Maintenance Matters Focus on: Plant & Asset Management 14 | Plant & Works Engineering www.pwemag.co.uk Annual Buyers’ Guide 2026 Structured asset data - the quiet catalyst reshaping maintenance performance Manufacturing has never been a gentle environment for assets. Heat, vibration, dust, load cycles and production pressures all conspire to shorten lifespans and complicate planning. Yet most engineering and maintenance teams are still working without the depth of information they need. One recent report found that almost one third of firms in Europe still rely on spreadsheets, and more than 40% depend on paper-based checklists. It places teams on the back foot, reacting to issues rather than influencing performance. Digitalisation is often discussed in grand terms, but the truth is more grounded. Structured asset data does not need to be complicated to be transformative. Once you collect reliable information on the condition, criticality and lifecycle of equipment, you unlock a level of operational clarity that no reactive or time-based maintenance regime can compete with. For organisations under pressure to improve uptime, reduce risk and control cost, this shift is essential. The pyramid model of asset management provides a helpful way to think about it. It starts with strategy, builds through maintenance methodology, and peaks with continuous management. Each layer requires good data to stand up, yet most organisations try to build the upper layers on foundations that are not stable. Structured asset data strengthens each stage of this pyramid, and creating a dependable dataset is becoming the most practical route to better reliability and reduced cost. Building the strategic base Every engineering leader wants the same thing: fewer failures, fewer surprises, more predictable performance and a better handle on cost. The challenge is knowing which actions will make the greatest impact. Without structured data, strategy falls back on instinct, familiarity or historic expectations. That makes it difficult to balance cost, risk and operational performance in a consistent way. The base of the asset management pyramid asks a simple question: what are we trying to achieve and what do the assets need to deliver? A production line running three shifts a day has a very different risk appetite to a lightly used administrative building. A heat-intensive process plant will wear components at a pace that bears little resemblance to manufacturer guidance. During the strategic phase, the aim is to understand the real operating context. This includes failure modes, environmental conditions, business priorities, compliance requirements and resource constraints. Doing this well requires a reliable dataset. It gives you clarity on which assets drive your cost base, which create the most disruption when they fail, and which represent realistic opportunities for improvement. By bringing performance, cost and risk into one view, leaders can set maintenance strategies that support wider business aims, whether that is carbon reduction, productivity, safety, compliance or a mix of all four. Structured data helps to test assumptions and exposes areas where longheld practices may no longer serve the organisation. Turning strategy into maintenance plans Once the strategy is set, the next layer of the pyramid focuses on implementation. This is where structured asset data becomes a practical benefit to engineers on the ground. Over the past year, I’ve worked with a national utilities company to help them move from a time-based approach towards predictive, riskled maintenance. The team surveyed 28,500 assets, generating more than 280,000 data points. Each asset was assessed for condition, criticality, lifecycle stage and performance. The data was then verified, cleaned and analysed to build a complete picture of the estate. With a unified dataset, our customer could see where maintenance effort was misaligned with risk. Some assets received scheduled checks far more often than their operational importance justified. Others were critical to resilience but lacked clear lifecycle information or had outdated profiles that underestimated their likelihood of failure. By adopting a risk-based methodology, the utilities company reduced the time required for planned maintenance by 35 per cent. That time was redirected to tasks that actually influenced performance, such as root cause investigations, targeted inspections and improvement works. This proves an important point. Digitalisation is not about collecting data for the sake of it. It is about creating a dataset that gives you the Matt Kent, Director at engineering at EMCOR UK, explores how structured asset data strengthens each stage of the asset management pyramid, and why creating a dependable dataset is becoming the most practical route to better reliability and reduced cost. Matt Kent, Director at engineering at EMCOR UK
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