What enables manufacturers to thrive in an unpredictable world?
Customer Example
Mazda, Daikin
In an increasingly turbulent world, digital systems help manufacturers patch problems before they happen.
For much of the past century, manufacturing has been shaped by a firm belief in efficiency. The idea? Refine processes, reduce waste and steadily produce more with less. Productivity improvements were pursued via lean protocols and optimisation practices. The model rewarded consistency, so factories were designed around known patterns of demand, steady inputs and long planning cycles.
In modern times that foundation is crumbling. Manufacturers operate in conditions that are uneven compared to those of previous decades. Energy markets fluctuated sharply… while once robust supply chains are fragile. Weather events disrupt logistics networks, labour availability varies. Digital systems – while offering greater connectivity – introduce new vulnerabilities, particularly in cybersecurity and data.
Efficiency still matters, but expectations are changing. Manufacturers pay closer attention to how their operations behave when conditions are less favourable. Uptime, flexibility, response speed and the ability to adjust resources have become part of the conversation. Efficiency now comes with a thick slice of resilience.
Rethinking production
Many factories still rely on systems designed during periods of greater stability, often with fixed maintenance cycles and data stored in operational silos. With these structures it’s harder to understand what is happening across all facilities, suppliers and partners. The fragmentation this causes can lead to decision-making delays and unclear accountability.
In response, manufacturers are introducing interconnected systems that allow equipment and logistics to be monitored together with real-time data. Connected sensors track the health of machinery continuously; cloud-based data platforms provide shared access to information across locations.
Digital models of production environments, sometimes referred to as “digital twins”, let teams test scenarios and understand how changes will affect output or supply needs.
These developments support a clearer, more coherent view of operations. Manufacturers can diagnose issues before they escalate and allocate maintenance where it’s needed most. In sum, it makes them better equipped to cope with unpredictability.
Enabling the shift
To make advanced, data driven manufacturing possible, companies first need a stable and modern digital foundation. This is where transformation projects like those with Mazda Logistics Europe and Daikin Europe come in: they provide the resilient IT backbone that allows emerging technologies to deliver real value.
This shift is illustrated by recent digital transformation projects at Mazda Logistics Europe and Daikin Europe. Mazda Logistics Europe, in partnership with Fujitsu, transitioned from legacy systems to a modern, multi-cloud architecture, migrating 600 systems and implementing advanced security and cost control tools. The result was cost transparency, improved security, and a stable, scalable IT environment supporting Mazda’s Vision 2030 objectives.
Daikin Europe modernized operations across more than 130 sites in 30 countries by moving to a unified hybrid cloud platform on Microsoft Azure, also delivered by Fujitsu. The transformation enabled seamless infrastructure transition with zero business disruption, empowered teams to focus on innovation and sustainability, and resulted in measurable cost savings and strengthened operational resilience. Both projects were built on strong, trust-based partnerships and set new standards for efficiency and agility in manufacturing
Real-time data and predictive systems have also prompted firms to reconsider how they structure work. Some are shifting away from rigid hierarchies of approvals and fixed processes, instead allowing teams more discretion to act quickly when data supports a decision. Others are investing in training so staff can interpret data responsibly and work alongside automated systems.
Efficiency across the supply chain
The shift is not limited to what happens inside the factory. Manufacturers are increasingly examining how efficiency works in the context of suppliers, logistics partners and customers. In a period where disruptions occur far from the point of production, the stability of one company depends on the visibility and behaviour of others in the network.
Research has shown that although many organisations review the resilience of their primary suppliers, fewer examine secondary or tertiary suppliers. This creates potential flash points and trouble spots. A shortage of a small component or a delay at a distant port can stall production even when operations closer to home function well.
Digital supply-chain systems help to improve clarity by providing more granular and up-to-date information, allowing companies to forecast problems earlier and take action. They also encourage collaboration: suppliers and manufacturers can share information openly.
The future of efficiency
The manufacturing sector is moving away from viewing efficiency purely in the form of internal optimisation. It focuses less on extracting increments of productivity from a stable environment and more on maintaining strong performance when the environment shifts.
Traditional efficiency isn’t obsolete: the fundamentals of reducing waste, maintaining quality and aligning production with demand all remain. But the context has changed in which these fundamentals are applied. Efficiency is about the capacity to adapt.
The shift is taking place through adjustments to infrastructure, changes to the way data is shared, updated maintenance practices and careful investment in the workforce. Manufacturers that are pursuing it most effectively are those that treat it as a continuous process rather than a discrete project.
It’s a more dynamic, responsive production sector based on regular, fresh information. Maintenance is guided by emerging conditions and educated predictions, less so schedules. Supply planning reflects potential disruptions; teams work with systems that support sound judgments.
Manufacturing’s approach to efficiency has broadened in recent years. The measure of success is not simply output at the lowest cost, but also continuity and resilience over time.
What’s next?
Over the next decade, AI-driven technologies and digital twins are poised to deliver measurable efficiency gains in manufacturing, not just in theory but in real applications today.
A recent report from Gartner indicates that three-quarters of companies adopting IoT have already incorporated digital twins into their operations or intend to do so within the next year. The digital-twin market is projected to surge to $48.2 billion by 2026, reflecting an impressive 58% compound annual growth rate.
Manufacturers using digital twins have seen up to 30% reductions in machine downtime and maintenance cost savings through predictive alerts and real-time simulation.
AI’s role will expand beyond single factories to end-to-end supply chains. McKinsey analysis shows that digital twins combined with predictive AI can boost production output by 15-20% and improve forecast accuracy, enabling smarter routing and inventory decisions.
In practice, advanced predictive maintenance models, such as those using machine learning to forecast faults well before they occur, are already reducing downtime and extending equipment life, strengthening resilience while cutting costs.
As manufacturers adopt interoperable data platforms and AI analytics at scale, they will shift from reacting to issues toward proactive optimisation, real-world testing and continuous improvement – with ROI potential within a few years of deployment.
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