A Framework for Sustainability Performance Measurement Through Process Mining: Integration of GRI Metrics in Operational Processes
Organizations face significant challenges in measuring and enhancing sustainability performance across complex operational processes. Current assessment methods frequently lack granularity, real-time capability, and integration with operational data. This study addresses these gaps by developing a c...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/7/547 |
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| Summary: | Organizations face significant challenges in measuring and enhancing sustainability performance across complex operational processes. Current assessment methods frequently lack granularity, real-time capability, and integration with operational data. This study addresses these gaps by developing a conceptual framework that integrates business process mining with Global Reporting Initiative (GRI) metrics. The methodology incorporates environmental, social, and economic sustainability indicators into process mining techniques through systematic metric mapping and event log enrichment. The framework enables the extraction and analysis of sustainability performance data at the process level, creating detailed heat maps that visualize resource utilization, emissions, and waste generation. An application to a Purchase-to-Pay process case study demonstrates how process variants impact sustainability metrics differently. Delays increase emissions by 16.7%, while rework increases waste generation by 41.7%. The results identify specific process bottlenecks with high environmental impact and reveal critical misalignments between economic and environmental sustainability goals. This framework provides organizations with a standardized yet flexible approach to measuring sustainability performance, bridging the gap between high-level sustainability reporting and operational processes. It enables continuous monitoring, targeted interventions, and transparent reporting across diverse industry contexts. |
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| ISSN: | 2079-8954 |