Article | October 8, 2026
Many executives still face the same uncomfortable question: why doesn’t more technology automatically translate into faster decisions, lower risk and better margins?
The answer is becoming clearer. The next performance gap in manufacturing will be shaped less by who buys the most automation and more by who connects operations well enough to make automation useful at scale.
Manufacturing leaders aren’t underinvesting in technology. Deloitte’s 2026 manufacturing outlook says 80% of surveyed manufacturing executives plan to allocate at least 20% of their improvement budgets to smart manufacturing, including automation hardware, analytics, sensors and cloud computing.
The risk is that automation within a fragmented enterprise might reinforce the fragmentation: a line becomes more efficient (but planning still waits for stale data); maintenance teams predict failures (but procurement can’t see the same risk signal); a factory improves throughput (but customer service still can’t provide reliable delivery updates).
This is why Gartner’s 2025 survey finding is important: 66% of manufacturing and supply chain leaders cited integrating supply chain and manufacturing as their premier challenge over the next 3 years.
Each new project has a defensible business case:
But value drains away when data, workflows and accountability don’t align. Too often advanced manufacturing initiatives are often pursued in silos, without business-driven prioritization, outcome measurement or stakeholder agreement, leading to duplication and technology debt.
For C-suite leaders, the strategic “More automation?” question is superseded by, “Where are decisions hindered by disconnection?” Those decision points are where integration pays off first: engineering changes that don’t smoothly reach production, supplier interruptions that aren’t visible early enough or quality issues that don’t feed back into design.
The World Economic Forum’s Global Lighthouse Network now includes 201 leading production facilities and value chains. Its latest cohort uses digital technologies at scale to improve productivity, supply chain resilience, sustainability, talent and customer centricity. The key lesson is that these gains are described as holistic transformation, not isolated automation.
Crucially, the connected factory is both a management model and a technology architecture. It links product design, production, logistics, field service, finance and workforce planning around shared information. In practice, it gives executives a more dependable view of capacity, constraints, risk and customer impact.
AI makes this more urgent. If production data, enterprise data and supplier data sit in separate worlds, AI may generate telling insights while struggling to influence choices that drive revenue, costs or endurance.
At Lockheed Martin Aeronautics, a next-gen manufacturing execution system tied to the digital thread has become central to modernizing the shop floor for advanced aircraft production. The business case focused on improved quality of internally produced and supplier-sourced parts, stronger production engineering, planning, tooling and shop-floor execution, and better data handoff to sustainment.
Gestamp, the automotive metal parts producer, applies the same logic at a global scale. With 115 production sites across 24 countries, the company has focused on improving production, enhancing the working environment and uncovering data-based insights as it moves from robotization toward AI, cloud and broader data-led operations.
At Croda International, the consolidation issue sits in enterprise data. The specialty chemicals manufacturer needed to support global supply chain management, country-specific product safety compliance and business performance dashboards, while improving agility across operations, sales and executive reporting.
GPI shows the commercial upside of establishing a slicker axis. After moving to a unified SAP ERP platform spanning finance, sales, production and planning across Taiwan, the U.S., China and Cambodia, the manufacturer reported 20% quicker data analysis, standardized global operations, speedier order processing and better service resolution.
Bridgestone demonstrates that integration includes the workforce. A modern device model supporting more than 4,000 employees across Latin America cut IT equipment operating costs by 10%, shortened device life cycles and gave employees faster access to AI-ready tools. In production training, a virtual reality environment reduced the use of production machines for training by 30% and cut the training period by 17%.
DXC helped these manufacturers modernize core systems, connect data across functions, improve worker enablement and transform digital investment into verifiable operating outcomes.
The takeaway for leaders is clear: before approving the next wave of automation, map the decisions that most affect margin, resilience and customer confidence. Then integrate the systems, data and teams around those decisions.
That discipline will help manufacturers get more from every robot, every AI model and every transformation dollar.
