Why smart factory pilots fail in practice. Key takeaways from Subcon 2026 on closing the gap between ambition and execution.

Published: 12 June 2026
Authors: Wei Wu

Summary

Smart factory programmes rarely fail because of weak ambition. They fail when execution drifts away from reality with too many organisations prioritising technology over operational need. That was the message from the Subcon 2026 panel “From pilot to production: Making smart factories work in the real world”, chaired by Shoosmiths’ Wei Wu in Birmingham earlier this month. In this article, we outline some of the key takeaways from the discussion.

Panellists

• Wei Wu, Partner & Manufacturing Sector Lead, Shoosmiths (Chair)
• Claire Robinson, Divisional Director & UK Industry Cluster Lead, Drees & Sommer
• Dr Marco Chacin, Head of Actuators and End Effectors, Airbus
• Russell Watkins, Lean Transformation Expert & Co-founder, Sempai
• Shazan Siddiqi, Automotive Trends Strategist, Advanced Propulsion Centre UK

Where smart factories go wrong

The most consistent issue is also the simplest: projects are built around technology rather than need.

Too many initiatives begin with ambition – full automation, digital twins, end-to-end visibility – without first understanding what is broken. That creates solutions that look impressive but struggle to justify their place on the factory floor.

This misalignment is reinforced during delivery. Transformation programmes are often driven from the centre, by teams tasked with hitting efficiency targets. Yet the detail that determines success sits elsewhere: on the shop floor, within existing processes, and with the people who run them. When those perspectives are missing, pilots translate poorly into live environments.

The result is predictable. Systems that worked in isolation fail to integrate. Business cases begin to stretch. What once looked like a five-year return becomes a 10-year question.

Scaling exposes the truth

The move from pilot to production is where assumptions are tested and usually exposed.

Legacy infrastructure is the first pressure point. Most factories are not built from scratch. They rely on systems that were never designed to connect, let alone share data in real time. Retrofitting becomes necessary, and quickly expensive.

At the same time, the economics shift. Integration costs, operational disruption and ongoing complexity reduce the viability of large-scale rollouts. What seemed viable at pilot stage becomes difficult to justify when applied across an entire site.

There is also a tendency to over-engineer. In trying to future-proof systems, organisations introduce layers of complexity and control that slow delivery. The result is not resilience, but inertia.

Against this backdrop, a more pragmatic view is emerging. The goal is no longer a fully rebuilt, fully connected factory. It is a hybrid environment where new technology sits alongside existing systems, focused on the points that deliver the most value.

What practical transformation looks like

Moving from pilot to production requires a shift in mindset as much as capability.

The strongest programmes begin not with investment decisions, but with operational clarity. They ask direct questions about performance today: where losses occur, how they can be measured, and what the cost of inaction really is. Only then do they consider how technology fits.

This approach changes the nature of the business case. Instead of projecting theoretical returns, it builds from what already exists. Improvements are targeted. Investment is phased. Value becomes visible earlier.

It also forces organisations to confront a less obvious risk: knowledge. In many cases, critical understanding of systems is held by a small number of experienced individuals. As those individuals move on, so does the organisation’s ability to operate, adapt and scale. Without capturing that knowledge, transformation becomes fragile from the outset.

In practice, delivery is rarely linear. It involves coordinating multiple teams, working around systems that cannot be stopped, and improving performance while production continues at pace. That reality cannot be modelled in a spreadsheet. It has to be managed on the ground.

The role of funding and sector pressure

External funding is increasing the level of discipline.

Programmes tied to public investment require organisations to articulate their starting point in detail. It is not enough to present a compelling idea – there must be a clear baseline, a quantified problem and a credible path to value.

This is particularly evident in sectors such as automotive, where innovation is closely linked to broader industry shifts. Manufacturing decisions are no longer driven purely by efficiency. They are shaped by regulation, supply chain resilience and long-term capability.

Battery production is one example. Emerging requirements around material sourcing and traceability are pushing manufacturers to think beyond individual processes. The ability to track inputs, understand origins and demonstrate compliance is becoming as important as production efficiency itself.

That changes the nature of transformation. It is no longer just about making factories smarter. It is about making them fit for a more complex, more scrutinised environment.

Closing the gap

The difference between a successful pilot and a successful rollout comes down to discipline.

Organisations that scale effectively are not the ones that invest the most in new technology. They are the ones that start with a clear understanding of their operations, focus on real problems, and build change around what already works.

They are also prepared to move at the pace reality demands: incremental where needed, decisive where it matters. Smart factories do not fail at scale because the concept is flawed. They fail because execution drifts away from the conditions they were designed for.

Bring it back to those conditions – operational, commercial and human – and production follows.