In an era defined by global volatility – from geopolitical conflict and inflation to pandemic-induced factory shutdowns – the logistics sector has emerged from behind the curtain and into the spotlight. Once an invisible infrastructure powering commerce, supply chains are now headline material. However, visibility does not always mean clarity. As goods move across fragmented systems and sovereign boundaries, so does the data meant to track them. Today’s global supply chains are data-intensive but rarely data-integrated.
At the core of this fragmentation lies the challenge of interoperability – the capacity for independent systems to communicate, exchange, and interpret data reliably. As logistics digitalizes, systems like ERP (Enterprise Resource Planning), WMS (Warehouse Management System), and TMS (Transportation Management System) must interact seamlessly via interfaces like APIs and EDI protocols. Yet, many operate in silos, using incompatible standards, data schemas, and legacy infrastructure. These technical gaps are compounded by a lack of trust, reluctance to share data, and regional fragmentation of governance and regulation.
Artificial intelligence (AI) and predictive analytics are increasingly touted as solutions to supply chain turbulence. In theory, AI can forecast demand spikes, pre-empt disruptions, and optimize transport networks in real time. But – without foundational interoperability – standardized formats, trusted exchanges, clean data – AI is limited to isolated gains. AI thrives on data; fragmented data ecosystems produce fragmented intelligence.
Towards Automation and Autonomous Supply Chains
Imagine that by the period 2025 – 2035, the logistics landscape has been entirely transformed by AI-driven automation and autonomy. What began as isolated pilot projects has evolved into comprehensive, end-to-end AI integration across planning, warehousing, and transportation. In this future, digital twins—virtual replicas of entire supply networks – are commonplace, allowing companies to simulate everything from demand surges to disruptions like factory fires well in advance, thereby refining contingency and risk mitigation strategies before crises strike. Meanwhile, warehouses and factories have reinvented themselves into dynamic hubs where AI coordinates fleets of autonomous mobile robots and automated guided vehicles, optimizing storage slotting and synchronizing operations in real-time for unprecedented productivity. On the transportation front, advanced AI systems continuously re-route trucks based on live conditions, secure backhaul loads to eliminate empty miles, and intelligently consolidate shipments, marking a dramatic shift from today’s partly manual processes to a fully automated, efficient environment
Wolfgang Lehmacher
Enter Wolfgang Lehmacher. As the former Head of Supply Chain and Transport at the World Economic Forum and co-founder of the Supply Chain Innovation Network, and Logistikweisen, Germany, Lehmacher has long had a panoramic view of global logistics – from port yards to boardrooms. In conversation, he stresses that the key to resilience lies not only in technological sophistication but also in collaboration, ecosystem thinking, and practical implementation of interoperable standards. He likens logistics today to a jazz combo: improvisational, layered, and complex. Everyone plays their part, but without harmony, there’s dissonance.
In the interview that follows, Wolfgang Lehmacher offers a candid perspective on today’s logistics challenges: how de-globalization intersects with systems-level inefficiencies, why predictive analytics alone can’t solve carbon emissions, and what kind of innovation -cultural as much as technical – is required to redesign supply chains for a turbulent future. His views dovetail with the research evidence: that building intelligent, AI-powered supply chains requires not just algorithms but alignment—between systems, stakeholders, and strategies.
The following interview with Wolfgang Lehmacher was conducted on March 13, 2025, and has been edited for clarity and brevity.
Dr. Cowin: How would you describe the evolution of logistics since your 2013 book metaphorized it as a conductor leading an orchestra?
Wolfgang Lehmacher: I still believe in the collaborative essence of logistics, like a conductor uniting various players to deliver a coherent performance. But today, I might compare it more to a jazz combo—improvisational, fragmented, and driven by individual expression. The world has become more volatile, and logistics reflects that—more dissonance, more unpredictability.
Dr. Cowin: What do you mean by a “jazz combo” in the context of supply chain logistics?
Wolfgang Lehmacher: In a jazz combo, everyone plays their own instrument, but they still have to produce a sound that meets audience expectations. In logistics, that means coordinating complex global movements where compliance disruptions—like a change in regulation overnight—can throw everything off. One wrong note can be a dual-use classification that halts a shipment. It’s increasingly fragmented, and that improvisation is the new reality.
