Maintenance Matters Focus on: Plant & Asset Management 16 | Plant & Works Engineering www.pwemag.co.uk April/May 2025 Why smart asset management is no longer optional As industrial sectors face rising costs, labour shortages, and growing sustainability pressures, smart asset management has become essential. By using data-driven strategies, companies can improve reliability, reduce downtime, and enhance cost-efficiency, while also supporting compliance and sustainability goals. Adopting these approaches is crucial for overcoming today’s operational challenges. Matt Kent, director of engineering at EMCOR UK explains further. Maintenance strategies across the industrial sector are undergoing a fundamental shift, driven by rising costs, labour shortages, and the growing role of technology. A recent maintenance trends recap found that 74% of maintenance managers now consider preventive and predictive maintenance to be essential to operational success - an increase of 14% in just two years. Yet, despite this progress, nearly 60% of companies still struggle with unplanned downtime, often due to insufficient data or outdated maintenance strategies. Compounding these challenges is a shortage of skilled workers, cited by over half of respondents as their biggest obstacle in the years ahead. The need to nurture the next generation of engineers is a subject that I’m passionate about as our industry has historically lacked apprenticeship opportunities and longterm skills-based work. In support of this, we are working closely with our industry professional bodies to further professionalise our workforce to help attract, train and retain the very best engineers. Sustainability is also becoming a key driver of asset management: 42% of maintenance professionals say environmental concerns are influencing their approach, prompting a shift towards smarter, more energy-efficient practices. Against this backdrop, manufacturers are looking for intelligent, data-driven solutions that not only extend asset life and reduce downtime, but also support compliance, costefficiency and carbon reduction goals. Asset management has therefore never been more important, or indeed more complex. But this complexity is exactly why we need to embrace a smarter way of working. In industrial environments where uptime is critical, and margins are under constant pressure, managing assets strategically is no longer a nice-to-have - it’s a necessity. Traditional maintenance models, whether reactive or based on fixed intervals, often miss the mark. They can drive up costs, increase risk, and fall short on compliance and sustainability. Instead, engineering leaders across manufacturing and processing sectors are turning to smart asset management. This dataled approach doesn’t just fix problems faster - it aims to prevent them altogether, improves decision-making, and aligns engineering performance with wider business goals. Understanding today’s pressures From food processing plants to chemical manufacturing facilities, many of the customers we support at are grappling with similar challenges. These include aging infrastructure and increasingly complex estates, fragmented data spread across disconnected systems and spreadsheets, and mounting expectations to increase reliability, reduce costs, and support ESG targets. Without a clear understanding of asset condition and criticality, it’s hard to know what to fix, upgrade or retire - let alone when or how. And in high-risk environments, a single point of failure can mean lost production, safety concerns, or non-compliance. Moving to a smarter model A smart asset management strategy puts data and engineering intelligence at its core. The goal is to answer key questions with clarity: What do I own? What condition is it in? What’s the impact if it fails? |What’s the most effective maintenance or replacement plan? It starts by building a digital asset register, populated with sufficient data attributes, consolidating data from across the estate into a single, secure source of truth. From there, organisations can apply modelling, predictive analytics and lifecycle insights to shift from, for example, time-based to condition-based or business Focused maintenance. A great example of this approach in action is our work with a global energy tech company which faced the challenge of managing real estate performance across five countries and 11 unstandardised data sources. By consolidating this into EMCOR UK’s One Data World platform, the customer gained a single source of truth for asset performance, compliance, and cost tracking. Key results included £500k in guaranteed annual savings, a 98% compliance rating, over 100 users collaborating across UK and European sites, and more than 30 efficiency and compliance improvements identified. This kind of transformation doesn’t require starting from scratch - it just needs a clear strategy, the right expertise, and scalable tools. Getting started: Building the foundations For engineering leaders wondering where to begin, the following steps are a good starting point: 1. Assess what you know: Conduct a gap analysis of your current asset data, systems and maintenance practices. 2. Define criticality: Identify which assets have the biggest impact on operations, safety or compliance. Where are the Single Points of Failure (SPoF)? 3. Align your goals: Link your asset strategy to broader objectives - such as reducing energy use, increasing uptime, or preparing for ESG audits.
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