Object-Centric Process Mining for Semi-Automated and Multi-Perspective Sustainability Analyses

International Conference on ICT for Sustainability (ICT4S), pp. 143–152

Abstract

Current approaches for sustainability analysis face significant methodological challenges in comprehensively assessing impacts across business processes. They are constrained by time-consuming data collection and allocation, inflexible, manually created models, and difficulties in relating impacts to root causes. This paper considers Object-Centric Process Mining (OCPM) as enabler for more dynamic and comprehensive sustainability analyses mitigating these challenges. We explore the integration of sustainability data into the current standard for Object-Centric Event Logs (OCELs) used by OCPM techniques and introduce a prototypical tool to assess impacts based on an OCEL and allocate these impacts to events and objects. We demonstrate how OCPM can support the specification of inventory data, impact assessment, and impact allocation for a semi-automated, multi-perspective sustainability analysis. This exploratory work provides a concrete illustration for sustainability assessment using OCPM, thereby, laying the foundation for further research towards a data and process driven technique to identify and measure company’s negative sustainability impacts more effectively.

Authors 5

1. Nina Graves Aachen Chair of Process and Data Science

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Process and Data Science,Aachen,Germany

2. Andreas Fritsch

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute AIFB,Karlsruhe Institute of Technology,Karlsruhe,Germany

3. Raimund Hensen Aachen Chair of Process and Data Science

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Process and Data Science,Aachen,Germany

4. István Koren Aachen Chair of Process and Data Science

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Process and Data Science,Aachen,Germany

5. Wil M. P. van der Aalst Aachen Chair of Process and Data Science

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University,Chair of Process and Data Science,Aachen,Germany