Postanalysen

Postanalysen are systematic evaluations conducted after events, data collections, or processes have concluded. The aim is to understand what happened, identify contributing factors, assess outcomes, and derive lessons to improve future practice. The term is used in German-speaking contexts and in some European disciplines, where it is often related to but distinct from preplanned analyses or prospective studies.

Applications span research, safety engineering, business, and organizational learning. In research, postanalyses refer to analyses performed after data collection to explore additional hypotheses, verify robustness, or reassess results; they should be clearly differentiated from preregistered analyses to avoid bias and multiple testing issues. In industry and safety contexts, postanalyses include after-action reviews, debriefings, and root-cause analyses meant to reconstruct events and inform corrective actions. In journalism and governance, postanalyses may support accountability, transparency, and policy recommendations.

Common methods include structured debriefings, document and data reviews, statistical reanalysis, and qualitative synthesis. Advantages are enhanced learning, process improvement, and accountability. Limitations include hindsight bias, selection bias, and the risk of data dredging if posthoc methods are not properly controlled or transparently reported.

See also: post hoc analysis, retrospective study, after-action review, lessons learned. Etymologically, post means after and analyse derives from analysis; the plural form postanalysen reflects discussions or literature addressing multiple instances of post-event evaluation.