Article | September 10, 2026

A digital thread starts on the factory floor 

Manufacturers are continuing to invest in smart factories, AI, digital twins and automation.

Which is all well and good, but will those investments create a connected operating model, or simply a set of impressive but isolated capabilities?

The unvarnished truth is that it depends on the manufacturing execution system (MES).

Although MES modernization is often treated as a plant-level software refresh, in reality, it’s a strategic decision. MES determines whether product data, engineering changes, quality events, work instructions and shop-floor activity can move together as a single digital thread.

In Deloitte’s 2026 manufacturing outlook, 80% of surveyed manufacturing executives said they intended to invest at least 20% of their improvement budgets in smart manufacturing initiatives, including automation hardware, data analytics, sensors and cloud computing. Further, Gartner expects manufacturing to be transformed by 2030 through semi-autonomous AI agents, software-defined products and closed-loop digital twins. 

Again, the intention is correct, but without execution, the plan is incomplete. As we know, product lifecycle management (PLM) describes the product, and enterprise resource planning (ERP) plans the enterprise. MES is where the pledge meets the plant, turning designs, orders, materials and schedules into work that operators, machines and quality/maintenance teams can execute.

Typically, when MES is fragmented or outdated, the digital thread frays:

• Engineering changes arrive late.

• Operators work from inconsistent instructions.

• Quality data is trapped in local systems.

• Compliance evidence is rebuilt manually.

Of course, leaders see dashboards, but they can’t always trust the chain of evidence behind them.

A modern MES makes production more predictable, visible and adaptable. It helps reduce friction between planning and execution, replace brittle interfaces, improve traceability and protect margin by reducing rework, scrap and delay.

MES modernization should start with business outcomes, not a systems inventory. Forget mulling over which platform should be upgraded. The key question is “Where does poor execution data slow our ability to deliver, certify, adapt or improve?”

Of course, not every factory should copy aerospace. However, complexity exposes weak data handoffs and when products have long lifecycles, strict regulatory demands, frequent engineering changes or service commitments that last decades, disconnected execution data becomes expensive.

A digital thread creates value when teams are able to understand what happened, why it happened, what changed and what should happen next. MES gives product, planning, machine, quality and service data the operational context required for those decisions.

AI depends on trustworthy execution data

Manufacturers want AI to explain defects, recommend schedule changes, optimize throughput and help workers make better decisions. Those use cases depend on clean, timely and contextualized data from production.

DXC’s smart factory platforms integrate computer vision, predictive analytics and quality monitoring to detect defects earlier, improve workflows and increase consistency. For example, multimodal GenAI was used to create edge-case images and improve an existing computer-vision model for detecting scratches on cars in a manufacturing line.  

DXC Xponential is an enterprise AI orchestration blueprint that connects technology, people and processes from pilot to scale, with governance, accelerators and automation built into the model. MES modernization helps close that gap by giving AI a more consistent view of production and a safer route into workflows where people remain accountable for quality, safety and delivery.

Technology alone won’t create the digital thread, though. Manufacturers need a practical operating model for estates spanning legacy systems, multiple vendors, regulated data and plants with varying maturity levels.

DXC’s work with a global industrial technology company illustrates the wider challenge. DXC supports more than 5,000 servers, 4.5PB of data and nearly 1,000 applications for the customer, including PLM, integrated MES and enterprise asset management systems. The engagement delivered more than a 25% reduction in legacy technical debt and more than a 30% reduction in operating costs. 

MES modernization also depends on infrastructure resilience, cybersecurity, cloud choices, data governance and support models that can work across global operations.

DXC OASIS is relevant because, being an intelligent orchestration platform for mission-critical operations, it brings systems, signals and decisions across the IT estate into a governed, real-time model with agentic AI and human judgment. In manufacturing, that visibility can help leaders move from reactive firefighting toward coordinated action across the systems that keep production moving.

Completing the modernization puzzle

1. Identify the production results that matter most. Does that mean fewer quality escapes, faster engineering changes, stronger schedule adherence, higher uptime, improved traceability or shorter time-to-market? Once decided, map where the digital thread breaks today, from manual rekeying and inconsistent work instructions to disconnected inspection records.
2. Modernize MES around those value streams. Avoid rebuilding old complexity on a newer platform. Standardize where possible, integrate where it matters and protect the local flexibility plants need to run safely and efficiently.
3. Treat AI as an outcome accelerator, not a separate agenda. The strongest AI use cases will be those grounded in trusted execution data and embedded into real workflows.

Smart manufacturing won’t be enriched by the company with the most pilots. It will be advanced by manufacturers that connect strategy to execution, engineering to operations and data to decisions.

MES makes that connection real.