Data Analytics in Sustainability Performance Measurement
Metric design, benchmarking, trend analysis, and decision-support methods for measuring sustainability performance.
Sustainability performance cannot be evaluated through isolated indicators alone. Energy intensity, emission trends, water use, waste reduction, supplier performance, and social indicators need to be interpreted together.
Research questions
- Which metrics best represent actual performance?
- Which variables explain increases in emissions or resource use?
- Are there meaningful differences across locations, facilities, or periods?
- What causes the gap between targets and actual performance?
Analytical methods
Trend analysis, normalization, segment comparison, correlation analysis, and anomaly detection help clarify sustainability performance. Decision quality improves when qualitative assessment and quantitative analysis are used together.
Value
Data analytics moves sustainability work beyond reporting. Organizations can better see which actions create impact, which areas carry risk, and where resources should be directed.