Methodology for material flow analysis at the organizational scale

Organizations play a crucial role in facilitating the transition to a circular economy. Implementing circular practices often begins with a material flow analysis (MFA) to identify issues and opportunities. However, existing MFA methodologies focus mainly on territorial applications and lack effectiveness at the organizational level. Conducting MFA at this level presents distinct challenges, requiring insights into dynamic material circulation and effective handling of heterogeneous data. Addressing this gap, this study introduces an innovative methodology tailored to organizational contexts. The developed methodology consists of six steps for conducting MFA while proposing an archetype-based approach capable of analyzing extensive and disparate datasets, coupled with bootstrapping and Monte Carlo simulation techniques, that considerably reduces the complexity of MFA execution. Furthermore, this methodology enables a comprehensive understanding of material flows within the system and provides a straightforward method for estimating uncertainty in mass estimations by incorporating confidence level calculations. A case study from a governmental organization is used to illustrate the proposed methodology. • Clarifying the steps to perform Material Flow Analysis at the organizational level proposed. • The archetype approach enables to analyze a large amount of heterogeneous data. • This approach reduces processing time while maintaining a suitable level of accuracy. • Bootstrapping and Monte Carlo Simulation (MCS) are utilized to enhance this approach. • A straightforward technique for measuring uncertainty based on MCS.