In this study, we analyse a medieval inquisitorial campaign by conceptualizing it as an information process. We investigate how investigative decision-making was structured by testimony-driven data gathering. Our case study is Peter Zwicker's well-documented 1393-4 anti-Waldensian inquisition in Stettin. We explore the reconstruction of the inquisitor's strategy by examining the sequencing of interrogations and subsequent actions based on suspects' names appearing in previous testimonies. We assess the extent to which the process was adaptive, with suspects summoned dynamically based on new testimonies versus being guided by pre-existing knowledge. We apply network analysis and temporal visualization to incriminations operationalized as network data and use statistical methods to map the feedback between information retrieval and decision-making. Our analysis follows sequences of interrogations where deponents incriminated others on specific dates. This allows us to identify inquisitorial responses to accumulated data, distinguishing between planned strategies and reactive decisions based on new testimony. The challenge of missing data adds complexity and theoretical engagement. A substantial portion of the depositions is lost, yet we can estimate the original volume, enabling an assessment of the impact of data loss. We employ data imputation simulations to test how missing records might obscure evidence of follow-up strategies. The results indicate that network visualization must be complemented by statistical analysis. Comparisons between deponents' testimony types reveal an interplay between structured pre-planning and selective incorporation of new intelligence. By conceptualizing inquisitorial work as a dynamic information process, this study proposes a novel methodological framework for analysing historical trial documents.