An Automated Multidimensional Framework for Diagnosing Organizational Communication: A Data-Driven Approach Using Enterprise Collaboration Platform Logs

초록

Following the digital transformation and the post-pandemic shift, smart working environments have become the standard organizational mode, increasing the need for effective communication management and cultural assessment. Traditional methods, relying on surveys, interviews, or partial log analyses, fail to capture communication's multidimensional and real-time nature fully, thereby limiting automation and objectivity. This study proposes an automated quantitative diagnostic framework to overcome these limitations that utilizes message and task log data generated in real collaborative settings. The framework defines four key indices: communication smoothness, workload adequacy, transmission clarity, and relational engagement. These indices are computed to classify communication patterns and culture types based on the Competing Values Framework (CVF). It integrates metrics such as message exchange ratio, workload distribution, direct and indirect message ratio, and network connectivity to provide a real-time and objective evaluation. The identified culture types were validated by comparing member perceptions collected through surveys and interviews. The findings show that this approach effectively bridges qualitative and quantitative organizational diagnostics, providing a solid foundation for continuous monitoring of communication and cultural dynamics in digital collaboration environments.

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