Structured Review Practices in Projects: A Systems Perspective on Experiential Knowledge Transfer—A Systematic Review

Project experience is distributed across individuals, project artifacts, team interactions, and organizational arrangements, making its transfer across project and temporal boundaries a multilevel systems challenge. Although after-action reviews, debriefs, retrospectives, postmortems, project reviews, and lessons-learned practices provide organized means of learning from experience, the interdependent components, transformation processes, and feedback relationships through which they generate reusable experiential knowledge remain insufficiently explained. This study systematically reviewed 106 English-language scholarly publications selected from 4157 records retrieved from the Web of Science Core Collection and Scopus. The evidence was synthesized through functional classification of evidence, typological analysis, thematic synthesis, and systems-oriented interpretive synthesis. The review establishes a common analytical domain for structured review practices based on four defining attributes and identifies four ideal-type configurations distinguished by their primary triggering mechanisms and knowledge boundaries. Across these configurations, four interconnected clusters of key cognitive tasks transform project experience materials into a shared interpretive foundation, reusable experiential knowledge, and a basis for future action. These transformations constitute a multilevel feedback architecture comprising short within-project and long cross-project loops, but may break down at five points under task–cognitive, social–political, and organizational–technological conditions. This study reframes structured review practices as a multilevel socio-technical learning system that connects actors, evidence, cognitive processes, knowledge artifacts, organizational uptake, and feedback from subsequent action. It thereby provides a systems-oriented conceptual basis for the design and diagnosis of structured reviews and for future research on human–AI support in project-based organizations.