analyseworkflows

Analyseworkflows is the systematic study of how work is performed within an organization, aimed at understanding, documenting, and improving processes. It draws on data analytics, process modeling, and organizational analysis to identify inefficiencies, bottlenecks, and opportunities for automation or redesign.

Core techniques include process mining (discovering process models from event logs), workflow analysis, value stream mapping, and simulation. Data sources include event logs from ERP, CRM, and BPM systems, as well as time measurements and qualitative observations. Outputs typically include process models, performance metrics, and a prioritized list of improvement actions.

Applications span manufacturing, financial services, healthcare, logistics, and software development, among others. Goals may include reducing cycle time, increasing throughput, improving compliance, lowering costs, and enhancing customer experience.

A typical approach comprises scoping, data collection and cleaning, discovery and conformance checking, performance analysis, solution design, testing with simulations, and implementation with monitoring. Iterative cycles support continuous improvement.

Challenges include data quality and privacy, process complexity and variability, organizational resistance, and the need to align changes with business strategy. Success depends on stakeholder involvement, governance, and clear success metrics.

Relation to related fields: Analyseworkflows overlaps with process mining, business process management, and operational research. It emphasizes data-driven insights and measurable outcomes, rather than purely descriptive modeling.