Dr. Cowin: You mentioned predictive analytics and anticipatory shipping back in 2018. Has it lived up to its promise?
Wolfgang Lehmacher: It’s progressing. But the world has become more fragmented – imagine multiple “jazz combos” now. There’s the Russian “shadow fleet,” the Chinese logistics ecosystem, and others that don’t communicate with each other. Predictive analytics exists, but it’s only as effective as the data sharing and standards behind it. Interoperability remains a major hurdle.
Dr. Cowin: What role do communication standards play in global logistics?
Wolfgang Lehmacher: They’re crucial. A standard is like a common language. Without it, systems don’t talk – one system lists location first, another time first, and they throw errors. Translators can be built with AI, but that adds cost and complexity. Standards are essential at the interface between systems to ensure innovation can happen independently yet still connect.
Dr. Cowin: Do you believe human oversight is still necessary with all this automation?
Wolfgang Lehmacher: Absolutely. Machines can fail and cannot be held accountable. Humans can. We are seeing attempts to delegate accountability to machines—especially with AI agents—but I strongly oppose this. I don’t collaborate with AI. I use it. It’s a tool, like my mobile phone. The moment something goes wrong, it’s a human who must answer for it.
Dr. Cowin: What skills and mindsets do you look for in the next generation of logistics professionals?
Wolfgang Lehmacher: Curiosity. Self-sufficiency. Critical thinking. The ability to learn, unlearn, and relearn. Knowing how machines work is still a huge asset. I’m still benefiting from having learned MS-DOS. Understanding the logic of systems – like programming or languages – shapes your thinking and helps you adapt in a fast-changing world.
Dr. Cowin: What’s the most important thing you’ve learned in your career?
Wolfgang Lehmacher: How to learn. That changed everything for me. Learning isn’t just a phase to get through school. It’s a life skill – your mental toolkit. I set up learning environments for myself, habits and spaces where I could focus and grow. That mindset, combined with curiosity and openness, has allowed me to reinvent myself again and again.
Logistics, Accountability, and the Ethics of Adaptation
In light of Wolfgang Lehmacher’s insights, the author is reminded of Aristotle’s Nicomachean Ethics and its elevation of phronesis – practical wisdom – essential in navigating uncertain, real-world conditions. Lehmacher’s shift in metaphor from orchestra to jazz combo highlights the pressures facing today’s logistics professionals, who must navigate ethical decision-making within complex systems shaped by fragmentation and algorithmic influence. His emphasis on human accountability and resistance to delegating moral agency to machines resonates with Aristotle’s view that “…Prudence includes a knowledge of particular facts, and this is derived from experience, which a young man does not a possess; [6] for experience is the fruit of years.48.” In this light, prudence is not a static trait but a cultivated capacity to make sound decisions in flux—a mindset closely aligned with Lehmacher’s call for curiosity, critical thinking, and lifelong learning in an increasingly volatile world.
Glossary of Key Terms
- Accountability: The principle that humans—rather than autonomous systems—remain responsible for logistical decisions and outcomes, especially when technologies malfunction or ethical dilemmas arise.
- AI (Artificial Intelligence): Advanced computational methods and algorithms that mimic human-like decision-making, enabling tasks such as demand forecasting, route optimization, and real-time problem-solving.
- APIs (Application Programming Interfaces): Tools and protocols that enable different software applications to communicate and share data. APIs streamline processes by creating consistent, direct lines of data exchange.
- Automation and Autonomous Supply Chains: Logistics systems in which many functions—warehousing, routing, and even decision-making—are performed by AI-driven robots or software, reducing manual intervention.
- Digital Twins: Virtual models that replicate real-world supply chain components, such as warehouses or entire networks. They allow businesses to test and refine strategies before actual deployment.
- Dual-Use Classification: A term that highlights goods or technologies that can be used for both civilian and military applications. Such classifications can halt or delay shipments due to compliance requirements.
