From Deloitte’s “Future of Supply Chain“ to the future of manufacturing
At a time when global manufacturing is navigating increasing complexity, supply chain management has moved firmly into the spotlight. Disruptions in recent years have shown how essential resilient, connected and intelligent supply chains are – not only to keep production running, but to remain competitive.
At Deloitte’s “Future of Supply Chain“ event in Zaventem (Belgium) beginning of April, industry leaders came together to explore how emerging technologies, data and collaboration are reshaping the landscape. Siemens was actively engaged in these conversations, contributing its perspective on how supply chains and manufacturing must evolve together. Following the event, we spoke with Magnus Rasmussen and Mitchel Jacobs from Siemens Digital Industries Software to capture their perspectives.
Meet the experts
Magnus Rasmussen brings more than a decade of experience in supply chain design and execution, complemented by work in process automation using computer vision and artificial intelligence (AI), particularly in warehousing and transportation. At Siemens, he is responsible for the Digital Logistics and Intra Plant Logistics portfolio across key European markets.
Mitchel Jacobs has close to 20 years of experience in the manufacturing industry. Starting his career as an electrician on the shop floor, he has developed a deep, hands-on understanding of shop floor operations. Today, he leads digital manufacturing initiatives in the BeNeLux region, focusing on connecting manufacturing execution, planning, logistics and data-systems.
Together, they combine strategic perspective with practical industry insight – bridging technology and real-world manufacturing challenges.
What made this year’s event particularly relevant?
Magnus: The event is very forward-thinking. It’s about looking into the future and aligning your strategic direction with real solutions that already exist in the market. What makes it valuable is the combination of thought leadership and practical insight – learning from others in the industry, understanding what works and what doesn’t, and seeing where companies are on their journey with AI and data integration.
The format supports that well: a central auditorium with presentations and discussions, combined with opportunities to engage directly with peers and solution providers. It’s designed to inspire, but also to help participants translate that inspiration into their own strategies.
Mitchel: What stood out to me – already last year and again this year – was how real-world examples bring these concepts to life. For instance, insights from high-performance environments like F1-teams show how data-driven decision-making can significantly improve performance. These examples can serve as a blueprint for manufacturing companies looking to enhance competitiveness. It proves that digitalization is not a thing of the future, but a powerful tool to strengthen the competitive position now.
What key trends emerged from the discussions?
Magnus: AI was present in nearly every discussion, but the conversation has evolved. It’s no longer about AI as a buzzword – it’s about concrete use cases and how to apply AI in an industrial context.
A key focus now is data integration. To make AI work in practice, you need clean, connected and actionable data. That means breaking down data silos and building a solid data foundation. Digital twins play an important role here, as they bring together different data streams and enable meaningful use of AI in operations.
Mitchel: From my perspective, many solutions presented across the market appear similar at first glance – everyone has a sleek dashboard nowadays. However, the real difference lies “under the hood” in how the underlying data and systems are connected and what value they deliver in practice. That’s where the focus should be – on the core technology and how it enables real outcomes. Without that seamless connection between the shop floor and the office, AI remains just a “shiny toy” rather than a transformative tool.
What role does supply chain management play in modern manufacturing?
Mitchel: If I look back, my perspective on manufacturing started very early. As a child, I spent time in factories with my father, who worked as a maintenance engineer on the shop floor. I watched fine-tuned machines by ear, focused on quality, and continuously improved processes. That mindset – of always improving – has stayed with me throughout my career.
Decades later, after visiting over 2,000 factories, I see that same drive, but the tools have changed. The biggest barrier today isn’t a lack of will; it’s that vital information is trapped in disconnected pillars. We are still trying to “fine-tune” the engine, but we are doing it with one eye closed because the data doesn’t flow between departments. By breaking down these silos and connecting the shop floor to the top floor, we don’t just improve a single machine – we build a resilient supply chain that can react instantly to global disruptions.”
What we can do today is connect those silos. By bringing data together, companies can make faster and better decisions – and that is ultimately what builds a more resilient and effective supply chain.
Magnus: Supply chain management is increasingly recognized as a foundational capability. Real-time visibility and data integration are key, but the real question is how to act on that information. For example, if there is a disruption in inbound logistics, how does that impact production? Connecting logistics with manufacturing allows companies to understand these dependencies and respond effectively.
