How do you identify and prioritize processes for RPA implementation?

Process selection determines RPA program success. Assessment framework: evaluate each candidate process on automation suitability (rule-based, structured inputs, stable systems, digital triggers), business value (time savings, error reduction, compliance improvement, employee satisfaction), and implementation complexity (number of applications, exception handling, integration requirements). Scoring methodology: rate each dimension 1-5, calculate weighted score (value: 40%, suitability: 35%, complexity inverted: 25%), and rank processes. Quick wins: start with processes scoring high on value and suitability, low on complexity. These build organizational confidence and demonstrate ROI quickly. Process documentation: before automating, document the current process with BPMN notation, identify all steps, decision points, exceptions, and system interactions, measure current performance (time per case, error rate, volume), and identify the happy path (most common flow) vs exception paths. Red flags for RPA suitability: high exception rate (30% of cases deviate from the standard path), frequent process changes (application updates, rule changes), heavy reliance on unstructured data (free-text emails, handwritten forms), and processes requiring complex judgment or interpretation. Process mining: use tools like Celonis or UiPath Process Mining to discover actual process flows from system event logs, revealing the true process (including workarounds and variations) rather than the documented ideal. Pipeline management: maintain a process automation pipeline with stages (identified, assessed, designed, developed, tested, deployed, optimized), track each process through stages, and communicate status to stakeholders.