In the world’s most advanced factories progress rarely stalls for lack of ambition. What gives leaders pause is something more elusive: the difficulty of seeing clearly what others do at the frontier, and how those choices translate into real performance gains in practice.
An electronics manufacturer in China found itself at precisely this juncture. Its operations were already highly automated and data rich, earning its place in the World Economic Forum’s Global Lighthouse Network – a community of leading manufacturing and supply chain sites that demonstrate how advanced technologies can drive not only efficiency and productivity, but also excellence in talent development, sustainability, resilience and customer focus. Yet as new possibilities emerged — from agentic AI to increasingly autonomous decision-making on the shop floor — the question was no longer whether to adopt advanced solutions, but which ones to pursue, and how to do so without fragmenting effort or slowing execution.
Logging into Lumina, the World Economic Forum’s new AI-powered industrial intelligence platform for manufacturing and supply chains, the company gained access to a broad, evidence-based view of how peers across industries were tackling similar challenges in very different ways. Instead of benchmarking narrowly against its own sector, leadership could explore how advanced capabilities were being deployed in pharmaceuticals, automotive, logistics and process industries — often combining technologies, organizational models and workforce practices in unexpected configurations.
In this hypothetical example, cited by Federico Torti, the Forum’s Lead of Technology and Innovation initiatives for the Centre for Advanced Manufacturing and Supply Chains, the expanded “peripheral vision” proved critical. Lumina did not surface a solitary best practice. Instead, it revealed patterns. The manufacturer could see where multi-technology convergence was delivering up to 1.6 times higher productivity impact; how advanced AI applications were embedded into end-to-end workflows rather than confined to pilots; and which capability foundations consistently underpinned success, explained Torti. For an already advanced organization, the value of Lumina is in staying ahead by gaining insights across sectors. “This ability to turn collective experience into practical insight reflects a deliberate evolution underway at the Forum’s Centre for Advanced Manufacturing and Supply Chains and underscores the value of the new Lumina AI intelligence platform,” Torti says.
Lumina is still in the early stages of development but evidence from the Forum’s Global Lighthouse Network shows that organizations drawing on shared intelligence achieve operational gains 25%–50% faster, experience up to eight times less revenue volatility during global shocks, and generate 2–3 times returns over three years, rising to 4–5 times at scale, he says.
From Isolated Excellence to Collective Progress
For more than eight years, the Centre has convened and grown the Global Lighthouse Network. The work initially focused on showcasing what was possible. Over time, the evidence base expanded to nearly 1,200 industrial transformation use cases. The challenge was to transform this into something digestible, so that transformation could be made more repeatable, Torti says.
This attracted a community of industrial leaders — including companies such as Bain, Bosch, Schneider Electric and Foxconn Industrial Internet as well as NEOM, Saudi Arabia’s economic development region— and led to the development of a Lighthouse Operating System (Lighthouse OS). The Forum describes Lighthouse OS as a way of capturing how leading organizations sequence change across technology, people and processes, offering a structured way to assess maturity, identify gaps and prioritize action, grounded in what has worked in practice.
It is in this context that Lumina was developed, says Torti. By bringing together eight years of proprietary transformation data from the Global Lighthouse Network with the Lighthouse OS, Lumina “makes this intelligence usable at scale,” he says. “It is an AI-enabled platform that allows organizations to benchmark performance, explore proven pathways and continuously update their understanding as new transformations are added. Unlike static benchmarks, it is grounded in operational journeys, not scores. By lowering the barrier to learning, Lumina helps shift industrial transformation from isolated excellence to collective progress.”
Bringing Small and Medium-Sized Manufacturers into the Mix
While Lumina is being launched with the support of the Forum’s corporate partners, the ambition is to open access to small and medium-sized companies via its network of affiliate centers, which are hosted by, or collaborate with, governments around the world.
SMEs, which form the backbone of many countries, often don’t know where to start, says Torti. “We are opening the possibility for them to use Lumina to go through a detailed assessment. By understanding a company’s business priorities and where they are in their technology transformation, we can tell them what has been working for lighthouses but also what they should be focusing on first.”
Consider the hypothetical example of a small dairy manufacturer in the Gulf region. Facing rising quality losses, labor constraints and intensifying competition, the company knows it needed to modernize. With limited resources and little margin for trial and error, choosing the wrong starting point could be costly.
Using the Lighthouse OS assessment embedded within Lumina, the company could step back and view its operations through a structured capability lens, says Torti. Rather than focusing first on advanced automation, the assessment would highlight more fundamental priorities: strengthening process stability, improving data capture at the line level, and deploying basic digital quality controls. Lumina could also surface relevant use cases from other SMEs, demonstrating that meaningful improvements could be achieved with lower maturity requirements and reasonable returns on investment.
Crucially, these insights are not theoretical, says Torti. They are grounded in the transformation pathways of companies that had faced similar constraints. Guided by this evidence, the dairy manufacturer used in the example could begin addressing root causes of defects, improving labor productivity and lifting overall equipment effectiveness. Benchmarking against Lumina’s dataset, the company would see that food manufacturers adopting comparable approaches had achieved labor productivity gains averaging over 40 % and Overall Equipment Effectiveness (OEE) improvements exceeding 50 %— well above cross-industry averages, which sit closer to 30% and 36% respectively.
“Lumina is not about prescribing solutions,” Torti says. “It is about giving organizations regardless of size, the clarity to take their next step with confidence, learning from what has already worked across best-in-class industrial operations.”
This article is content that would normally only be available to subscribers. Become a subscriber to see what you have been missing
