Managing complexity: Trade-offs, standardization, and the limits of technology
Holbach is direct about the challenge facing supply chain leaders today: the agenda keeps expanding while resources do not. Digitalization, resilience, sustainability, and organizational integration all compete for attention simultaneously. “The list of priorities is not only getting longer – everything is becoming more important. That is not manageable without disciplined trade-offs.”
A less visible but equally powerful driver of supply chain complexity is corporate strategy itself. Holbach points to the acceleration of M&A activity across industries – driven by low multiples, strong balance sheets, and the rising cost of organic growth – as a force that continuously resets supply chain requirements. Verticalization, portfolio consolidation, and scaling decisions all impose immediate operational consequences. “You have to continuously review and align your supply chain strategy and your system setup – where you produce, how you distribute,” says Holbach. Henkel itself recently announced a major acquisition in its adhesives business, a reminder that physical supply networks take years to reconfigure regardless of how quickly the deal closes. This is why supply chain integration with business strategy consistently ranks as the top concern in the IMD survey: “It is not a static design problem, but a moving target.”
Henkel’s response is to build for adaptability rather than optimize for any single configuration, operationalized through a limited set of enterprise-wide transformation programs spanning plan, source, make, and deliver – with defined checkpoints to recalibrate. Platform-based architecture supports scale without sacrificing flexibility. A single cloud-based global Manufacturing Execution System (MES) backbone enforces standardization and deployment speed, and mandatory capabilities set a performance baseline; optional modules allow local teams to capture incremental value. Holbach calls this “freedom within a frame.”
On technology, his position is measured. Current AI applications focus on targeted use cases: manufacturing problem-solving, cost-to-serve analytics, and selective decision support. Large-scale automation in planning or customer service is less compelling than it might appear. With 60% of Henkel’s customer service and planning teams already located in lower-cost locations, the incremental efficiency gain from replacing those roles with AI is limited. “We are still in the hype cycle. There is value – but not yet at scale.” The priority is architecture and data readiness, not deployment for its own sake.
He also highlights cybersecurity as a structurally underweighted risk, organizing it across three domains: information and data security, manufacturing site continuity, and upstream supply security. Each requires distinct governance, and few organizations have addressed all three with equal rigor.