Improving Project Management Performance Through Data Analytics

Jesusa  N. Padilla,; Neil  P. Balba,; Michael  R. Ramos,; Edgardo  Dajao,; Juan  C. Tallara Jr,

Improving Project Management Performance Through Data Analytics

Michael R. Ramos | Neil P. Balba | Jesusa N. Padilla | Edgardo Dajao | Juan C. Tallara Jr

Abstract:

In today’s complex IT landscape, organizations frequently encounter budget overruns and schedule delays that undermine project success. This study investigates the role of data analytics in enhancing project management performance, focusing on cost efficiency and schedule adherence. Through a comparative analysis of multiple infrastructure and IT outsourcing projects—some managed with advanced analytics tools and others with traditional methods—this employs descriptive and inferential statistics alongside a structured cost-benefit evaluation. Key findings reveal that analytics-enabled projects achieved an average cost reduction of 2.5 percent and an 11 percent decrease in completion time relative to non-analytics counterparts. Predictive forecasting and real-time monitoring improved resource allocation and mitigated risks, while the five-year cost-benefit analysis demonstrated a 214 percent return on investment. These results underscore the strategic value of integrating data analytics to drive proactive decision-making, optimize resource use, and secure timely project delivery. Practical recommendations are offered for organizations seeking to embed analytics into their project workflows and maximize both financial and operational outcomes.

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