Most biopharma organizations invest heavily in training, yet struggle to answer a basic question: is that training actually improving performance?
In many labs, training success is still inferred from completion rates or informal feedback rather than tracked through R&D training KPIs that link learning to quality, speed, and cost. As pressure grows to improve lab reproducibility, reduce operational waste, and accelerate timelines, this gap is becoming harder to ignore.
Training directly influences outcomes such as time to independent work, deviation rates, rework, and throughput. However, without defined R&D training metrics and standardized instructional approaches, these effects remain difficult to measure.
In 2026, leading teams are moving beyond “training delivered” toward training measured against R&D performance indicators, increasingly supported by visual method-level instruction.