IJSEA Volume 14 Issue 8

Assessing Data Analytics Readiness for Enhanced Decision-Making in Software Project Management: An Empirical Framework and Case Study of Yonyou Network Technology Co., Ltd.

Mao Ruolan, Rhodora N. Ontal
10.7753/IJSEA1408.1002
keywords : Data Analytics Readiness?Decision-Making?Software Project Management?Empirical Framework?Case Study

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The effective integration of data analytics (DA) into software project management (SPM) holds significant potential for enhancing decision-making quality and project outcomes, yet organizations often struggle with assessing their readiness for such adoption. This study develops and validates an empirical framework to evaluate Data Analytics Readiness (DAR) specifically within SPM contexts, addressing the gap in tailored assessment tools. Through a comprehensive literature review and expert validation, we identify critical dimensions of DAR, including data infrastructure, skills maturity, analytical culture, governance, and strategic alignment. The framework is applied in a detailed case study of Yonyou Network Technology Co., Ltd., a leading enterprise software provider. Mixed-methods research—incorporating surveys, interviews, and project artifact analysis—reveals that while Yonyou possesses robust technical infrastructure, gaps in analytical skills and inconsistent data-driven culture hinder optimal DA deployment for SPM decisions. The framework proves effective in diagnosing strengths and barriers, providing actionable insights. Findings emphasize that beyond technology, organizational and human factors are pivotal for DAR. The study contributes a validated assessment tool for practitioners and underscores strategic imperatives for enhancing DA-driven decision-making in software enterprises.
@artical{m1482025ijsea14081002,
Title = "Assessing Data Analytics Readiness for Enhanced Decision-Making in Software Project Management: An Empirical Framework and Case Study of Yonyou Network Technology Co., Ltd.",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "14",
Issue ="8",
Pages ="3 - 9",
Year = "2025",
Authors ="Mao Ruolan, Rhodora N. Ontal "}