Unlocking the Potential of Supply Chain Digital Twins

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With the rising number of global regulations, sustainability demands and market fluctuations, the need to predict supply chain disruptions, mitigate risks and enhance procurement processes has never been greater. This has given rise to some new approaches to visualizing and managing complex supply chains — a key one being digital twins.

In this article, we’ll delve into the rising role of digital twin technology in supply chain management and how this innovative approach to supply chain optimization empowers organizations to safeguard against a wide range of potential risks, improves cost savings, and ultimately facilitates better long-term decision-making and strategy planning.

The Rise of Supply Chain Digital Twins

Digital twins are virtual models of physical objects, entities or processes that provide dynamic, data-rich representations which mirror their real-world counterparts. Through active monitoring, analysis and optimization, they can be used to enhance the performance of a product by running simulations.

The concept of digital twins dates back to the 1960s when NASA used them during the Apollo 13 mission. These digital representations, created through simulators, were instrumental in assessing and resolving critical issues onboard, ultimately saving lives and preventing a disaster. Since 2003, digital twin technology has gained significant interest and is now a pivotal component of hyper-automation — a top strategic technology trend, according to Gartner.

In recent years, there’s been a surge of interest in the value of a digital twin when it comes to supply chains, products, and weapons systems. In supply chain management, digital twins provide detailed simulation models of existing supply chains for the purpose of conducting scenario analysis. They offer a comprehensive and real-time view of the entire ecosystem, enabling precise decision-making, better risk mitigation and long-term business continuity.

Supply chains are inherently dynamic, influenced by numerous variables like market fluctuations, ESG concerns and geopolitical changes. Identifying and mitigating risks within these complexities can be challenging, and digital twins address this by allowing organizations to map detailed, multi-tier virtual simulation models based on their supply chain processes, current and prospective suppliers, and procurement habits. These simulation models, in turn, use real-time data and external sources to discern interdependencies and vulnerabilities, as well as forecast supply chain dynamics.

Here’s how digital twin technology empowers supply chain leaders and provides a competitive advantage:

  • Enhanced visibility: Digital supply chain twins provide unprecedented visibility into the supply chain. Every node, partner and process can be monitored in real time, enabling swift issue detection and response.
  • Risk mitigation: Digital twins allow proactive risk identification through simulation, aiding in the development of strategies to mitigate potential vulnerabilities posed by geopolitical shifts, natural disasters, or market disruptions. They also help to ensure consistent quality control and minimize supplier risk by giving organizations the visibility to understand common material inputs — enabling procurement leaders to direct their vendors to buy selected materials from trusted, secure and competitive sources of supply.
  • Operational efficiency: Digital twins help to streamline operations and procurement, reduce costs, and minimize friction in vendor onboarding and refreshing processes.
  • Business resiliency: They contribute to building a resilient vendor ecosystem by identifying single points of failure, predicting operational disruptions, and facilitating continuous monitoring and data refreshing.

Optimizing Supply Chain Management with Digital Twins

Digital twins have come a long way since their inception. While primarily used in manufacturing and product development, their application has become invaluable to end-to-end supply chain management. Key advancements include real-time data integration, where digital twins can incorporate up-to-date information from various sources, such as press releases, news reports, bills of materials from technical data packages, commerce records, and other public and private data. The ability to continuously monitor multiple structured and unstructured data sources gives supply chain managers a comprehensive and up-to-date view of their logistics network.

Additionally, digital twins harness advanced analytics, powered by machine learning and artificial intelligence algorithms, to provide actionable insights and predictive analytics. This enables supply chain professionals to make informed, data-driven decisions and optimize their operations.

However, it should be noted that there is no one-size-fits-all approach when it comes to deploying a digital twin of your supply chain ecosystem. The power of an effective digital twin lies in its ability to replicate an organization’s multi-tier supply chain — all the way down to the nth tier, as well as mirror a product and all of its sub-assemblies. This includes all the components and raw materials that go into an end product, such as chemicals, plastics, electronics, or even pharmaceutical ingredients.

“An optimal digital twin solution should utilize creative ways to maintain the freshness and accuracy of the data in the model, so that if a part transitions from one supplier to another, the system will detect the change and prompt the stakeholder to make sure that the data is still valid,” said Derek Lemke, SVP, Product Level Intelligence, at Exiger. “And if there’s a new part introduction — something novel and unique — the system will ideally detect the change and prompt the appropriate stakeholders to incorporate the new bill of materials associated with the item.”

