In audit environments, financial data from diverse client systems is exchanged through spreadsheets that differ in structure, naming conventions, and logical content. Each variation demands manual adaptation, matching, and mapping of data into standardized templates. This variability complicates quality assurance, version control, and governance across multiple engagements and teams. The goal of the Bachelor thesis was to design an automated, configurable spreadsheet data mapping solution using MS Power Automate and Office Scripts to streamline parts of the audit preparation process.

The research applied a Design Science Research (DSR) methodology, encompassing problem analysis, design, development, and evaluation. Existing automation scripts and workflows were analyzed to identify barriers to reuse and gaps in governance. Drawing on literature and expert interviews, a conceptual platform model was developed to separate reusable mapping logic from client-specific configurations. The conceptual artefact illustrated how configuration-driven automation could enhance maintainability, transparency, and scalability in financial data preparation.

The outcome is a conceptual blueprint for a configurable data mapping approach that clearly distinguishes between reusable automation logic and source-specific configuration. This shift from client-specific automation to controlled configuration and governance can reduce redundant redevelopment efforts, improve consistency and transparency, and strengthen traceability for audits and reviews. Additionally, the thesis delivers reusable documentation artefacts, including requirements, evaluation criteria, and rollout considerations, to support implementation planning and decision-making in confidential or compliance-sensitive environments.