As companies increasingly adopt service-based business models, the design of coherent and scalable service architectures becomes essential. While literature highlights the need for service analyses as a precursor to architectural design, it lacks concrete methodologies that integrate data from various life-cycle stages and organizational domains. This study addresses this gap by proposing a structured analysis method for identifying hierarchical decompositions across digital, physical, and mental sources–spanning sales, invoicing, and operations. The research question guiding this work is: how can the scope of service architecture analyses be systematically expanded to include more preexisting system decompositions, in order to reduce knowledge-based implementation barriers? The proposed method is tested in a case study at a Danish third-party logistics (3PL) company, revealing structural and semantic misalignments across organizational systems. By increasing transparency and highlighting misaligned service structures, the analysis improves the foundation for conceptualizing and implementing service architectures.