taskanalytic

Taskanalytic is an interdisciplinary practice that combines traditional task analysis with data analytics to study how people perform work and how systems enable or constrain that work.

Practitioners create task models by deconstructing activities into goals, subgoals, steps, and decision points. They collect quantitative and qualitative data from observations, logs, time measurements, and system telemetry. Using methods from statistics, process mining, sequence analysis, and machine learning, they estimate task durations, dependencies, error rates, and completion times, and they identify bottlenecks and opportunities for optimization. The output often includes formal task models, performance metrics, and dashboards for stakeholders.

Applications span software design, operations management, healthcare, aviation, manufacturing, and logistics. In software UX, taskanalytic helps prioritize feature development and streamline workflows. In operations, it supports resource allocation and process redesign. In safety-critical domains, it supports risk assessment and training by revealing where human error is most likely.

Challenges include data quality and privacy, interpretability of models, evolving processes, and the need for domain expertise to validate models. Ethical considerations and governance are important in balancing efficiency with worker autonomy.

See also: task analysis, process mining, workflow optimization, cognitive task analysis, operations research.