- EDI (Electronic Data Interchange): A standard for exchanging business documents—like purchase orders and invoices—electronically between organizations, reducing paper-based workflows.
- ERP (Enterprise Resource Planning): A software platform that integrates core business processes—from finance to production—into a single system, ensuring internal operational coherence.
- Forecasting: The practice of using data analysis and predictive techniques to anticipate future trends—such as demand surges or logistical bottlenecks—in order to optimize operations.
- Fragmentation: Refers to the division of supply chains into multiple, often incompatible systems or processes. This hampers seamless data exchange and increases complexity.
- Interoperability: The ability of different systems or organizations to communicate and work together effectively. In logistics, it involves standardizing data formats, protocols, and processes so that information flows unimpeded among stakeholders.
- “Jazz Combo” Metaphor: Wolfgang Lehmacher’s analogy suggesting that modern logistics operates like an improvisational jazz group, where multiple independent entities must coordinate in real time for a coherent outcome.
- Predictive Analytics: A branch of data analytics that uses statistical models and machine learning to forecast future events. In logistics, it aims to anticipate potential disruptions and demand fluctuations.
- “Shadow Fleet”: Refers to unsanctioned or informal maritime networks (e.g., Russian shipping operations) operating outside mainstream data-sharing channels, complicating global logistics visibility.
- Standards (Communication Standards): Agreed-upon data formats, protocols, or guidelines that ensure different systems and stakeholders can interact smoothly. Without common standards, interoperability suffers.
- TMS (Transportation Management System): A system that organizes and executes the physical movement of goods, covering route planning, carrier selection, freight rating, and shipment visibility.
- WMS (Warehouse Management System): Software designed to manage daily warehouse operations, including inventory tracking, order picking, and shipping. It plays a key role in optimizing storage and workflow within a facility.
Further reading
- Carbone, J. (2022, May 12). Supply Chain Interoperability: Its Meaning, Its Challenges, and How to Overcome Them. Vector. Retrieved from https://www.withvector.com/blog/supply-chain-interoperability-its-meaning-its-challenges-and-how-to-overcome-them/
- World Economic Forum. (2017). Impact of the Fourth Industrial Revolution on Supply Chains. [White paper authored by Wolfgang Lehmacher and colleagues]. Geneva, Switzerland: World Economic Forum. Retrieved from https://www3.weforum.org/docs/WEF_Impact_of_the_Fourth_Industrial_Revolution_on_Supply_Chains.pdf
- Lehmacher, W., & Padilla-Taylor, E. (2019). The New Silk Roads: Logistics in the Belt and Road Initiative.
Journal of Supply Chain Management & Logistics, 12(2), 43–59. - Lehmacher, W. (2017). The global supply chain: How technology and circular thinking transform our future (Softcover reprint of the original 1st ed.). Springer. on Amazon
- Lind, M., Lehmacher, W., & Ward, R. (Eds.). (2023). Maritime decarbonization: Practical tools, case studies and decarbonization enablers [Kindle edition].
- Lester, A. (2021, Oct 8). EDI vs. API in the Modern Supply Chain. Four Kites. Retrieved from https://www.fourkites.com/blogs/api-vs-edi-in-the-modern-supply-chain/
- McClure, R. (2025, Jan 6). Securing Data Interoperability in the Supply Chain: Can the Government Make for Better Results? Supply Chain Tech Insights. Retrieved from https://sctechinsights.com/securing-data-interoperability-in-the-supply-chain-can-the-government-make-for-better-results/
- Savills (2024, Aug 15). Future impact of AI on the supply chain: A game changer in the making? The Savills Blog. Retrieved from https://www.savills.us/blog/article/365509/us-articles/future-impact-of-ai-on-the-supply-chain–a-game-changer-in-the-making.aspx
Dr. Jasmin (Bey) Cowin, a columnist for Stankevicius, employs the ethical framework of Nicomachean Ethics to examine how AI and emerging technologies shape human potential. Her analysis explores the risks and opportunities that arise from tech trends, offering personal perspectives on the interplay between innovation and ethical values. Connect with her on LinkedIn.
