Workflow Analysis Framework

Document the workflow as it exists today — every step, actor, system, decision point, and handoff.

• •Process name and owner
• •Trigger: what initiates the workflow
• •Step-by-step process flow
• •Actors involved at each step (person, team, system)
• •Systems and tools used
• •Decision points and branching logic
• •Handoff points between people or systems
• •End state: what marks completion

Quantify how often the process runs, the volume of items processed, and the total time and cost per cycle.

• •Number of instances per day / week / month
• •Average time per instance
• •Total time spent per period
• •Number of people involved
• •Fully loaded cost per period
• •Peak periods and variability

Identify where delays, errors, manual workarounds, and frustration create the biggest drag on efficiency.

• •Steps with highest error rates
• •Steps that take disproportionate time
• •Manual workarounds and why they exist
• •Bottleneck steps (queue builders)
• •Rework loops and their triggers
• •Staff frustration points

For each step, assess whether AI or automation could handle it — and what technique would apply.

• •Step-by-step automation assessment (full / partial / not suitable)
• •AI technique match (classification, extraction, generation, routing)
• •Data availability for each step
• •Integration complexity (API, file, manual)
• •Estimated accuracy for AI handling
• •Human-in-the-loop requirements

Map the systems that need to connect and the data that needs to flow between them.

• •Source systems and their APIs / export capabilities
• •Target systems and their import capabilities
• •Data format requirements (JSON, CSV, PDF, etc.)
• •Authentication and access requirements
• •Real-time vs. batch processing needs
• •Error handling and retry requirements