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Take fast supply chain action with analytics

Identify vulnerabilities and solutions through modeling

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Vial and Syringe A harsh spotlight on supply chain vulnerabilities has been one effect of the COVID-19 crisis. Unfortunately, only about 12% of attendees at a recent life sciences event actually understand their organization’s specific exposure. They and the others learned more about recognizing causes and taking the steps necessary to manage their risks. The key, presenters made clear, is regular, in-depth predictive modeling.

Recognize primary risks An organization’s supply chain and its operations, growth, financial performance and shareholder value are impacted by government through new regulatory and statutory requirements, trade policies, tax changes and legislation. Nongovernmental factors that reduce supply chain reliability and increase supply chain costs include the proliferation of multichannel sales, cannibalization of demand and transportation aspects such as higher fuel costs, as well as pandemic-related labor shortages, trade route disruptions, supplier failures and production issues.

Use predictive modeling to point to solutions Jonathan Eaton"The companies with the best performing supply chains use predictive analytics and advanced modeling to proactively manage all aspects of their supply chains."

— Jonathan Eaton
Leader, National Supply Chain Practice
“Predictive modeling offers early insights into changes within the supply chain and how they impact financial and operational performance,” said Jonathan Eaton, leader of Grant Thornton’s National Supply Chain Solution. “The companies with the best performing supply chains use predictive analytics and advanced modeling to proactively manage all aspects of their supply chains.”

The case is made, Eaton said, in the Gartner Supply Chain Top 25 for 2020. Of the top 25 supply chains, over 20 have one very telling thing in common — they have modeled and optimized their physical supply chain to address the number one supply chain issue facing most companies, which is rapidly rising supply chain cost to serve. In fact, most of these companies use a digital twin of their supply chain to model their supply chain so they can proactively adapt it as challenges arise or excess cost appears. “A digital twin,” Eaton explained, “is a living, breathing model of your supply chain that’s rooted in data, with sophisticated algorithms, machine learning and artificial intelligence that allow you to know, based on scenarios and simulations, what may happen with your supply chain before it happens. The idea is to understand cost-to-serve trends and take action faster than your competitors to achieve sustainable competitive advantage.”

Robert Shea"I think at some point we'll see a wholesale examination of the nation's healthcare industrial complex to give a sense of what life sciences companies can do to improve their identification and mitigation of risks to improve business continuity."

— Robert Shea
National Managing Principal, Public Policy
One analytical tool focuses on qualitative assessments for building resilience. It identifies four major failures in understanding:

  • Liquidity and cash flow needs
  • Cash management
  • Changes to supply and demand
  • Projection of demand

In studying its failures, an organization can model answers to critical questions. Will demand go up or down? Will it come through historical or new channels? Will our suppliers be able to meet our needs? With the answers, the organization can take steps toward solutions.

Going forward, success depends on a greater emphasis on technology and a firm position at the intersection of supply chain and enterprise risk management.

Contacts:

Jonathan EatonJonathan Eaton
Leader, National Supply Chain Practice
T +1 704 632 3523


Robert SheaRobert Shea
National Managing Principal, Public Policy
T +1 703 637 2780