SUSTAINABILITY
HARNESSING THE POWER OF DATA
Andrew Curry, Head of Client Services at Trident Utilities, explains how harnessing the power of data can cut energy bills and improve efficiencies
D
ata is everywhere and with artificial intelligence (AI) constantly at the top of the news agenda, industry is looking
at ways to digitalise and harness the power of data to bring about productivity, efficiency and budget gains. Manufacturers and engineering companies are starting to integrate new technologies and processes, and many have the data they need, but there is a lack of understanding of how to use it effectively. For many of these SMEs one of the most valuable applications, especially for energy- intensive industries, lies in energy management. With continued cost pressures from unstable energy prices, staffing costs, disrupted supply chains and squeezed margins, using data to better understand, control and optimise energy use can instantly affect the bottom line. As energy is often the second highest controllable cost after labour it’s one of the fastest areas to deliver measurable savings.
Understanding energy wastage They say the cheapest kWh is the one you don’t use, so understanding when and where energy is being consumed and wasted is key. Traditionally energy management was a reactive task, reviewing invoices or analysing spreadsheets to understand usage and spot potential anomalies. But the large-scale use of half-hourly meters means companies have real-time, accurate information, often across multiple sites, which can be used to calculate daily usage patterns and create a yearly profile. If this data is analysed correctly, this enables business leaders to better understand the relationship between operational activity and energy demand.
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What’s more it can help identify energy anomalies and potential wastage. Is a manufacturing line, only in use from midday, using full energy consumption from 9am when staff arrive on site and switch
everything on? Or is the air conditioning on in an unoccupied room?
Using temporary clamp on meters, sub meters,
pressure sensors and sensors installed at circuit or equipment level take this a step further, generating huge amounts of valuable, live data. These can also trigger real-time alerts if usage spikes. This level of visibility often uncovers hidden waste, from baseload creep to equipment cycling that would otherwise go unnoticed for months or even years. For food processing plants for example, operating continuous refrigeration and production equipment, even small spikes can have a significant impact on overall energy costs over time. Having and understanding these data patterns helps businesses make more informed operational decisions, improving energy efficiency without compromising production. Having all this data means businesses can be
far more proactive in their energy management. It can be used to benchmark performances, detect variation between sites and/or lines and identify opportunities for cost savings. Things that would once have been hidden or missed within operational data can now be seen and acted upon in a timely manner. And while an engineer might listen and feel there’s an issue with a piece of equipment, data takes the guesswork away and can help inform pre-planned maintenance, minimising downtime.
AI doesn’t replace human
expertise, it enhances it, giving teams the insight they need to act faster and with greater confidence
PROCESS & CONTROL ENGINEERING | OCTOBER 2026 ”
Benchmarking also helps identify best performing sites or lines, allowing successful practices to be replicated across the estate.
The role of AI
AI can take this a step further, digesting and analysing data quickly and efficiently while reducing the current administrative burden on employees. One of its greatest strengths is in bringing together different forms of data, for example, energy use with shift patterns overlayed with site layouts. Rather than just analysing energy consumption in one area, AI can combine data down to the number of staff on shift, production schedules and room use dimensions to create a full operational picture. AI doesn’t replace human expertise, it enhances it, giving teams the insight they need to act faster and with greater confidence. Understanding these data patterns means business leaders can make more informed operational and investment decisions while improving energy efficiency and saving money. Data is changing how industry monitors energy use. Instead of relying on monthly reports or bills, businesses can now access real-time information on consumption and costs, often remotely. This insight helps leaders make confident, informed decisions about processes, maintenance and investment. Historical and live data can also support predictive modelling, producing more accurate forecasts of future energy use to guide planned expenditure and budgeting. AI can add further value by combining energy data with staffing costs and revenue projections to assess the viability of new lines or sites. This level of forecasting reduces budgeting uncertainty, turning energy from a volatile cost into one that can be actively managed. Ultimately, data gives businesses control. Those who harness it will cut waste, reduce costs, strengthen margins and build the operational resilience needed to thrive in an unpredictable energy landscape.
Trident Utilities
tridentutilities.co.uk
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