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Abstract

Purpose: This research explores the integration between professional judgment and comprehensive information analysis in organizational decision-making processes, focusing on the synergistic potential of combining human expertise and computational capabilities to optimize decision outcomes.


Research Design and Methodology: Using qualitative research methodology, this study adopts a systematic literature review approach by synthesizing existing literature from academic databases such as PubMed, Scopus, and Google Scholar. It analyzes the dynamics, implications, and challenges of such integration in an organizational context.


Findings and Discussion: The results highlight the complementary nature between professional judgment and information analysis, emphasizing the importance of a balanced approach that leverages the strengths of both perspectives. Professional judgment offers adaptability and sensitivity to context, while information analysis through decision support systems (DSS) provides objectivity and systematic data processing. However, both approaches have limitations, such as bias in professional judgment, data quality, and interpretability challenges in information analysis.


Implications: The implication of this integration is the importance of building a culture of evidence-based decision-making within organizations, as well as providing decision-makers with the necessary tools and resources. By adopting an integrated decision-making approach, organizations can improve their decision-making effectiveness and face the complexities of their context with more confidence.

Keywords

Professional Judgment Information Analyses Decision-Making Processes Decision Support Systems

Article Details

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite
Aulia, R. (2023). Enhancing Decision Making through Professional Judgment and Comprehensive Information Analyses. Advances in Managerial Auditing Research, 1(3), 146–155. https://doi.org/10.60079/amar.v1i3.230
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