By Pietro Negri and Tommaso Cesati
In today’s rapidly evolving supply chain landscape, advanced technologies like digital twins are making waves by providing unprecedented visibility and actionable insights. At the forefront of these advancements is SCNODE, a pioneering open-source initiative focused on advanced digital topics in supply chain management, specifically in manufacturing and logistics. Here’s a deep dive into the recent presentation by SCNODE at the Gemini Call that explores their mission, the power of digital twins, and real-world applications in sustainability.
Introducing SCNODE: The Mission
SCNODE stands for Supply Chain Node, but it’s much more than a catchy acronym. As highlighted in the introduction of their presentation, SCNODE is an open-source platform dedicated to the exchange of information on advanced supply chain topics. The mission behind the project is twofold:
- Building a Community: SCNODE aims to foster a network of supply chain professionals and enthusiasts interested in cutting-edge technologies like simulation, data analytics, and digital twins.
- Raising Awareness: Many people misunderstand advanced technologies, particularly when it comes to their deployment and the added value they offer. SCNODE empowers its community to share knowledge and raise awareness about these critical topics, making them accessible to a broader audience.
What makes SCNODE unique is its open-source approach, meaning anyone with expertise or interest in these areas can contribute to the platform, creating a dynamic, collaborative environment. By providing a space where professionals and organizations can learn and share, SCNODE democratizes access to advanced supply chain knowledge and solutions.
Unpacking Digital Twins: Scope and Functionality
One of the key technologies SCNODE emphasizes is digital twins, but understanding their full potential requires breaking them down into scopes and functionalities. SCNODE has chosen to focus primarily on simulative and prescriptive digital twins—the more advanced types that go beyond just monitoring systems in real-time or predicting future states based on historical data.
Simulative Digital Twins
Simulative digital twins allow businesses to test different scenarios in a risk-free, what-if environment. This is particularly valuable in supply chain operations where uncertainty reigns supreme. Instead of relying on gut instincts or oversimplified models, supply chain managers can run detailed simulations to see how specific changes—like a new supplier contract or route optimization—might affect overall performance.
Prescriptive Digital Twins
On the other hand, prescriptive digital twins take things one step further by offering actionable insights. These systems do not merely predict outcomes; they prescribe corrective actions that would lead to the desired goals. This feature addresses one of the main limitations of machine learning (ML) black-box models, where decision-makers can’t always understand the reasons behind an ML model’s predictions. Digital twins, in contrast, provide clarity by making the behavior of a system visible over time and showing how corrective actions can guide the system toward improved performance.
Why Are Digital Twins Relevant to Supply Chains?
Supply chains, by their nature, are complex and dynamic systems that evolve constantly. Decisions made at any point can have a ripple effect on the rest of the network, making it difficult to predict outcomes with certainty. This is where supply chain digital twins come into play.
Tackling Uncertainty and Complexity
As highlighted in the presentation, supply chains are far from being deterministic. A simulative approach provides much-needed clarity by helping managers better understand system behavior and how different elements interact. With this knowledge, businesses can align and synchronize their operations, mitigate the impact of events, and identify bottlenecks that hinder efficiency.
Moreover, digital twins offer the unique advantage of analyzing potential scenarios and preparing for various challenges, from disruptions in transportation to shifts in customer demand. By using simulative digital twins, supply chain professionals can develop resilient and adaptable strategies, ensuring that their operations remain efficient, even in the face of unpredictable changes.
The Power of Modularity: From Local to Global
Another key takeaway from SCNODE’s presentation is the modularity and scalability of simulative digital twins. Whether a company wants to optimize a single workstation or analyze a global supply chain impacted by geopolitical events, digital twins can be customized to fit any scope or complexity. This flexibility allows enterprises and policymakers alike to address an endless list of critical questions regarding supply chain assets and nodes.
Policy makers, in particular, benefit from simulative digital twins as they study the impacts of trade policies, geopolitical shifts, and global competition. For enterprises, the digital twin approach can help with cost-saving initiatives, right-sizing assets, and making more informed decisions regarding their supply chain operations.
Real-World Application: Digital Twins for Supply Chain Sustainability
After SCNODE co-founder Tommaso Cesati introduced the project, the presentation was handed over to Pietro Negri, who shared a compelling case study on how digital twin technology can drive supply chain sustainability.
The Case Study: Dairy Supply Chain in Italy
Pietro walked the audience through a real-world application of digital twins in the dairy industry in Italy, where they worked with a yogurt manufacturer. The objective was to enhance sustainability performance without negatively impacting the company’s financials—a critical balance for many businesses today, especially with the introduction of regulations like the European CSRD (Corporate Sustainability Reporting Directive).
By creating a digital twin of the manufacturer’s supply chain, SCNODE and the client were able to estimate the company’s current carbon footprint and financial performance. From there, they tested various sustainability alternatives, such as adjusting packaging, modifying transportation methods, and restructuring the distribution network.
After testing three different sustainability scenarios over five years, the digital twin simulation revealed several opportunities for emissions reductions and cost savings. One notable outcome was the resizing of the distribution network for finished yogurt, which helped reduce stock levels and minimize the volume of expired products—a critical issue for perishable goods. This alone led to a 10% reduction in emissions and a 5% increase in EBITDA.
The simulations also provided clear, data-driven targets for the company’s sustainability strategy, helping management prioritize the most effective measures while strengthening the business’s financial performance.
SCNODE’s Future Initiatives: Building a Sustainable Supply Chain Network
The presentation ended with the presentation of SCNODE’s future plans, including expanding their virtual and physical presence through thematic roundtables, case study publications, and educational events. These initiatives aim to further build the SCNODE community, fostering collaboration and continuing the conversation around digital twins and their role in sustainable supply chain management.
Conclusion
Digital twins are reshaping the future of supply chain management, offering companies the tools they need to better understand, predict, and optimize their operations in real-time. SCNODE is at the forefront of this movement, providing an open-source platform for collaboration and innovation. With a commitment to sustainability and practical real-world applications, SCNODE is not just unlocking the future of supply chains but also making sure they evolve to meet the challenges of the modern world.
Watch the Gemini Call Presentation
Want to see how these insights were originally shared with the Digital Twin Hub community? Watch my Gemini Call presentation where Pietro & Tommaso delivered his presentation:
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