This paper introduces distributed reanalysis as an innovative methodological strategy to reuse qualitative data to compare multiple large-scale phenomena. Distributed reanalysis combines collaborative team research and data reuse to reanalyze previously collected data using a shared analytical guide. This method preserves the depth of qualitative case analysis while facilitating cross-case comparisons. We present this approach and examine its application through a study involving 27 contributing researchers analyzing data from 15 distinct cases. Using a shared analytical guide, distributed reanalysis circumvents the confidentiality and decontextualization challenges of data sharing while supporting generalizable conclusions across multiple cases. This method offers a solution for comparing multiple cases by leveraging pre-existing datasets and the familiarity of the original researchers, contributing a methodological strategy to organizational studies.
