Organizational Barriers to Data-Driven Decision Making in Educational Management

Taryana

doi:10.61255/jeemba.v4i3.1092

Authors

Taryana Politeknik Penerbangan Indonesia (PPI) Curug

DOI:

https://doi.org/10.61255/jeemba.v4i3.1092

Keywords:

Analytical Capability, Data-Driven Decision Making, Educational Management, Organizational Resistance, System Fragmentation

Abstract

Purpose – This study examines organizational barriers affecting the implementation of Data-Driven Decision Making (DDDM) in educational institutions. Although digital academic systems are increasingly adopted, many institutions still struggle to utilize academic data effectively for evidence-based educational management and institutional coordination.

Design/methodology/approach – A quantitative survey approach was employed using purposive sampling techniques. Data were collected from 179 respondents consisting of lecturers, academic staff, administrators, and educational managers from universities, colleges, polytechnics, institutes, and schools in Padang through online questionnaires. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS).

Findings/Results – The findings reveal that data quality problems, organizational resistance, analytical capability deficiency, and system fragmentation significantly influence weak DDDM. Among these variables, analytical capability deficiency emerged as the strongest predictor. Weak DDDM also significantly affects educational management ineffectiveness.

Originality/Value – This study advances DDDM scholarship by positioning weak Data-Driven Decision Making as the key organizational mechanism through which data quality problems, organizational resistance, analytical capability deficiency, and system fragmentation become translated into educational management ineffectiveness. The Padang context shows that the main limit of educational digital transformation is not merely system adoption, but institutional readiness to convert data into coordinated, evidence-based governance.

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