Key takeaways
- UK commodity chemical production is contracting – 87% of companies expect at least a year of weak business.
- The growth is in speciality chemicals, which demands agile batch processing and real-time operational visibility.
- The bottleneck isn’t the chemistry or the equipment – it’s disconnected operational data.
- Connecting existing systems into a single source of intelligence is faster, cheaper and less disruptive than replacing them.
Why does this matter now?
The UK’s commodity chemical sector is under serious pressure. Output is down 30% compared with 2019. In the last 12 months alone, three significant sources of production capacity have been lost or scheduled for closure in 2026: ExxonMobil’s Fife Ethylene Plant (FEP), SABIC’s Olefins 6 cracker plant on Teesside, and Dow’s siloxanes operation in Barry.
The Chemical Industries Association’s (CIA) most recent business survey is blunt: 87% of UK chemical companies expect at least a year of weak business ahead, and headcount is falling – 38% reported a decrease in the final quarter of 2025. The commodity model, built on high volume, low margins and energy-intensive production, is being undercut by cheaper operations in China, the Middle East and North America, and is under significant pressure with the downturn of hydrocarbon output from the North Sea.
The competitive ground is shifting beneath manufacturers who have relied on commodity for decades. Higher-value, higher-complexity speciality production offers stronger margins and a more defensible market position, but only if your plant can actually deliver it.
However, whether you can do this competitively depends on the capabilities of your digital infrastructure.
How do disconnected systems become the bottleneck?
Most chemical plants aren’t short of data or technology. SCADA systems monitor your processes; data historians archive your operational records; batch management tracks your production. Quality data gets recorded, and maintenance teams follow their own schedules.
The problem is that these systems often exist in silos – a spreadsheet here, another one there; teams using entirely different systems, with no communication between departments. As a result, your data historian doesn’t feed your batch management system, quality results aren’t visible to the production team in real time, maintenance has no line of sight into what production is planning, and production can’t see what maintenance has flagged. The data exists across your operation, but it doesn’t connect – meaning people fill in the gaps based on what they think and make decisions without seeing the full picture.
When you’re running commodity production – one process, one product, shift after shift – you can live with those gaps to a degree: the process is stable enough and the pace predictable enough that manual workarounds hold without disrupting operations. But when you’re switching recipes, adjusting batch sizes, meeting tighter quality tolerances, proving full material genealogy and traceability to a customer or a regulator, those same gaps compound. Each disconnected system adds time, adds risk, and adds cost.
For example, a recipe change that should take minutes takes hours because three systems need updating manually, or a maintenance intervention clashes with a production run because nobody could see the conflict in advance. These aren’t merely hypothetical scenarios – they’re the operational reality in plants where the systems were never designed to work together.
Research from EY found that fewer than one in four chemical companies that invest in digital innovation succeed in scaling it beyond pilot stage. A significant factor is infrastructure: 40% of companies cite the challenge of integrating new digital tools with existing operational technology (OT) – the systems that actually run the plant floor.
The answer, in most cases, isn’t more technology. It’s making the technology you already have work as a connected whole.
What does connected intelligence look like in practice?
This is the challenge that Real-Time Information Systems (RtIS) are designed to solve. The AVEVA PI System – the platform most industrial operators rely on for real-time data management – takes operational data from all kinds of sources and structures it into a single, reliable data infrastructure. It doesn’t replace existing systems, but connects them, turning fragmented, siloed data into a unified, trustworthy picture of what’s really happening across your operation.
When CEMEX implemented the PI System, they were able to reduce data extraction times for their 70 sites from 740 hours to less than one, enabling dynamic comparison between sites and processes that were previously managed individually. This paved the way for shifting their classic commodity model (~90% of the business) towards speciality manufacturing, introducing complex chemicals to the process such as superplasticizers, accelerators and retarders.
At ITI Group, our RtIS engineers have been working with the AVEVA PI System for over 20 years. We’re an AVEVA Endorsed Operations Systems Integrator – AVEVA’s highest partner level, awarded to organisations that have met their most demanding standards for expertise, proven delivery and customer service.
What this means for your plant is practical and measurable. Real-time data from your existing infrastructure becomes operational truth you can trust, rather than a number on a screen that might be two hours old. Analytics pre-empt issues before they reach production, and unified visualisation gives your people faster, better-informed decisions from control room to boardroom, without waiting for a report that’s already out of date by the time it arrives.
Bridgestone, Goodyear and Michelin all deployed the PI System to start capturing these types of efficiencies. Michelin saved €4M in just one year by developing easy-to-use real time tools for plant operators to track complex processes, enabling one plant to recover from a 2,000-ton material disruption within six months. Later they incorporated Braincube, which used the fine-grained real-time data to create genealogies for their materials – tracing raw materials batch-by-batch, moment-by-moment right through to final product, reducing material waste and adapting their processes in real-time, saving $1M annually.
“Seeing a 35% waste reduction so quickly was eye-opening. It showed us how much potential we had been leaving on the table.” – Operations Director.
We’ve written before about why getting your data foundations right is the essential first step – whether you’re preparing for AI implementation, digital transformation, or simply trying to get more from the systems you’ve already invested in. The same principle applies here. Before you invest in new capability, make sure your existing data infrastructure is connected, secure and fit for purpose.
Is your plant ready for what’s coming next?
The shift towards speciality production is already under way, driven by market pressures that show no sign of reversing. For most UK chemical manufacturers, the question isn’t whether to adapt – it’s how to do it without disrupting what’s already working.
And the starting point is simpler than it might seem. The first question isn’t what new technology you need. It’s whether the systems you’ve already invested in are connected well enough to support the flexibility that speciality demands. If the answer is no – and in many plants, it is – the gap is more bridgeable than you might think. It starts with the data infrastructure you already have, and it starts with making it visible to the people and processes that depend on it.
Most chemical plants have the technology they need. What they don’t have is a connected view of what that technology is telling them. That’s the gap, and it’s the one that matters most.
Talk to our RtIS team about getting your plant ready for what’s coming next