Utilities generate vast amounts of operational data, but much of it remains trapped in disconnected systems. A unified data strategy can improve operational efficiency, simplify regulatory compliance and support decarbonisation goals, argues Krzysztof Kubosz, Product Manager – SolutionsPT.
Utilities have never had access to more data, yet despite the abundance many organisations are finding it hard to draw insights and improve operations.
Data is often locked inside legacy systems, isolated between operational teams or spread across geographically separate sites, making it difficult to build a complete operational picture.
Traditionally, utilities have deployed site-specific systems to solve individual operational challenges, responding to immediate needs with site-specific systems for monitoring, reporting, compliance or other specific tasks. Over time this has led to a fragmented landscape, creating disconnected HMI, SCADA and reporting systems that rarely share context with one another. The data exists but lacks context for meaningful insight and improvement.
As the utilities sector is critical for public safety, regulatory frameworks have prioritised reliability. Again, this has led to systems being in place for decades, slowing the evolution of how data is managed when compared to other sectors. For example, the drive for profit in manufacturing has led to investment in data architectures that provide context to data so that different sites, applications and lines can be analysed against one another and historic performance.
Ultimately this creates a gap for utilities where they are data rich but insight poor. This gap will only become harder to ignore as the population grows and challenges increase.
The growing regulatory focus on operational transparency highlights the importance of reliable, accessible operational data.
For example Ofgem is launching an independent enquiry into the National Energy System Operator’s (NESO) operational decision making and record keeping to determine if NESO complied with relevant security standards and followed correct procedures during recent extreme heatwaves. Similarly, UK water companies are under pressure from Ofwat to reduce pollution incidents, improve operational resilience and measure improvements.
Ageing infrastructure under growing pressure
In the UK water sector alone, many treatment works, pumping stations and sewer networks were built several decades ago and are now expected to cope with larger populations, more extreme weather and increasingly stringent environmental standards. Although these assets may be performing their core function to acceptable standards, operators may lack visibility to monitor, control and optimise them in line with increasing demand.
Lack of data in these cases can leave utilities short of evidence when justifying investment to regulators, or when evaluating how their proactive approach to sustainability is on track to meet Net Zero targets.
Collection to contextualisation
Just as aging assets are holding utilities back, the traditional approach to data management keeps providers focused on collection only. It is usual practice for SCADA systems to capture the real-time data, historians then store it and reporting tools present it. While it may seem on the surface that this provides necessary visibility, it does not provide understanding, especially when the volume of data is increasing fast across multiple disconnected HMI systems.
This limits utilities as they look to adopt more advanced capabilities, for example using AI tools to identify efficiency improvements. These rely on the ability to interpret patterns across live and historical data and multiple sites. Even the most sophisticated AI tools struggle when operational data is fragmented or inconsistently structured. So even if utility companies are investing in advanced technology and connecting previously siloed systems to increase data flow, the burden will still remain on the human operator.
Addressing this requires utilities to move from simple data collection to contextualisation. This means that data from across disparate assets must be embedded within a consistent framework. By defining assets in terms of type, role, age and location, utilities can make sure that data is not only available but meaningful. This allows insights learnt to be applied across multiple sites and networks.
Unified data strategy
Contextualising data in utilities is a critical step in a unified data strategy. Rather than the traditional way of introducing another technology layer on top, it focuses on connecting what already exists which is crucial whenever there is a mix of new and legacy equipment.
A unified data strategy creates a single view across assets in different locations, multiple controls systems and previously siloed functions. Treatment works, pumping stations and power network infrastructure will all have elements that work independently but where performance is connected to other parts of operations.
A recent example is LondonEnergy’s £1.2 billion EcoPark South redevelopment. During the redevelopment, engineering systems integrator March implemented an AVEVA System Platform with support from SolutionsPT to unify more than 50 disparate subsystems under one unified digital infrastructure. Real-time data now drives decision-making across energy usage, odour management, equipment health, and traffic control within the plant. LondonEnergy expects to recover between £150,000 and £200,000 annually through energy optimisations alone.
Furthermore, a unified view of data will provide an accurate baseline for recording and measuring progress against emissions benchmarks. In turn utilities can have greater confidence in sustainability targets.
Connecting systems with purpose
Utilities are not lacking in data, but what they do lack is data structure and strategy. The sector has deployed isolated systems in reaction to evolving needs, but this is no longer effective for modern utilities.
Moving forward is not about replacing everything that exists but connecting systems with purpose. Utilities that employ a unified data strategy can transform operations, unlock insight and streamline regulatory compliance. As the sector continues to serve a growing population with increasing needs, the companies that treat data as a strategic asset will be best positioned for future challenges.
