one can explain. Those checks were built to catch overt hardware and software faults, not the design choices that decide whether a complex lab run holds: the drivers no one is measuring.
Why Passing Every Check Doesn't Make a Run Reliable
Pre-run checks on automated lab workflows and sequencers exist to prevent the most overt failures: a missing tip box, an uncalibrated module, a software version mismatch. They confirm the instrument can run. They say nothing about whether the workflow was designed to run reliably at volume.
Reliability is decided somewhere the checks never look. Operator interactions, manual pipetting steps, manual labeling, recovery actions when a run stalls: each was added for a reasonable local reason, and each is a point where the run depends on a person getting it right. None of them is tracked as a reliability metric. The checklist counts what is easy to verify at the gate, not what actually drives failure across a full run.
So the drivers accumulate unmeasured. A workflow can pass every pre-run check and still carry a 20 percent failure rate, because the metrics that predict that rate, how many manual interactions a run requires, how many handling steps invite error, were never assessed or designed against. Occasionally the check itself is the problem: a QC threshold calibrated to run health rather than result reliability will pass runs it should stop, as a high-throughput sequencing workflow found when standard QC cleared batches that were misreporting. More often, the failure drivers were simply never on anyone's list.
The Fix: Designing Against the Metrics That Predict Reliability
Pre-run checks catch overt hardware and software faults. Reliability is decided by the metrics they never measure: operator interactions, manual steps, and the points where a run depends on someone getting it right. The fix designs the workflow against those drivers, so reliability is built in rather than checked for.
Blanchard Strategic's Approach:
This is systems integration and risk assessment work: assessing the full run as one system rather than a set of components that each pass their own checks. The assessment identifies the reliability drivers the checks never count, quantifies them, and designs the workflow against them, so the failure modes that survive pre-run checks are engineered out before validation, transfer, or field deployment.
Mapping and quantifying the operator interactions, manual pipetting, manual labeling, and recovery steps that pre-run checks and QC gates never count.
Separating the design choices that genuinely protect the run from the inherited ones that add risk without value.
Restructuring the workflow to remove or contain those drivers, so reliability comes from the design rather than an external checklist.
Defining checks and metrics that reflect the real failure drivers, not just overt hardware and software faults.
When This Work Is Useful
This work fits automated lab and diagnostic workflows and sequencers where runs keep failing despite passing their checks, and the reliability issues have to be designed out before validation, transfer, or field deployment.
