HPI treats human performance as a system. Our research program studies the necessary conditions under which cognition, energy, motivation, social dynamics, and adaptive capacity interact to sustain work that matters.
Research directions
Rather than measuring isolated outcomes, we examine how behavioural workflow data reflects the underlying system state of a team. Current work includes:
- Cognitive load under AI augmentation — how attentional and decision-making capacity shifts when routine work is automated.
- Recovery rhythms in distributed teams — identifying patterns that predict burnout risk weeks before self-reports do.
- Social friction as a performance signal — modelling how coordination overhead accumulates and where it breaks.
- Adaptive capacity over time — distinguishing teams that grow stronger from those that drift toward instability.
Method
HPI studies are conducted in real AI-enabled work environments in partnership with operating teams. We combine behavioural workflow telemetry with structured performance diagnostics, interpreted through the HPI framework.
Published findings and case studies will be shared here as they are released. If you lead a team interested in participating in a study, please get in touch.