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The global digital transformation, accelerated by the COVID-19 pandemic and the massive adoption of generative artificial intelligence (AI) architectures, has triggered an exponential surge in the construction of hyperscale data center infrastructure, positioning data centers among the most energy-intensive industrial facilities in the world. This research presents a comprehensive analysis of the role of Data Center Infrastructure Management (DCIM) as an instrument to diagnose, orchestrate, and improve energy efficiency, quantified specifically through the reduction of the Power Usage Effectiveness (PUE) metric. Using a framework of systematic review and empirical multi-case analysis, this research explores the operational thermodynamic dynamics that cause inefficiencies, such as zombie servers and over- provisioning of HVAC systems. Quantitative analysis demonstrates that DCIM intelligence features can help reduce PUE, with several institutional facilities successfully lowering baseline PUE from 1.83 to 1.51 while cutting cooling loads by up to 48%. In Indonesia, DCIM integration supports the fulfillment of the mandates of SNI 8799:2020 and SPBE guidelines and helps mitigate peak load resilience risks for PT PLN (Persero).
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Fuady et al. (2026) studied this question.
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