EXPLORATORY ANALYSIS OF TRANSACTIONAL DATA TO AID IN THE SUPPLY CHAIN NETWORK DESIGN OF A FOOD BANKING NETWORK

• Ane Janse van Vuuren Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa https://orcid.org/0009-0008-3030-9152
• Euodia Vermeulen Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa https://orcid.org/0000-0002-5732-2428
• Christopher Mejia Argueta Center for Transportation and Logistics, Massachusetts Institute of Technology, Cambridge, United States of America https://orcid.org/0000-0002-4601-2459
• Sara Grobbelaar Department of Industrial Engineering, Stellenbosch University, Stellenbosch, South Africa | DST-NRF CoE in Scientometrics and Science, Technology and Innovation Policy, Stellenbosch University, Stellenbosch, South Africa https://orcid.org/0000-0002-2793-9689

DOI:

https://doi.org/10.7166/35-2-2986

Abstract

This article applies a network lens to transactional data in order to improve a food banking network's supply chain design and planning. This study draws on data from FoodForward South Africa. This food bank has compiled a rich dataset of connections between supply chain partners (e.g., donors), the flow of stock (volume of food), and their beneficiary organisations. Our analysis showed an increase in the system's 'moving parts' (increased handling of donations), resulting in a significant imbalance between supply and demand. Additionally, in 2022, the organisation's warehouses received a larger number of smaller-volume donations from a wider variety of suppliers, placing an extra burden on the network.