COVID 19 showed us that it was imperative that suppliers' assessments used by companies evolve into being more predictive. Supply Chain Risk Resiliency is a term that encompasses that idea and attempts to address questions such as "How do we make sure that in times of crisis my suppliers will come through?" or  "How do we identify suppliers  that will not be able to deliver due to various existing constraints?" and "What are those constraints?"

The intent of this project was therefore to develop an approach to evaluate and report Supply Chain Risk Resiliency using R Shiny for data modeling and visualization. Successful advances in the project required following an Agile methodology and working closely with stakeholders to clearly understand their vision and at times help them conceptualize that vision.


Critical Tool Features
 
1. Dynamic scoring model that allows apple to apple resiliency comparisons between suppliers.
2. Filtering system which allow user to focus on very specific type of suppliers

Due to the confidential nature of the data used to complete the project the tool will not be shared