There is also a growing focus on resilience. Companies are rethinking supplier strategies, inventory levels and overall supply chain design to ensure continuity in a volatile environment. Warehousing and transportation are no longer seen as stand alone verticals – they are part of one interconnected system that includes production and manufacturing.
How does Siemens connect supply chain management and manufacturing?
Mitchel: Across the many factories I’ve visited, one common theme is continuous improvement. But what often limits progress is that data remains trapped in silos.
What Siemens enables is connecting those silos – linking shop floor data, manufacturing execution and enterprise systems to create a consistent and usable data foundation. This allows companies to move from isolated improvements to true end-to-end optimization – or as we call it: closed-loop manufacturing.
Even more importantly, we are using AI to capture “Tribal Knowledge.” We can take the 20 years of experience from a veteran operator – who knows that a certain “ticking” sound means the machine should run 5% slower to avoid a breakdown – and feed that into the system. We are not just connecting data; we are digitizing human intuition to shorten the learning curve for the next generation. That is how you build true resilience.
Magnus: What differentiates Siemens is the ability to connect the full stack – from hardware to software. Reliable data flows depend not only on IT systems, but also on how data is generated on the shop floor.
By combining these layers, Siemens creates a coherent data environment that supports both operational execution and strategic optimization. This is essential for enabling industrial-grade AI – because without high-quality, connected data, AI cannot deliver real business value.
Ultimately, this integrated approach allows companies to link supply chain decisions directly to manufacturing outcomes, creating a closed-loop system that improves performance, resilience and agility.
What are your key takeaways from the event?
Magnus: There is a clear shift happening. Over the past years, companies have focused on automating individual processes and collecting data. Now, the challenge is that this data is often disconnected. The focus is shifting toward building a coherent data and IT architecture – connecting data silos, ensuring data quality and making data actionable. This is the foundation for effectively leveraging AI.
Another important aspect is the increasing focus on geopolitical uncertainty. Supply chain leaders are actively looking for ways to test scenarios and improve resilience. Simulation capabilities are becoming critical for evaluating different strategies without impacting real operations.
Mitchel: My biggest takeaway is that we need to stop talking about technology in isolation. Software doesn’t run a factory; people do. But we are at a crossroads: if we continue to give our workforce complex, fragmented tools, we will lose them.
The future of digital manufacturing belongs to the “Worker.” We must provide technology that feels as intuitive as the apps on their smartphones – tools that don’t add to their workload but remove the “mental load.” At the end of the day, our success isn’t measured by how many sensors we install, but by how much more confident and efficient a technician feels when they walk onto the shop floor. That is the only way to build a supply chain that lasts.
Looking ahead: What defines the future of supply chains?
The discussions at the event highlight a clear direction: supply chains are becoming more connected, data-driven and resilient. The ability to integrate data across systems, act on real-time insights and simulate future scenarios will be essential.
At the same time, one message stands out clearly: technology is only part of the equation. While AI and digital twins are powerful enablers, their true value depends on how they are applied by people. Expertise, experience and decision-making remain central. Rather than replacing people, these technologies augment human capabilities – helping teams make faster, more informed and more confident decisions in increasingly complex environments.
For Siemens, this means continuing to focus on connecting the full value chain – from hardware to software, from shop floor to top floor – while empowering people to unlock the full potential of data and technology.
As the manufacturing landscape continues to evolve, supply chain management is no longer a supporting function. It is a strategic capability – one that combines technology and human insight to drive resilience, performance and sustainable success.
Frequently Asked Questions
What is the main shift in supply chain management today?
The focus is moving from isolated process optimization to connected, end-to-end systems with integrated data and a coherent IT architecture.
Why is data integration so critical?
Because AI and advanced analytics depend on clean, connected and actionable data. Without it, meaningful insights and automation are not possible.
How are supply chains and manufacturing connected?
They are increasingly part of one system. Decisions in logistics directly impact production – and vice versa – requiring integrated visibility and coordination.
What differentiates Siemens’ approach?
Siemens connects hardware and software across the entire value chain, enabling consistent data flows and supporting closed-loop optimization from shop floor to supply chain.
What role does AI play?
AI enables better predictions, simulations and decision-making – but only when built on a strong data foundation and integrated into real operational processes.
Will AI replace people in manufacturing?
People remain central. AI enhances human decision-making by providing better insights, but expertise and experience are still essential for successful operations.
What defines a future-ready supply chain?
A future-ready supply chain is connected, resilient, data-driven and closely integrated with manufacturing – supported by technology and empowered by people.
