Authors: Clara Valente and Mehrdad Ghorbani Mooselu
It is crucial to propose and discuss digital solutions to make Social Life Cycle Assessment (S-LCA) easier for industries to implement. The increasing interest in social sustainability and the lack of accessible and time-saving digital solutions for companies to streamline and quantify S-LCA necessitates developing digital solutions for collecting, systematizing, and analyzing sustainability data.
The main goal of the SoBOS project is to facilitate achieving social sustainability goals for companies through easy and time-saving solutions that visualize the impact of implemented measures and include automatic data harvest, machine learning, the use of digital twins, and big data.
The indicators related to Workers and Local communities were prioritized for data collection, including quantitative and qualitative indicators. Our findings suggest that quantitative metrics are more likely to be integrated into the digital system. In contrast, qualitative indicators exhibit variations in definitions across industries, resulting in a broader spectrum of focal areas.
Social aspects given precedence in this study, such as work-life balance, the physical and psychological well-being of employees, and the promotion of diversity in various manifestations, are more challenging to integrate into a digital framework.
Limitations for different indicators and data collection possibilities were discussed with Grayn and involved industrial partners.