Supply Chain Network Performance Optimization

Nowadays, businesses are faced with an overwhelming amount of data. Companies are using data-driven solutions to improve decision making and stay competitive, especially in the supply chain industry where data management and analysis can improve operations and reduce costs. Accenture is no exception. As the amount of data increases, some internal libraries have become the bottleneck for large size client projects. In this work, we aim to improve the performance of the Network library used for generating graphs from supply chain data. Research is conducted on two popular graph tools (NetworkX and Neo4j) to find a suitable alternative. Results show that NetworkX offers a good balance between execution time and memory usage while Neo4j has fast query performance but high memory usage.