According to a 2013 research report published jointly by MIT and PwC, over 69% of companies surveyed experienced a supply chain disruption that resulted in a 3% or higher increase in total supply chain costs. Meanwhile, a 2014 survey of supply chain executives conducted by the Global Supply Chain Institute found that “many supply chain execs have done very little to formally manage supply chain risks.”
With so much on the line, why has there been so little focus on supply chain risk mitigation? Until recently, there have been no supply chain-focused risk management tools that enable organizations to manage both catastrophic risks (natural disasters), that result in major supply chain disruptions, and operational risks (port congestion), that destroy supply chain performance by a thousand cuts.
Download this white paper to learn how real-time big data and machine learning are enabling transformative new capabilities for risk detection, mapping, visibility and fast response:
- Dynamically discovering and modeling all nodes, facilities, assets, trading partners and customers in the end-to-end supply chain, continuously
- Enabling real-time visibility into unfolding interdependent risks and disruptions
- Performing dynamic, frequent assessments of risks unfolding in real-time and those predicted to occur based on behavioral modeling
- Producing prescriptive recommendations for risk remediation, and facilitating intelligent actions