Using risk modeling to build supply chain resilience
In supply chain, analytical risk measurement models can explore the likelihood of suppliers shutting down, spot inventory handling and order fulfillment risks, and track customer behavior patterns. The models also consider demographic profiles to predict risks associated with worker safety, order fulfillment, and customer satisfaction. This helps businesses make more strategic procurement, capacity planning, and worker safety decisions.
AI and ML algorithms for designing multi-tier supplier clusters also give a geo-spatially prioritized view of suppliers' on-time fulfillment capabilities. In this way, they can identify alternative suppliers in regions less impacted by COVID-19 if necessary.
While exploring new risk models, businesses also need to mobilize their digital and analytical teams to develop solutions to support other strategic priorities.