E2E Risk Guru: A digital twin for supply chain resilience in life sciences


Resilience is considered a key success factor for supply chain management in the coming years. Not surprisingly, a vast majority of supply chain leaders in life sciences plan to increase resilience. Key objectives for many companies are to better manage global supply risks and combat drug supply shortages.


Why traditional risk management struggles

However, also showed why the pandemic showed why traditional risk management practices in supply chains often struggle:

  • The probability trap: Traditional risk models require highly subjective judgment (e.g., type and the probability of risk), which renders them often impractical to use.

  • Struggling to quantify end-to-end risk exposure: The complexity of global supply chains prevents companies from quantifying risk exposure and detecting emerging drug shortages.

  • Failing to identify weak links: The pandemic showed the risk of overlooking weak links as non-drug nodes (packaging materials, excipients) became critical.

  • Poor optimization of risk strategies: Manually evaluating risk strategies such as dual sourcing and risk inventory is overwhelming, while simple heuristics may lead to poor results.

 
 

Focus on supply chain vulnerability

Therefore, new supply chain risk management approaches focus on managing and limiting the impact of potential disruptions. Instead of trying to identify each and every possible disruptive event and estimating its impact and probability, they aim to analyze a supply chain’s vulnerability. Modern supply chain analytics play a prominent role in implementing this type of risk analysis. Digital twins – computerized models of a supply chain – provide the means to assess supply chain vulnerability and risk exposure.


E2E Risk Guru: A holistic approach for managing risks and increasing resilience

The E2E Risk Guru solution provides analytics for analyzing risks and optimizing resilience in supply chains. It provides easy to understand risk metrics based on standard supply chain data that are commonly available in ERP and planning systems. Based on a pragmatic digital twin and prescriptive analytics tailored to supply chains in life sciences it allows to:

  • Identify Risks: Find hidden risks in your multi-tier supply chain.

  • Evaluate impact: Understand the financial and operational impact of disruptions.

  • Optimize Resilience: Simulate changes and optimize (risk) inventory and mitigation measures.


Please contact us if you are interested in a demo or pilot study. More information is available here.