Disruptions and instability within global supply chains have been the subject of intense media focus in the wake of the ongoing COVID-19 pandemic. Shortages of raw materials, ingredients, components, and certain finished goods are impacting daily life. Supply chain issues are not specific to any one industry, but global supply chain shocks are occurring more frequently and have a bigger impact on organizations than ever before. Visibility remains a key supply chain technology component, but expanded capabilities now move beyond that by deploying digital twin technology, enabling companies to digitize their entire end-to-end supply chains, embed intelligence and automation, optimize operations and increase on-time in-full (OTIF) delivery.
The costs of disruption are significant, too. In the pharmaceutical sector, the industry stands to lose an average of 24 percent of one year’s EBITDA every ten years due to supply chain disruptions. Clearly, this is not good business, nor is it sustainable in the long term. Companies must identify risks and vulnerabilities right away, and then adapt their plans and supply chain operations to mitigate these issues so they can course-correct as soon as possible. Ideally, organizations should have enough data-driven visibility and intelligence embedded into their supply chains to take preemptive steps rather than scrambling to find a solution. Alleviating supply chain challenges begins with gaining visibility into the end-to-end supply chain, then applying intelligence and automation to the workflow, allied to systems that manage risk and volatility.
Creating More Resilient Supply Chains
Across the whole ecosystem of customers, suppliers, and transportation modalities, new tools and technologies are fast emerging in the cloud to help build better, more resilient supply chains. There are three fundamental elements that, combined, will drive tangible improvements in real-time supply operations and help minimize the effect of disruption.
- Create digital twin models of supply chain networks, enabling real-time operational modeling and monitoring.
- Leverage actionable intelligence to anticipate problem scenarios, incorporate ground truth into operations, and automate response to potential disruptions.
- Empower partners and suppliers to collaborate and optimize the ecosystem to coordinate supply chain operations at all stages. This includes monitoring all assets and inventory throughout the supply chain to continuously align planning and execution with ground truths to improve service levels.
Advantages of Digital Twin Technology
#1: Virtual Representation
Digital twin technology provides a virtual representation of the entire supply chain ecosystem—a virtual map of assets across operations and business processes that is built from vast amounts of accessible, real-time, ground truth data flowing across connected systems. Historically, digital twins were associated more with static analysis, but now the concept is being operationalized to track many dependencies to mitigate risks, automate workflows and corrective action, and drive better supply chain resilience.
#2: Data Intelligence
Digitizing the supply chain using digital twins allows all constituents to be constantly monitored at multiple levels, including attributes, configuration, and metadata. Deep signal and data intelligence can be generated from any entity, system, or device—from containers and pallets right down to individual unit boxes, bottles, and vials—and shared via interactive dashboards in real-time. The resulting thread of connected data allows organizations to overcome data and organizational silos—within their own company and across every other organization involved in the supply chain—and truly understand how well the entire supply chain is performing on a minute-to-minute basis.
Embedding deep data intelligence into these digital twin models builds transparency. This creates approved cross-organizational collaboration across all partners in the ecosystem. Any variance or disruptions to the plans can be identified and flagged quickly. Partners can identify and resolve subpar performance or deviations in any aspect of the supply chain, thereby improving resilience. Predictive modeling is also possible with digital twins. So, organizations can virtually model and test what-if scenarios where disruptions may occur, with potential actions and outcomes outlined. Now, organizations can prepare contingency plans for supply chain failures, disruptions, and supply-demand fluctuations.
Since secure components of digital twins can be shared with suppliers and other partners in the ecosystem, continuous realignment, collaboration, and communication are possible across every organization and constituent involved, regardless of location. Digital twins can be easily extended across these networks with AI/ML and low-code/no-code scripts that help drive predictive intelligence and automated workflows across the entire supply chain. Furthermore, networks of digital twins can be extensible, with more components added to the supply chain infrastructure that can provide the visibility required to highlight duplicate dependencies and sources for any given element, regardless of whether a supplier is one or more levels removed from the core. So, with a network of digital twins, there’s a common node where the risk of duplication of effort can be identified and removed. This serves to streamline and improve overall supply chain efficiencies.
The Future of Supply Chain Issues
Supply chain disruptions are here for the foreseeable future, and this is prompting more investment in solutions that drive greater resilience and agility to supply chain operations. Digital twins free organizations to innovate faster and on a larger scale while reducing risk by identifying points of weakness and driving strategic initiatives to reduce cycle time. They can greatly reduce some of the uncertainty that exists in supply chain operations today. Organizations can use digital twins to increase their competitive edge through efficiencies gained from better insight into sourcing, manufacturing, inventory locations, and logistics tracking—even at the individual item level.
- Asset Tracking
- Equipment Tracking
- Freight and Package Tracking
- Industrial Internet of Things
- Supply Chain and Logistics