Data-Driven ESG KPIs Optimization: A Framework for Smart Buildings and Smart Factories

The growing importance of Environmental, Social, and Governance (ESG) performance across sectors has accelerated the adoption of digital technologies for the continuous monitoring, analysis, and optimization of key sustainability indicators. This study investigates the role of data-driven infrastructures—spanning hardware components (such as Smart Meters, IoT sensors, and Power Quality Analyzers) and software solutions (including Energy Management Systems, Business Intelligence, Digital Twins, and Artificial Intelligence)—in enabling more transparent, adaptive, and evidence-based ESG governance. Despite this trend, the literature remains fragmented, often focusing on isolated technologies and lacking a holistic framework. This study employs a critical literature review to address this gap, guided by the research question: How does the integration of advanced digital technologies contribute to the effective monitoring and optimization of ESG Key Performance Indicators (KPIs)? This approach allows for a comprehensive understanding of the strategic, technological, and operational dimensions involved in scaling such solutions. Findings identify two major application domains—Smart Buildings and Smart Factories—where the integration of digital tools enables a critical shift from static reporting to dynamic, real-time governance, demonstrating tangible benefits for sustainability and resilience. The study concludes by presenting an integrated framework and outlining key implications for practice and theory.

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Publication Details

Journal
Sustainability
Published
2025-12-03
DOI
https://doi.org/10.3390/su172310837
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
2.28
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article

Data-Driven ESG KPIs Optimization: A Framework for Smart Buildings and Smart Factories

Nicola Magaletti, Giustina Secundo, Claudia Spilotro, Chiara Tognon et al.
1 citations
Sustainability
Big Data and Business Intelligence
2.28
article

Data-Driven ESG KPIs Optimization: A Framework for Smart Buildings and Smart Factories

Nicola Magaletti, Giustina Secundo, Claudia Spilotro, Chiara Tognon, Angelo Zerega, Ettore Zini
article en
1 citations

Abstract

The growing importance of Environmental, Social, and Governance (ESG) performance across sectors has accelerated the adoption of digital technologies for the continuous monitoring, analysis, and optimization of key sustainability indicators. This study investigates the role of data-driven infrastructures—spanning hardware components (such as Smart Meters, IoT sensors, and Power Quality Analyzers) and software solutions (including Energy Management Systems, Business Intelligence, Digital Twins, and Artificial Intelligence)—in enabling more transparent, adaptive, and evidence-based ESG governance. Despite this trend, the literature remains fragmented, often focusing on isolated technologies and lacking a holistic framework. This study employs a critical literature review to address this gap, guided by the research question: How does the integration of advanced digital technologies contribute to the effective monitoring and optimization of ESG Key Performance Indicators (KPIs)? This approach allows for a comprehensive understanding of the strategic, technological, and operational dimensions involved in scaling such solutions. Findings identify two major application domains—Smart Buildings and Smart Factories—where the integration of digital tools enables a critical shift from static reporting to dynamic, real-time governance, demonstrating tangible benefits for sustainability and resilience. The study concludes by presenting an integrated framework and outlining key implications for practice and theory.

SustainabilityVol. 17(23)
Deloitte (United States) (US), LUM Jean Monnet University (IT), Ospedale San Giuseppe (IT)
Openalex Percentile: Top 8%
Big Data and Business Intelligence
2.28
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Data-Driven ESG KPIs Optimization: A Framework for Smart Buildings and Smart Factories — Nicola Magaletti, Giustina Secundo, et al. · Sustainability (2025) | TGRS Research Map | TGRS