Automation is key, as the alternative to utilizing a digital twin is relying on manual processes and exposing your business to the inevitable risk of human error.

Maintaining data quality and accuracy is necessary for managing a successful digital twin. Having up-to-date records and detailed historical data allows the digital twin to simulate relevant scenarios, which in turn leads to accurate forecasting. Supply chain managers can use these forecasts to optimize inventory levels, supply routes and production schedules, as well as develop strategies to mitigate procurement shortages. Furthermore, this enables better long-term decision-making and strategic planning by allowing supply chain professionals to accurately simulate the impact of decisions in the long run and ensure that their supply chain is adaptable to future market trends and disruptions.

That’s why it’s important for supply chain and procurement leaders to implement a supply chain risk management (SCRM) solution that not only creates a full digital twin of their supply chain ecosystem which provides insight, visibility and control across all supplier tiers, but also addresses gaps in supplier network data without the need for manual intervention.

“An effective approach is to match supply networks beneath a Tier 1 supplier using commerce records, tax receipts and other data sources,” Lemke said. “When mapping interior supplier networks and products that are moving from one entity or economic sector to another, you should be able to invite those vendors into your risk management platform to validate data or provide information that’s missing. Or if they already have the data you need in their ERP, PLM or legacy IT systems, they should be able to send it over for easy integration with your SCRM platform.”

The Key Benefits of Implementing Supply Chain Digital Twins

The adoption of digital twins offers many advantages — transforming how businesses manage their operations. Two key benefits include better cost savings and enhanced risk mitigation:

Improved Cost Savings
Over the last 20 years, most original equipment manufacturers across different industries — from aerospace and defense to oil and gas and telecommunications — have been outsourcing the majority of what they used to make in-house. By designing products and outsourcing the fabrication of the individual components to interior suppliers, they rely on the end-to-end visibility that an efficient third-party risk management platform brings to orchestrate the collaborative purchasing of common materials.

“We’ve seen savings that range from three to 25 percent depending on the material input or material category,” said Lemke. “Material inputs across industries constitute somewhere between 30 and 50% of product costs. Using this visibility to understand common material inputs enables procurement or supply chain leaders to direct their vendors to buy them from vetted competitive sources of supply.”

Standardizing the parts and materials that go into an end product with the help of a digital twin results in organizations being able to capitalize on the economies of scale. By purchasing fewer SKUs at higher volumes, this potentially eliminates minimum order requirements and maximizes discounts.   

Better Risk Management
A digital twin allows supply chain managers to scan and screen suppliers for various legal, regulatory and trade compliance considerations. This helps to identify risk indicators — for instance, if a supplier has a nexus in China relative to forced labor or if dangerous goods are being added to materials or components in the supply chain. Additionally, for organizations that outsource production, a digital twin provides the ability to track any variances in what a supplier should have purchased for the development of the end product, and whether or not the purchases were made with sufficient lead times.

“There are lots of ways to assess operational and product risks, as well as some of the other more traditional risk areas,” said Lemke. “There are almost 300 different risk categories that we monitor, from man-made to natural disaster risks. If there’s a hurricane or flood or power outage or strike, our platform will detect it and alert the appropriate stakeholders to let them know that something has happened that might impede the timely delivery of a part or material that goes into their product, equipment, or weapon system.”

“An optimal digital twin solution should utilize creative ways to maintain the freshness and accuracy of the data in the model, so that if a part transitions from one supplier to another, the system will detect the change and prompt the stakeholder to make sure that the data is still valid.”

Derek Lemke
EXIGER SVP OF PRODUCT LEVEL INTELLIGENCE

Harness the Full Potential of Digital Twins with Exiger

Choosing the right supply chain risk management partner makes all the difference. To optimize your supply chain operations, you can use the 1Exiger platform to create a digital twin of the supply chain ecosystem providing insight, visibility, and control across all tiers to protect your business from risk.

The 1Exiger platform can help you gain visibility into previously unknown supplier risks such as sub-tier supplier concentrations risks, bottlenecks or dependencies; identification of geographic concentration for environmental and geopolitical risk analysis; and export control, tariff, and commerce restriction detection for supply chain planning optimization. Execute effective risk management actions through the advanced and intuitive user interface that drives increased operational efficiencies and stakeholder collaboration across the enterprise.

By utilizing the advanced technology in the 1Exiger platform, you can effectively prepare the data landscape required for a digital twin, thus enabling it to harness its full potential in supply chain management.

Contact us to learn more about how Exiger can help you manage supply chain risks with a digital twin.

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