In a large insurance claims process, domain experts only describe specific claim instances they have handled and no single person has end-to-end visibility due to departmental silos. Tacit knowledge about exceptions is also rarely documented. As a process analyst, identify the main discovery challenges present and the best mitigation approach., Only lack of documentation; use automated process mining exclusively, Fragmented knowledge, instance-level thinking, and tacit knowledge gaps; use multi-stakeholder workshops combined with interviews and selective evidence triangulation, Poor modeling skills of domain experts; conduct only individual interviews, Over-reliance on syntactic verification during discovery, For a highly variable, cross-departmental claims adjudication process with outdated documentation and conflicting stakeholder views, which discovery method combination would best ensure a complete and accurate “as-is” process model?, Evidence-based discovery using documents and logs only, Workshop-based and interview-based discovery supplemented by selective document and log analysis for triangulation, Individual interviews only to avoid groupthink, Automated process mining as the single primary method, During quality assurance, the analyst ensures all gateways have matching splits and joins and the model complies with BPMN syntax rules. Later, domain experts point out that the model does not correctly represent real-world exception handling and decision logic. Which quality aspects were primarily addressed first, and which were deficient?, Pragmatic quality addressed; syntactic quality deficient, Syntactic quality (verification) addressed; semantic quality (validation) deficient, Semantic quality addressed; pragmatic quality deficient, All three quality dimensions addressed equally.

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